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a/previews/PR1171/api/citation/index.html b/previews/PR1171/api/citation/index.html new file mode 100644 index 0000000000..3d62f13b59 --- /dev/null +++ b/previews/PR1171/api/citation/index.html @@ -0,0 +1,12 @@ + +Citation · PowerSystems.jl
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Citation

Users are requested to please cite the following paper:

@article{LARA2021100747,
+title = {PowerSystems.jl — A power system data management package for large scale modeling},
+journal = {SoftwareX},
+volume = {15},
+pages = {100747},
+year = {2021},
+issn = {2352-7110},
+doi = {https://doi.org/10.1016/j.softx.2021.100747},
+url = {https://www.sciencedirect.com/science/article/pii/S2352711021000765},
+author = {José Daniel Lara and Clayton Barrows and Daniel Thom and Dheepak Krishnamurthy and Duncan Callaway},
+keywords = {Power Systems, Julia, Energy},

PowerSystems has been developed as part of the Sienna modeling framework by the U.S. Department of Energy's National Renewable Energy Laboratory (NREL).

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Specifying the type of...

Some fields in PowerSystems.jl are specified with an option from a pre-defined list (Specified with IS.scoped_enums).

Example syntax:

set_fuel!(gen, ThermalFuels.COAL)

These predefined lists are below:

AC Buses

ACBusTypes categorize buses for modeling activities and denote which quantities are specified for load flow calculations. ACBusTypes has the options:

NameDescription
ISOLATEDDisconnected from network
PQActive and reactive power defined (load bus)
PVActive power and voltage magnitude defined (generator bus)
REFReference bus (θ = 0)
SLACKSlack bus

Prime Movers

Each generator contains a field for prime_mover::PrimeMovers, based on the options in EIA form 923. PrimeMovers has the options:

NameDescription
BAEnergy Storage, Battery
BTTurbines Used in a Binary Cycle (including those used for geothermal applications)
CACombined-Cycle – Steam Part
CCCombined-Cycle - Aggregated Plant *augmentation of EIA
CEEnergy Storage, Compressed Air
CPEnergy Storage, Concentrated Solar Power
CSCombined-Cycle Single-Shaft Combustion turbine and steam turbine share a single generator
CTCombined-Cycle Combustion Turbine Part
ESEnergy Storage, Other
FCFuel Cell
FWEnergy Storage, Flywheel
GTCombustion (Gas) Turbine (including jet engine design)
HAHydrokinetic, Axial Flow Turbine
HBHydrokinetic, Wave Buoy
HKHydrokinetic, Other
HYHydraulic Turbine (including turbines associated with delivery of water by pipeline)
ICInternal Combustion (diesel, piston, reciprocating) Engine
PSEnergy Storage, Reversible Hydraulic Turbine (Pumped Storage)
OTOther
STSteam Turbine (including nuclear, geothermal and solar steam; does not include combined-cycle turbine)
PVePhotovoltaic (Note: renaming from EIA PV to PVe to avoid conflict with ACBusType.PV)
WTWind Turbine, Onshore
WSWind Turbine, Offshore

Fuels for Thermal Generators

Each ThermalGen generator has a field for fuel::ThermalFuels where ThermalFuels are intended to reflect the options in the Aggregated Fuel Codes from the EIA Annual Energy Review. ThermalFuels has the options:

NameEIA Fuel CodeDescription
COALCOLAnthracite Coal and Bituminous Coal
WASTE_COALWOCWaste/Other Coal (includes anthracite culm, gob, fine coal, lignite waste, waste coal)
DISTILLATE_FUEL_OILDFODistillate Fuel Oil (Diesel, No. 1, No. 2, and No. 4)
WASTE_OILWOOWaste Oil Kerosene and JetFuel Butane, Propane
PETROLEUM_COKEPCPetroleum Coke
RESIDUAL_FUEL_OILRFOResidual Fuel Oil (No. 5, No. 6 Fuel Oils, and Bunker Oil)
NATURAL_GASNGNatural Gas
OTHER_GASOOGOther Gas and blast furnace gas
NUCLEARNUCNuclear Fission (Uranium, Plutonium, Thorium)
AG_BIPRODUCTORWAgricultural Crop Byproducts/Straw/Energy Crops
MUNICIPAL_WASTEMLGMunicipal Solid Waste – Biogenic component
WOOD_WASTEWWWWood Waste Liquids excluding Black Liquor (BLQ) (Includes red liquor, sludge wood, spent sulfite liquor, and other wood-based liquids)
GEOTHERMALGEOGeothermal
OTHEROTHOther

Energy Storage

StorageTech defines the storage technology used in an energy Storage system, based on the options in EIA form 923. StorageTech has the options:

NameDescription
PTESPumped thermal energy storage
LIBLiON Battery
LABLead Acid Battery
FLWBRedox Flow Battery
SIBSodium Ion Battery
ZIBZinc Ion Battery
HGSHydrogen Gas Storage
LAESLiquid Air Storage
OTHER_CHEMOther Chemical Storage
OTHER_MECHOther Mechanical Storage
OTHER_THERMOther Thermal Storage

Dynamic States

StateTypes are used to denote the type of dynamic equation a specific state is subject to in PowerSimulationsDynamics.jl. StateTypes has the options:

NameDescription
DifferentialState evolves over time via a differential equation $\dot{x} = f(x)$
AlgebraicState evolves over time by satisfying an algebraic equation $0 = g(x)$
HybridDepending on specific parameters, the state can be Differential or Algebraic

Angle Units

AngleUnits can be specified in:

Name
DEGREES
RADIANS
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Glossary and Acronyms

A | D | E | F | H | I | O | P | R | S | V | W | Z

A

  • AC: Alternating current

  • ACE: Area control error

  • AGC: Automatic generation control

  • AVR: Automatic Voltage Regulator

D

  • DC: Direct current

  • DERA1:

  • Dynamic: Refers to data and simulations for power system transient simulations using differential equations. Common examples include signal stability analysis to verify the power system will maintain stability in the few seconds following an unexpected fault or generator trip. For contrast, see the definition for Static data.

E

  • EMF: Electromotive force

  • ESAC: IEEE Type AC Excitation System model

  • ESDC: IEEE Type DC Excitation System model

  • EXAC: IEEE Type AC Excitation System (modified) model

  • EXPIC: Proportional/Integral Excitation System from PSS/E

  • EXST: IEEE Type ST (Static) Excitation System model

  • EX4VSA: IEEE Excitation System for Voltage Security Assessment with Over-Excitation Limits.

F

  • Forecast: Predicted values of a time-varying quantity that commonly features a look-ahead and can have multiple data values representing each time period. This data is used in simulation with receding horizons or data generated from forecasting algorithms. See the article on Time Series Data.

  • Forecast window: Represents the forecasted value starting at a particular initial time. See the article on Time Series Data.

H

  • Horizon: Is the duration of all time steps in one forecast. As of PowerSystems.jl version 4.0, all horizons in PowerSystems.jl are represented as a Dates.Period. For instance, many Day-ahead markets will have an hourly-resolution forecast for the next day, which would have a horizon of Dates.Hour(24) or Dates.Day(1). If the forecast included the next day plus a 24-hour lookahead window, the horizon would be Dates.Hour(48) or Dates.Day(2). See the article on Time Series Data.

  • HVDC: High-voltage DC

I

  • IEEET: IEEE Type I Excitation System.

  • Injector or Injection: Injectors refer to models that represent how a generator or storage device injects power or current into the power system. Loads are negative injectors. In PowerSystems.jl, some components can accept data for both StaticInjection and DynamicInjection models for both static and dynamic modeling.

  • Interval: The period of time between forecast initial times. In PowerSystems.jl all intervals are represented using Dates.Period types. For instance, in a Day-Ahead market simulation, the interval is usually Hour(24).

  • Initial time: The first time-stamp in a forecast window. See the article on Time Series Data.

  • IPC: Interconnecting power converter

O

  • OEL:

P

  • PLL: Phase-locked loop

  • PSS: Power System Stabilizer

  • PSSE or PSS/E: Siemen's PSS®E Power Simulator

  • PPA: Power purchase agreement

  • PSID:

  • PSLF:

  • pu or p.u.: Per-unit

R

  • REECB1:

  • REPCA1:

  • Resolution: The period of time between each discrete value in a time series. All resolutions are represented using Dates.Period types. For instance, a Day-ahead market data set usually has a resolution of Hour(1), a Real-Time market data set usually has a resolution of Minute(5).

S

  • SCRX: Bus Fed or Solid Fed Static Exciter

  • SEXS: Simplified Excitation System model from PSS/E

  • SIL: Surge impedance loading

  • States: Correspond to the set of inputs, outputs or variables, that evolve dynamically in PowerSimulationsDynamics.jl, commonly via a differential-algebraic system of equations. In PowerSystems.jl, a component associated to a DynamicInjector (for example an AVR) specifies the set of states that specific component requires to be modeled accurately.

  • Static: Typically refers to steady state data or models where the power system and each of its components are assumed to be operating at a steady state equilibrium point. This includes both power flow data for a single time point simulation as well as quasi-static time series data and models, where the power system is at an equilibrium point at each time step. Static data can be used as the input to single time point power flow models and production cost models with, for example, 5-minute, 15-minute, or 1-hour Resolution. For contrast, see the definition for Dynamic data.

  • STAB: Speed Sensitive Stabilizing PSS Model

V

  • VSCDCLine: Voltage-Source Converter Direct Current Line

  • VSM:

W

  • Window: A forecast window is one forecast run that starts at one initial time and extends through the forecast horizon. Typically, a forecast data set contains multiple forecast windows, with sequential initial times. For example, a year-long data set of day-ahead forecasts contains 365 forecast windows

Z

  • ZIP load: A ZIP load model accounts for the voltage-dependency of a load and is primarily used for dynamics modeling. It includes three kinds of load: constant impedance (Z), constant current (I), and constant power (P), though many dynamics models just use the constant impedance model. StandardLoad and ExponentialLoad are both ZIP load models: StandardLoad breaks up the load into each of its three components, while ExponentialLoad expresses the load as an exponential equation.
diff --git a/previews/PR1171/api/internal/index.html b/previews/PR1171/api/internal/index.html new file mode 100644 index 0000000000..905857af2d --- /dev/null +++ b/previews/PR1171/api/internal/index.html @@ -0,0 +1,873 @@ + +Internal API Reference · PowerSystems.jl
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Internal API

PowerSystems._pti_dtypes — Constant

lookup array of data types for PTI file sections given by field_name, as enumerated by PSS/E Program Operation Manual.

source
PowerSystems.EX4VSA — Type
mutable struct EX4VSA <: AVR
+    Iflim::Float64
+    d::Float64
+    f::Float64
+    Spar::Float64
+    K1::Float64
+    K2::Float64
+    Oel_lim::MinMax
+    G::Float64
+    Ta::Float64
+    Tb::Float64
+    Te::Float64
+    E_lim::MinMax
+    V_ref::Float64
+    ext::Dict{String, Any}
+    states::Vector{Symbol}
+    n_states::Int
+    internal::InfrastructureSystemsInternal
+end

IEEE Excitation System for Voltage Security Assesment

Arguments

  • Iflim::Float64: OEL Field current limit, validation range: (0, nothing)
  • d::Float64: OEL parameter d, validation range: (0, nothing)
  • f::Float64: OEL parameter f, validation range: (0, nothing)
  • Spar::Float64: OEL parameter Spar, validation range: (0, nothing)
  • K1::Float64: OEL delay time constant, validation range: (0, nothing)
  • K2::Float64: OEL parameter K2, validation range: (0, nothing)
  • Oel_lim::MinMax: Oel integrator limits (Oelmin, Oelmax)
  • G::Float64: AVR Exciter Gain, validation range: (0, nothing)
  • Ta::Float64: Numerator lead-lag (lag) time constant in s, validation range: (0, nothing)
  • Tb::Float64: Denominator lead-lag (lag) time constant in s, validation range: (0, nothing)
  • Te::Float64: Exciter Time Constant in s, validation range: (0, nothing)
  • E_lim::MinMax: Voltage regulator limits (regulator output) (Emin, Emax)
  • V_ref::Float64: (default: 1.0) Reference Voltage Set-point (pu), validation range: (0, nothing)
  • ext::Dict{String, Any}: (default: Dict{String, Any}()) An extra dictionary for users to add metadata that are not used in simulation, such as latitude and longitude.
  • states::Vector{Symbol}: (Do not modify.) The states are:
Vll: Lead-lag internal state,
+Vex: Exciter Output, 
+oel: OEL integrator state
  • n_states::Int: (Do not modify.) The EX4VSA has 3 states
  • internal::InfrastructureSystemsInternal: (Do not modify.) PowerSystems.jl internal reference
source
PowerSystems.EXST1 — Type
mutable struct EXST1 <: AVR
+    Tr::Float64
+    Vi_lim::MinMax
+    Tc::Float64
+    Tb::Float64
+    Ka::Float64
+    Ta::Float64
+    Vr_lim::MinMax
+    Kc::Float64
+    Kf::Float64
+    Tf::Float64
+    V_ref::Float64
+    ext::Dict{String, Any}
+    states::Vector{Symbol}
+    n_states::Int
+    internal::InfrastructureSystemsInternal
+end

IEEE Type ST1 Excitation System (PTI version)

Arguments

  • Tr::Float64: Voltage Measurement Time Constant in s, validation range: (0, nothing)
  • Vi_lim::MinMax: Voltage input limits (Vimin, Vimax)
  • Tc::Float64: Numerator lead-lag (lead) time constant in s, validation range: (0, nothing)
  • Tb::Float64: Denominator lead-lag (lag) time constant in s, validation range: (0, nothing)
  • Ka::Float64: Amplifier Gain, validation range: (0, nothing)
  • Ta::Float64: Amplifier Time Constant in s, validation range: (0, nothing)
  • Vr_lim::MinMax: Voltage regulator limits (regulator output) (Vrmin, Vrmax)
  • Kc::Float64: Current field constant limiter multiplier, validation range: (0, nothing)
  • Kf::Float64: Excitation control system stabilizer gain, validation range: (eps(), 0.3)
  • Tf::Float64: Excitation control system stabilizer time constant, validation range: (eps(), nothing)
  • V_ref::Float64: (default: 1.0) Reference Voltage Set-point (pu), validation range: (0, nothing)
  • ext::Dict{String, Any}: (default: Dict{String, Any}()) An extra dictionary for users to add metadata that are not used in simulation, such as latitude and longitude.
  • states::Vector{Symbol}: (Do not modify.) The states are:
Vm: Sensed Terminal Voltage,
+Vrll: Lead-Lag state,
+Vr: Regulator Output, 
+Vfb: Feedback state
  • n_states::Int: (Do not modify.) The EXST1 has 4 states
  • internal::InfrastructureSystemsInternal: (Do not modify.) PowerSystems.jl internal reference
source
PowerSystems.PowerFlowDataNetwork — Method
PowerFlowDataNetwork(
+    file::Union{IO, String};
+    kwargs...
+) -> PowerSystems.PowerFlowDataNetwork
+

Constructs PowerFlowDataNetwork from a raw file. Currently Supports PSSE data files v30, v32 and v33

source
Base.convert — Method
convert(
+    _::Type{@NamedTuple{min::Float64, max::Float64}},
+    input::Tuple{Float64, Float64}
+) -> @NamedTuple{min::Float64, max::Float64}
+

Convert Tuple to Min Max Named Tuple

source
Base.convert — Method
convert(
+    _::Type{@NamedTuple{up::Float64, down::Float64}},
+    input::Tuple{Float64, Float64}
+) -> @NamedTuple{up::Float64, down::Float64}
+

Convert Tuple to Up Down Named Tuple

source
PowerSystems._convert_argument_types! — Method
_convert_argument_types!(
+    str::AbstractString,
+    struct_args::Vector
+) -> Any
+

Convert specific parameters to types that are not Float64 for specific inverter components

source
PowerSystems._create_starbus_from_transformer — Method
_create_starbus_from_transformer(
+    pm_data::Dict,
+    transformer::Dict,
+    starbus_id::Int64
+) -> Dict{String, Any}
+
create_starbus(pm_data, transformer)

Creates a starbus from a given three-winding transformer. "sourceid" is given by `["busi", "name", "I", "J", "K", "CKT"]` where "bus_i" and "name" are the modified names for the starbus, and "I", "J", "K" and "CKT" come from the originating transformer, in the PSS(R)E transformer specification.

source
PowerSystems._float2string — Method
_float2string(
+    v::AbstractFloat,
+    float_precision::Int64
+) -> Union{String, WeakRefStrings.PosLenString}
+

converts a float value into a string of fixed precision

sprintf would do the job but this work around is needed because sprintf cannot take format strings during runtime

source
PowerSystems._get_bus_value — Method
_get_bus_value(
+    bus_i::Int64,
+    field::String,
+    pm_data::Dict{String, Any}
+) -> Any
+
_get_bus_value(bus_i, field, pm_data)

Returns the value of field of bus_i from the PowerModels data. Requires "bus" Dict to already be populated.

source
PowerSystems._get_line_elements — Method
_get_line_elements(
+    line::AbstractString
+) -> Tuple{Vector{T} where T<:SubString, Union{String, SubString}}
+
_get_line_elements(line)

Internal function. Uses regular expressions to extract all separate data elements from a line of a PTI file and populate them into an Array{String}. Comments, typically indicated at the end of a line with a '/' character, are also extracted separately, and Array{Array{String}, String} is returned.

source
PowerSystems._grey — Method
_grey(s::String) -> String
+

Makes a string grey in the terminal, does not seem to work well on Windows terminals more info can be found at https://en.wikipedia.org/wiki/ANSIescapecode

source
PowerSystems._import_remaining_comps! — Method
_import_remaining_comps!(
+    data_out::Dict,
+    data_in::Dict;
+    exclude
+)
+

Imports remaining top level component lists from data_in into data_out, excluding keys in exclude

source
PowerSystems._import_remaining_keys! — Method
_import_remaining_keys!(
+    comp_dest::Dict,
+    comp_src::Dict;
+    exclude
+)
+

Imports remaining keys from a source component into detestation component, excluding keys in exclude

source
PowerSystems._init_bus! — Method
_init_bus!(bus::Dict{String, Any}, id::Int64)
+
_init_bus!(bus, id)

Initializes a bus of id id with default values given in the PSS(R)E specification.

source
PowerSystems._instantiate_param_vector_size — Method
_instantiate_param_vector_size(
+    str::AbstractString,
+    param_map::Dict
+) -> Any
+

Construct appropiate vector size for components that collect parameters from more than 2 PSS/E components

source
PowerSystems._merge_cost_data! — Method
_merge_cost_data!(
+    data::Dict{String, Any}
+) -> Union{Nothing, Dict{String, Any}}
+

merges generator cost functions into generator data, if costs exist

source
PowerSystems._parse_dera1! — Method
_parse_dera1!(
+    bus_dict,
+    componentID,
+    componentValues,
+    param_map::Dict,
+    bus_num::Int64
+)
+

Parse dictionary of data (from _parse_dyr_file) into a dictionary of DERA1. The function receives the parsed dictionary and constructs a dictionary indexed by bus, that contains a dictionary with each DERA1 indexed by its id.

source
PowerSystems._parse_dyr_components — Method
_parse_dyr_components(
+    dyr_file::AbstractString
+) -> Dict{Int64, Any}
+

Parse a .dyr file directly from its name by constructing its dictionary of dictionaries.

source
PowerSystems._parse_dyr_components — Method
_parse_dyr_components(data::Dict) -> Dict{Int64, Any}
+

Parse dictionary of dictionaries of data (from _parse_dyr_file) into a dictionary of struct components. The function receives the parsed dictionary and constructs a dictionary indexed by bus, that contains a dictionary with each dynamic generator and dynamic inverter components (indexed via its id).

For Generators, each dictionary indexed by id contains a vector with 5 of its components:

  • Machine
  • Shaft
  • AVR
  • TurbineGov
  • PSS

For Inverters, each dictionary indexed by id contains a vector with 7 of its components:

  • Converter
  • ActivePowerControl
  • ReactivePowerControl
  • InnerControl
  • DCSource
  • FrequencyEstimator
  • Filter
source
PowerSystems._parse_dyr_file — Method
_parse_dyr_file(file::AbstractString) -> Dict{Int64, Dict}
+

Parse .dyr file into a dictionary indexed by bus number. Each bus number key has a dictionary indexed by component type and id.

Comments in .dyr files are not supported (beginning of lines with //).

source
PowerSystems._parse_dyr_generator_components! — Method
_parse_dyr_generator_components!(
+    bus_dict::Dict,
+    componentID,
+    componentValues,
+    gen_map::Dict,
+    param_map::Dict
+)
+

Parse dictionary of data (from _parse_dyr_file) into a dictionary of struct components. The function receives the parsed dictionary and constructs a dictionary indexed by bus, that contains a dictionary with each dynamic generator indexed by its id.

source
PowerSystems._parse_dyr_inverter_components! — Method
_parse_dyr_inverter_components!(
+    bus_dict::Dict,
+    inv_dict::Dict,
+    componentID::Tuple{String, String},
+    inv_map::Dict
+)
+

Parse dictionary of data (from _parse_dyr_file) into a dictionary of struct components. The function receives the parsed dictionary and constructs a dictionary indexed by bus, that contains a dictionary with each dynamic inverter indexed by its id.

source
PowerSystems._parse_elements — Method
_parse_elements(
+    elements::Array,
+    dtypes::Array,
+    defaults::Dict,
+    section::AbstractString
+) -> Dict{String, Any}
+

This is an experimental method for parsing elements and setting defaults at the same time. It is not currently working but would reduce memory allocations if implemented correctly.

source
PowerSystems._parse_line_element! — Method
_parse_line_element!(
+    data::Dict,
+    elements::Array,
+    section::AbstractString
+)
+
_parse_line_element!(data, elements, section)

Internal function. Parses a single "line" of data elements from a PTI file, as given by elements which is an array of the line, typically split at ,. Elements are parsed into data types given by section and saved into data::Dict.

source
PowerSystems._parse_pti_data — Method
_parse_pti_data(data_io::IO) -> Dict{String, Array{Dict}}
+
_parse_pti_data(data_string, sections)

Internal function. Parse a PTI raw file into a Dict, given the data_string of the file and a list of the sections in the PTI file (typically given by default by get_pti_sections().

source
PowerSystems._populate_args — Method
_populate_args(param_map::Vector, val) -> Vector{Any}
+

Populate arguments in a vector for each dynamic component (except Shafts). Returns a vector with the parameter values of the argument of each component.

source
PowerSystems._process_get_cost — Method
_process_get_cost(_, _, cost::Nothing, _, _, _, _)
+

Helper function for cost getters.

Arguments

  • T: type/eltype we expect
  • component::Component: the component
  • cost: the data: either a single element of type T or a TimeSeriesKey
  • transform_fn: a function to apply to the elements of the time series
  • start_time: as in get_time_series
  • len: as in get_time_series
source
PowerSystems._process_set_cost — Method
_process_set_cost(_, _, _, _, _::Nothing)
+

Helper function for cost setters.

Arguments

  • T1: type we expect if it's not a time series
  • T2: eltype we expect if it is a time series
  • sys::System: the system
  • component::Component: the component
  • cost: the data: either a single element of type T1 or a IS.TimeSeriesData of eltype T2
source
PowerSystems._psse2pm_branch! — Method
_psse2pm_branch!(
+    pm_data::Dict,
+    pti_data::Dict,
+    import_all::Bool
+)
+
_psse2pm_branch!(pm_data, pti_data)

Parses PSS(R)E-style Branch data into a PowerModels-style Dict. "source_id" is given by ["I", "J", "CKT"] in PSS(R)E Branch specification.

source
PowerSystems._psse2pm_bus! — Method
_psse2pm_bus!(
+    pm_data::Dict,
+    pti_data::Dict,
+    import_all::Bool
+)
+
_psse2pm_bus!(pm_data, pti_data)

Parses PSS(R)E-style Bus data into a PowerModels-style Dict. "source_id" is given by ["I", "NAME"] in PSS(R)E Bus specification.

source
PowerSystems._psse2pm_dcline! — Method
_psse2pm_dcline!(
+    pm_data::Dict,
+    pti_data::Dict,
+    import_all::Bool
+)
+
_psse2pm_dcline!(pm_data, pti_data)

Parses PSS(R)E-style Two-Terminal and VSC DC Lines data into a PowerModels compatible Dict structure by first converting them to a simple DC Line Model. For Two-Terminal DC lines, "sourceid" is given by ["IPR", "IPI", "NAME"] in the PSS(R)E Two-Terminal DC specification. For Voltage Source Converters, "sourceid" is given by ["IBUS1", "IBUS2", "NAME"], where "IBUS1" is "IBUS" of the first converter bus, and "IBUS2" is the "IBUS" of the second converter bus, in the PSS(R)E Voltage Source Converter specification.

source
PowerSystems._psse2pm_generator! — Method
_psse2pm_generator!(
+    pm_data::Dict,
+    pti_data::Dict,
+    import_all::Bool
+) -> Union{Nothing, Vector{Dict{String, Any}}}
+
_psse2pm_generator!(pm_data, pti_data)

Parses PSS(R)E-style Generator data in a PowerModels-style Dict. "source_id" is given by ["I", "ID"] in PSS(R)E Generator specification.

source
PowerSystems._psse2pm_load! — Method
_psse2pm_load!(
+    pm_data::Dict,
+    pti_data::Dict,
+    import_all::Bool
+)
+
_psse2pm_load!(pm_data, pti_data)

Parses PSS(R)E-style Load data into a PowerModels-style Dict. "source_id" is given by ["I", "ID"] in the PSS(R)E Load specification.

source
PowerSystems._psse2pm_shunt! — Method
_psse2pm_shunt!(
+    pm_data::Dict,
+    pti_data::Dict,
+    import_all::Bool
+)
+
_psse2pm_shunt!(pm_data, pti_data)

Parses PSS(R)E-style Fixed and Switched Shunt data into a PowerModels-style Dict. "source_id" is given by ["I", "ID"] for Fixed Shunts, and ["I", "SWREM"] for Switched Shunts, as given by the PSS(R)E Fixed and Switched Shunts specifications.

source
PowerSystems._psse2pm_transformer! — Method
_psse2pm_transformer!(
+    pm_data::Dict,
+    pti_data::Dict,
+    import_all::Bool
+)
+
_psse2pm_transformer!(pm_data, pti_data)

Parses PSS(R)E-style Transformer data into a PowerModels-style Dict. "source_id" is given by ["I", "J", "K", "CKT", "winding"], where "winding" is 0 if transformer is two-winding, and 1, 2, or 3 for three-winding, and the remaining keys are defined in the PSS(R)E Transformer specification.

source
PowerSystems._pti_to_powermodels! — Method
_pti_to_powermodels!(
+    pti_data::Dict;
+    import_all,
+    validate,
+    correct_branch_rating
+) -> Dict{String, Any}
+
_pti_to_powermodels!(pti_data)

Converts PSS(R)E-style data parsed from a PTI raw file, passed by pti_data into a format suitable for use internally in PowerModels. Imports all remaining data from the PTI file if import_all is true (Default: false).

source
PowerSystems._read_data_row — Method
_read_data_row(
+    data::PowerSystemTableData,
+    row,
+    field_infos;
+    na_to_nothing
+) -> NamedTuple
+

Reads values from dataframe row and performs necessary conversions.

source
PowerSystems._remove_pwl_cost_duplicates! — Function
_remove_pwl_cost_duplicates!(id, comp, type_name) -> Bool
+_remove_pwl_cost_duplicates!(
+    id,
+    comp,
+    type_name,
+    tolerance
+) -> Bool
+

checks that each point in the a pwl function is unique, simplifies the function if duplicates appear

source
PowerSystems._simplify_pwl_cost! — Function
_simplify_pwl_cost!(id, comp, type_name) -> Bool
+_simplify_pwl_cost!(id, comp, type_name, tolerance) -> Bool
+

checks the slope of each segment in a pwl function, simplifies the function if the slope changes is below a tolerance

source
PowerSystems._split_loads_shunts! — Method
_split_loads_shunts!(data::Dict{String, Any})
+
_split_loads_shunts!(data)

Seperates Loads and Shunts in data under separate "load" and "shunt" keys in the PowerModels data format. Includes references to originating bus via "loadbus" and "shuntbus" keys, respectively.

source
PowerSystems._standardize_cost_terms! — Method
_standardize_cost_terms!(
+    components::Dict{String},
+    comp_order::Int64,
+    cost_comp_name::String
+) -> Set{Int64}
+

ensures all polynomial costs functions have at exactly comp_order terms

source
PowerSystems._type_array — Method
_type_array(
+    string_array::Array{T<:AbstractString, 1}
+) -> Vector
+

Attempts to determine the type of an array of strings extracted from a matlab file

source
PowerSystems._type_value — Method
_type_value(value_string::AbstractString) -> Any
+

Attempts to determine the type of a string extracted from a matlab file

source
PowerSystems.add_service_internal! — Method
add_service_internal!(device::Device, service::Service)
+

This function add a service to the component without checking if the component and the service are attached to the same system

source
PowerSystems.adequacy_check — Method
adequacy_check(sys::System)
+
adequacy_check(sys::System)

Checks the system for sum(generator ratings) >= sum(load ratings).

Arguments

  • sys::System: system
source
PowerSystems.bus_gen_lookup — Method
bus_gen_lookup(
+    gen_data::Dict{String},
+    bus_data::Dict{String}
+) -> Dict
+

builds a lookup list of what generators are connected to a given bus

source
PowerSystems.bus_load_lookup — Method
bus_load_lookup(
+    load_data::Dict{String},
+    bus_data::Dict{String}
+) -> Dict
+

builds a lookup list of what loads are connected to a given bus

source
PowerSystems.bus_shunt_lookup — Method
bus_shunt_lookup(
+    shunt_data::Dict{String},
+    bus_data::Dict{String}
+) -> Dict
+

builds a lookup list of what shunts are connected to a given bus

source
PowerSystems.bus_storage_lookup — Method
bus_storage_lookup(
+    storage_data::Dict{String},
+    bus_data::Dict{String}
+) -> Dict
+

builds a lookup list of what storage is connected to a given bus

source
PowerSystems.calc_branch_flow_ac — Method
calc_branch_flow_ac(data::Dict{String}) -> Dict{String, Any}
+

assumes a vaild ac solution is included in the data and computes the branch flow values

source
PowerSystems.calc_branch_flow_dc — Method
calc_branch_flow_dc(data::Dict{String}) -> Dict{String, Any}
+

assumes a vaild dc solution is included in the data and computes the branch flow values

source
PowerSystems.calc_connected_components — Method
calc_connected_components(
+    pm_data::Dict{String};
+    edges
+) -> Set{Set{Int64}}
+

computes the connected components of the network graph returns a set of sets of bus ids, each set is a connected component

source
PowerSystems.calc_cost_pwl_lines — Method
calc_cost_pwl_lines(comp_dict::Dict) -> Dict{Any, Any}
+

compute lines in m and b from from pwl cost models data is a list of components.

Can be run on data or ref data structures

source
PowerSystems.calc_power_balance — Method
calc_power_balance(data::Dict{String}) -> Dict{String, Any}
+

assumes a vaild solution is included in the data and computes the power balance at each bus

source
PowerSystems.calculate_saturation_coefficients — Method
calculate_saturation_coefficients(
+    E::Tuple{Float64, Float64},
+    Se::Tuple{Float64, Float64}
+) -> Tuple{Float64, Float64}
+

Obtain coefficients (A, B) of the function Se(x) = B(x - A)^2/x for Se(E1) = B(E1 - A)^2/E1 and Se(E2) = B(E2 - A)^2/E2 and uses the negative solution of the quadratic equation

source
PowerSystems.check_component_addition — Method
check_component_addition(
+    sys::System,
+    component::Component;
+    kwargs...
+)
+

Throws ArgumentError if a PowerSystems rule blocks addition to the system.

This method is tied with handlecomponentaddition!. If the methods are re-implemented for a subtype then whatever is added in handlecomponentaddition! must be checked here.

source
PowerSystems.check_status — Method
check_status(data::Dict{String})
+

checks that active components are not connected to inactive buses, otherwise prints warnings

source
PowerSystems.check_type — Method
check_type(typ, value) -> Any
+

Checks if the given value is of a given type, if not tries to make it that type

source
PowerSystems.correct_network_data! — Method
correct_network_data!(
+    data::Dict{String};
+    correct_branch_rating
+) -> Dict{String, Dict{Symbol, Set{Int64}}}
+

Runs various data quality checks on a PowerModels data dictionary. Applies modifications in some cases. Reports modified component ids.

source
PowerSystems.correct_transformer_parameters! — Method
correct_transformer_parameters!(
+    data::Dict{String}
+) -> Set{Int64}
+

checks that each branch has a reasonable transformer parameters

this is important because setting tap == 0.0 leads to NaN computations, which are hard to debug

source
PowerSystems.correct_voltage_angle_differences! — Function
correct_voltage_angle_differences!(
+    data::Dict{String}
+) -> Set{Int64}
+correct_voltage_angle_differences!(
+    data::Dict{String},
+    default_pad
+) -> Set{Int64}
+

checks that voltage angle differences are within 90 deg., if not tightens

source
PowerSystems.deactivate_isolated_components! — Method
deactivate_isolated_components!(data::Dict{String}) -> Bool
+

removes buses with single branch connections and without any other attached components. Also removes connected components without suffuceint generation or loads.

also deactivates 0 valued loads and shunts.

source
PowerSystems.get_avr_saturation — Method
get_avr_saturation(
+    E::Tuple{Float64, Float64},
+    Se::Tuple{Float64, Float64}
+) -> Tuple{Float64, Float64}
+

Obtain coefficients for an AVR

source
PowerSystems.get_dataframe — Method
get_dataframe(
+    data::PowerSystemTableData,
+    category::PowerSystems.InputCategoryModule.InputCategory
+) -> DataFrames.DataFrame
+

Return the dataframe for the category.

source
PowerSystems.get_exponential_saturation — Method
get_exponential_saturation(
+    Se::Tuple{Float64, Float64}
+) -> Tuple{Float64, Float64}
+

Obtain coefficients (A, B) of the function Se = Bx^A for Se(1.2) = B(1.2)^A and Se(1.0) = B(1.0)^A as: B = Se(1.0) and hence (1.2)^A = Se(1.2)/B -> A = log(Se(1.2)/B) / log(1.2)

source
PowerSystems.get_generator_mapping — Function
get_generator_mapping() -> Dict{NamedTuple, DataType}
+get_generator_mapping(
+    filename
+) -> Dict{NamedTuple, DataType}
+

Return a dict where keys are a tuple of input parameters (fuel, unit_type) and values are generator types.

source
PowerSystems.get_generator_type — Method
get_generator_type(
+    fuel,
+    unit_type,
+    mappings::Dict{NamedTuple, DataType}
+) -> Union{Nothing, DataType}
+

Return the PowerSystems generator type for this fuel and unit_type.

source
PowerSystems.get_quadratic_saturation — Method
get_quadratic_saturation(
+    Se::Tuple{Float64, Float64}
+) -> Tuple{Float64, Float64}
+

Obtain coefficients (A, B) of the function Se = B(x - A)^2/x for Se(1.2) = B(1.2 - A)^2/1.2 and Se(1.0) = B(1.0 - A)^2/1.0 as: Se(1.0) = (Se(1.2) * 1.2) /(1.2 - A)^2 * (1.0 - A)^2/1.0 that yields (1.2 - A)^2 Se(1.0) = Se(1.2) * 1.2 * (1.0 - A)^2 or expanding: (1.2 * Se(1.2) - Se(1.0)) A^2 + (2.4 Se(1.0) - 2 * 1.2 * Se(1.2)) A + (1.2 * Se(1.2) - 1.44 Se(1.0)) = 0 and uses the negative solution of the quadratic equation.

source
PowerSystems.get_series_susceptance — Method
get_series_susceptance(
+    b::Union{PhaseShiftingTransformer, TapTransformer}
+) -> Float64
+

Returns the series susceptance of a controllable transformer following the convention in power systems to define susceptance as the inverse of the imaginary part of the impedance. In the case of phase shifter transformers the angle is ignored.

source
PowerSystems.get_user_field — Method
get_user_field(
+    data::PowerSystemTableData,
+    category::PowerSystems.InputCategoryModule.InputCategory,
+    field::AbstractString
+) -> Any
+

Return the custom name stored in the user descriptor file.

Throws DataFormatError if a required value is not found in the file.

source
PowerSystems.get_user_fields — Method
get_user_fields(
+    data::PowerSystemTableData,
+    category::PowerSystems.InputCategoryModule.InputCategory
+) -> Any
+

Return a vector of user-defined fields for the category.

source
PowerSystems.handle_deserialization_special_cases! — Method
handle_deserialization_special_cases!(
+    component::Dict,
+    _::Type{<:Component}
+)
+

Allow types to implement handling of special cases during deserialization.

Arguments

  • component::Dict: The component serialized as a dictionary.
  • ::Type: The type of the component.
source
PowerSystems.im_replicate — Method
im_replicate(
+    sn_data::Dict{String},
+    count::Int64,
+    global_keys::Set{String}
+) -> Dict{String, Any}
+

Transforms a single network into a multinetwork with several deepcopies of the original network

source
PowerSystems.is_attached — Method
is_attached(component::Component, sys::System) -> Bool
+

Return true if the component is attached to the system.

source
PowerSystems.isafield — Method
isafield(component::Component, field::Symbol) -> Any
+

Checks if a PowerSystemDevice has a field or subfield name.

source
PowerSystems.iterate_rows — Method
iterate_rows(
+    data::PowerSystemTableData,
+    category;
+    na_to_nothing
+) -> Channel{Any}
+

Return a NamedTuple of parameters from the descriptor file for each row of a dataframe, making type conversions as necessary.

Refer to the PowerSystems descriptor file for field names that will be created.

source
PowerSystems.load_csv_parser! — Method
load_csv_parser!(sys::System, data::PowerSystemTableData)
+
load_csv_parser!(sys::System, data::PowerSystemTableData)

Add loads to the System from the raw load data.

source
PowerSystems.loadzone_csv_parser! — Method
loadzone_csv_parser!(
+    sys::System,
+    data::PowerSystemTableData
+)
+
loadzone_csv_parser!(sys::System, data::PowerSystemTableData)

Add branches to the System from the raw data.

source
PowerSystems.make_bus — Method
make_bus(bus_dict::Dict{String, Any}) -> ACBus
+

Creates a PowerSystems.ACBus from a PowerSystems bus dictionary

source
PowerSystems.make_generator — Method
make_generator(
+    data::PowerSystemTableData,
+    gen,
+    cost_colnames,
+    bus,
+    gen_storage
+) -> Any
+

Creates a generator of any type.

source
PowerSystems.make_thermal_gen — Method
make_thermal_gen(
+    gen_name::Union{SubString{String}, String},
+    d::Dict,
+    bus::ACBus,
+    sys_mbase::Float64
+) -> ThermalStandard
+

The polynomial term follows the convention that for an n-degree polynomial, at least n + 1 components are needed. c(p) = cn*p^n+...+c1p+c0 co is stored in the field in of the Econ Struct

source
PowerSystems.parse_psse — Method
parse_psse(io::IO; kwargs...) -> Dict{String, Any}
+
function parse_psse(io::IO; kwargs...)::Dict

Parses directly from iostream

source
PowerSystems.parse_psse — Method
parse_psse(filename::String; kwargs...) -> Dict{String, Any}
+
parse_psse(filename::String; kwargs...)::Dict

Parses directly from file

source
PowerSystems.parse_pti — Method
parse_pti(io::IO) -> Dict{String, Array{Dict}}
+
parse_pti(io::IO)

Reads PTI data in io::IO, returning a Dict of the data parsed into the proper types.

source
PowerSystems.parse_pti — Method
parse_pti(filename::String) -> Dict{String, Array{Dict}}
+
parse_pti(filename::String)

Open PTI raw file given by filename, returning a Dict of the data parsed into the proper types.

source
PowerSystems.propagate_topology_status! — Method
propagate_topology_status!(
+    data::Dict{String}
+) -> Union{Nothing, Bool}
+

finds active network buses and branches that are not necessary for the computation and sets their status to off.

Works on a PowerModels data dict, so that a it can be used without a GenericPowerModel object

Warning: this implementation has quadratic complexity, in the worst case

source
PowerSystems.read_and_convert_ts — Function
read_and_convert_ts(
+    ts::TimeSeriesData,
+    component::Component
+) -> TimeSeries.TimeArray
+read_and_convert_ts(
+    ts::TimeSeriesData,
+    component::Component,
+    start_time::Union{Nothing, Dates.DateTime}
+) -> TimeSeries.TimeArray
+read_and_convert_ts(
+    ts::TimeSeriesData,
+    component::Component,
+    start_time::Union{Nothing, Dates.DateTime},
+    len::Union{Nothing, Int64}
+) -> TimeSeries.TimeArray
+read_and_convert_ts(
+    ts::TimeSeriesData,
+    component::Component,
+    start_time::Union{Nothing, Dates.DateTime},
+    len::Union{Nothing, Int64},
+    transform_fn
+) -> TimeSeries.TimeArray
+

Call gettimeseriesarray on the given time series and return a TimeArray of the results, values mapped by `transformfn` if it is not nothing

source
PowerSystems.read_gen! — Method
read_gen!(
+    sys::System,
+    data::Dict,
+    bus_number_to_bus::Dict{Int64, ACBus};
+    kwargs...
+)
+

Transfer generators to ps_dict according to their classification

source
PowerSystems.replicate — Method
replicate(
+    sn_data::Dict{String},
+    count::Int64;
+    global_keys
+) -> Dict{String, Any}
+

Turns in given single network data in multinetwork data with a count replicate of the given network. Note that this function performs a deepcopy of the network data. Significant multinetwork space savings can often be achieved by building application specific methods of building multinetwork with minimal data replication.

source
PowerSystems.resolve_swithces! — Method
resolve_swithces!(data::Dict{String})
+

given a network data dict merges buses that are connected by closed switches converting the dataset into a pure bus-branch model.

source
PowerSystems.simplify_network! — Method
simplify_network!(data::Dict{String}) -> Bool
+

attempts to deactive components that are not needed in the network by repeated calls to propagate_topology_status! and deactivate_isolated_components!

warning: this implementation has quadratic complexity, in the worst case

source
PowerSystems.total_capacity_rating — Method
total_capacity_rating(sys::System) -> Any
+
total_capacity_rating(sys::System)

Sum of system generator and storage ratings.

Arguments

  • sys::System: system
source
PowerSystems.total_load_rating — Method
total_load_rating(sys::System) -> Any
+
total_load_rating(sys::System)

Checks the system for sum(generator ratings) >= sum(load ratings).

Arguments

  • sys::System: system
source
PowerSystems.update_bus_ids! — Method
update_bus_ids!(
+    data::Dict{String},
+    bus_id_map::Dict{Int64, Int64};
+    injective
+)
+

given a network data dict and a mapping of current-bus-ids to new-bus-ids modifies the data dict to reflect the proposed new bus ids.

source
PowerSystems.update_data! — Method
update_data!(data::Dict{String}, new_data::Dict{String})
+

recursively applies new_data to data, overwriting information

source
PowerSystems.verify_device_eligibility — Method
verify_device_eligibility(
+    sys::System,
+    component::StaticInjection,
+    service::Service
+)
+

Validates if a device is eligible to contribute to a service.

Arguments

  • sys::System: PowerSystem System
  • component::StaticInjection: Static injection device
  • service::Service,: Service for which the device is eligible to contribute
source
diff --git a/previews/PR1171/api/public/index.html b/previews/PR1171/api/public/index.html new file mode 100644 index 0000000000..eab4cce814 --- /dev/null +++ b/previews/PR1171/api/public/index.html @@ -0,0 +1,1000 @@ + +Public API · PowerSystems.jl
Edit on GitHub

Public API Reference

Modeling

PowerSystems.Component — Type

Supertype for all PowerSystems components. All subtypes must include a InfrastructureSystemsInternal member. Subtypes should call InfrastructureSystemsInternal() by default, but also must provide a constructor that allows existing values to be deserialized.

source
PowerSystems.get_base_power — Method
get_base_power(c::Component) -> Float64
+

Default behavior of a component. If there is no base_power field, assume is in the system's base power.

source
PowerSystems.set_dynamic_injector! — Method
set_dynamic_injector!(
+    static_injector::StaticInjection,
+    dynamic_injector::Union{Nothing, DynamicInjection}
+)
+

Any StaticInjection struct that wants to support dynamic injectors must implement this method to set the value.

The method is only for internal uses.

source
PowerSystems.has_service — Method
has_service(device::Device, _::Type{T<:Service}) -> Bool
+

Return true if a service with type T is attached to the device.

source
PowerSystems.remove_service! — Method
remove_service!(device::Device, service::Service)
+

Remove a service from a device.

Throws ArgumentError if the service is not attached to the device.

source
PowerSystems.RenewableGen — Type

Supertype for all renewable generation technologies

Requires the implementation of get_ratingand get_power_factor methods

source
PowerSystems.get_max_reactive_power — Method
get_max_reactive_power(d::RenewableGen) -> Any
+

Return the max reactive power for the Renewable Generation calculated as the rating * sin(acos(power_factor))

source
PowerSystems.Reserve — Type

A reserve product to be able to respond to unexpected disturbances, such as the sudden loss of a transmission line or generator.

source
PowerSystems.ReserveDown — Type

A downwards reserve to decrease generation or increase load

Downwards reserves are used when total load falls below its expected level, typically due to forecast errors or contingencies. Not work

A Reserve can be specified as a ReserveDown when it is defined.

source
PowerSystems.ReserveSymmetric — Type

A symmetric reserve, procuring the same quantity (MW) of both upwards and downwards reserves

A symmetric reserve is a special case. ReserveUp and ReserveDown can be used individually to specify different quantities of upwards and downwards reserves, respectively.

A Reserve can be specified as a ReserveSymmetric when it is defined.

source
PowerSystems.ReserveUp — Type

An upwards reserve to increase generation or reduce load

Upwards reserves are used when total load exceeds its expected level, typically due to forecast errors or contingencies.

A Reserve can be specified as a ReserveUp when it is defined.

source
PowerSystems.Service — Type

Supertype for all system services

Services (or ancillary services) include additional requirements and support to ensure reliable electricity service to customers. Common services are reserve products to be able to respond quickly to unexpected disturbances, such as the sudden loss of a transmission line or generator.

source
PowerSystems.GeometricDistributionForcedOutage — Type

Attribute that contains information regarding forced outages where the transition probabilities are modeled with geometric distributions. The outage probabilities and recovery probabilities can be modeled as time series.

Arguments

  • time_to_recovery::Int: Time elapsed to recovery after a failure in Milliseconds.
  • outage_transition_probability::Float64: Characterizes the probability of failure (1 - p) in the geometric distribution.
  • internal::InfrastructureSystemsInternal: power system internal reference, do not modify
source
PowerSystems.PlannedOutage — Type

Attribute that contains information regarding planned outages.

Arguments

  • outage_schedule::String: String name of the time series used for the scheduled outages
  • internal::InfrastructureSystemsInternal: power system internal reference, do not modify
source
PowerSystems.TimeSeriesForcedOutage — Type

Attribute that contains the representation of the status of the component forced outage. The data can be obtained from the simulation of an stochastic process or historical information.

Arguments

  • outage_status_scenario::String: String name of the time series used for the forced outage status in the model. 1 is used represent outaged and 0 for available.
  • internal::InfrastructureSystemsInternal: power system internal reference, do not modify
source
PowerSystems.StaticInjection — Type

Abstract type for devices that inject power or current

A static injection is a steady state injection, such as modeling the output power of a generator held constant over a five-minute period.

Many StaticInjection models can accept a DynamicInjection model as an optional add-on for conducting dynamic simulations.

source
PowerSystems.StaticInjectionSubsystem — Type

Abstract type for a subsystem that contains multiple instances of StaticInjection

Subtypes must implement:

  • get_subcomponents(subsystem::StaticInjectionSubsystem)

The subcomponents in subtypes must be attached to the System as masked components.

source
PowerSystems.copy_subcomponent_time_series! — Method
copy_subcomponent_time_series!(
+    subsystem::StaticInjectionSubsystem,
+    subcomponent::Component
+)
+

Efficiently add all time series data in the subcomponent to the subsystem by copying the underlying references.

source
PowerSystems.get_dynamic_components — Method
get_dynamic_components(
+    device::DynamicInjection
+) -> Base.Generator{I, F} where {I<:(Base.Iterators.Filter{PowerSystems.var"#6#8", I} where I<:(Base.Iterators.Zip{Is} where Is<:Tuple{Any, Tuple})), F<:(PowerSystems.var"#5#7"{<:DynamicInjection})}
+

Return all the dynamic components of a DynamicInjection device

source
PowerSystems.get_states_types — Method
get_states_types(d::DynamicComponent) -> Vector{StateTypes}
+
Default implementation of get_state_types for dynamic components. Assumes all states are
+Differential
source
InfrastructureSystems.get_fuel_cost — Method
get_fuel_cost(
+    component::StaticInjection;
+    start_time,
+    len
+) -> Union{Float64, TimeSeries.TimeArray}
+

Get the fuel cost of the component's variable cost, which must be a FuelCurve.

source
PowerSystems.get_no_load_cost — Method
get_no_load_cost(
+    device::StaticInjection,
+    cost::MarketBidCost;
+    start_time,
+    len
+) -> Union{Float64, TimeSeries.TimeArray}
+

Retrieve the no-load cost data for a StaticInjection device with a MarketBidCost. If this field is a time series, the user may specify start_time and len and the function returns a TimeArray of Float64s; if the field is not a time series, the function returns a single Float64.

source
PowerSystems.get_services_bid — Method
get_services_bid(
+    device::StaticInjection,
+    cost::MarketBidCost,
+    service::Service;
+    start_time,
+    len
+) -> TimeSeries.TimeArray
+

Return service bid time series data for a StaticInjection device with a MarketBidCost. The user may specify start_time and len and the function returns a TimeArray of CostCurves.

source
PowerSystems.get_start_up — Method
get_start_up(
+    device::StaticInjection,
+    cost::MarketBidCost;
+    start_time,
+    len
+) -> Union{@NamedTuple{hot::Float64, warm::Float64, cold::Float64}, TimeSeries.TimeArray}
+

Retrieve the no-load cost data for a StaticInjection device with a MarketBidCost. If this field is a time series, the user may specify start_time and len and the function returns a TimeArray of Float64s; if the field is not a time series, the function returns a single Float64.

source
PowerSystems.get_variable_cost — Method
get_variable_cost(
+    service::ReserveDemandCurve;
+    start_time,
+    len
+) -> Union{CostCurve{PiecewiseIncrementalCurve}, TimeSeries.TimeArray}
+

Retrieve the variable cost data for a ReserveDemandCurve. The user may specify start_time and len and the function returns a TimeArray of CostCurves.

source
PowerSystems.get_variable_cost — Method
get_variable_cost(
+    device::StaticInjection,
+    cost::MarketBidCost;
+    start_time,
+    len
+) -> Union{CostCurve{PiecewiseIncrementalCurve}, TimeSeries.TimeArray}
+

Retrieve the variable cost bid for a StaticInjection device with a MarketBidCost. If this field is a time series, the user may specify start_time and len and the function returns a TimeArray of CostCurves; if the field is not a time series, the function returns a single CostCurve.

source
PowerSystems.set_fuel_cost! — Method
set_fuel_cost!(
+    sys::System,
+    component::StaticInjection,
+    data::Union{Float64, TimeSeriesData}
+) -> Any
+

Set the fuel cost of the component's variable cost, which must be a FuelCurve.

source
PowerSystems.set_no_load_cost! — Method
set_no_load_cost!(
+    sys::System,
+    component::StaticInjection,
+    data::Union{Float64, TimeSeriesData}
+) -> Union{Float64, TimeSeriesKey}
+

Set the no-load cost for a StaticInjection device with a MarketBidCost to either a single number or a time series.

Arguments

  • sys::System: PowerSystem System
  • component::StaticInjection: Static injection device
  • time_series_data::Union{Float64, IS.TimeSeriesData},: the data. If a time series, must be of eltype Float64.
source
PowerSystems.set_service_bid! — Method
set_service_bid!(
+    sys::System,
+    component::StaticInjection,
+    service::Service,
+    time_series_data::TimeSeriesData
+)
+

Adds service bids time-series data to the MarketBidCost.

Arguments

  • sys::System: PowerSystem System
  • component::StaticInjection: Static injection device
  • service::Service,: Service for which the device is eligible to contribute
  • time_series_data::IS.TimeSeriesData: TimeSeriesData
source
PowerSystems.set_start_up! — Method
set_start_up!(
+    sys::System,
+    component::StaticInjection,
+    data::Union{@NamedTuple{hot::Float64, warm::Float64, cold::Float64}, TimeSeriesData}
+) -> Union{@NamedTuple{hot::Float64, warm::Float64, cold::Float64}, TimeSeriesKey}
+

Set the startup cost for a StaticInjection device with a MarketBidCost to either a single StartUpStages or a time series.

Arguments

  • sys::System: PowerSystem System
  • component::StaticInjection: Static injection device
  • time_series_data::Union{StartUpStages, IS.TimeSeriesData},: the data. If a time series, must be of eltype NTuple{3, Float64}.
source
PowerSystems.set_variable_cost! — Method
set_variable_cost!(
+    _::System,
+    component::ReserveDemandCurve,
+    data::CostCurve{PiecewiseIncrementalCurve}
+) -> CostCurve{PiecewiseIncrementalCurve}
+

Adds fixed energy market bids to the ReserveDemandCurve.

Arguments

  • sys::System: PowerSystem System
  • component::ReserveDemandCurve: the curve
  • `timeseriesdata::CostCurve{PiecewiseIncrementalCurve}
source
PowerSystems.set_variable_cost! — Method
set_variable_cost!(
+    sys::System,
+    component::ReserveDemandCurve,
+    data::Union{Nothing, TimeSeriesData}
+) -> TimeSeriesKey
+

Adds energy market bids time-series to the ReserveDemandCurve.

Arguments

  • sys::System: PowerSystem System
  • component::ReserveDemandCurve: the curve
  • time_series_data::IS.TimeSeriesData: TimeSeriesData
source
PowerSystems.set_variable_cost! — Method
set_variable_cost!(
+    sys::System,
+    component::StaticInjection,
+    data::Union{Nothing, CostCurve{PiecewiseIncrementalCurve}, TimeSeriesData}
+) -> Any
+

Set the variable cost bid for a StaticInjection device with a MarketBidCost.

Arguments

  • sys::System: PowerSystem System
  • component::StaticInjection: Static injection device
  • time_series_data::Union{Nothing, IS.TimeSeriesData, CostCurve{PiecewiseIncrementalCurve}},: the data. If a time series, must be of eltype PiecewiseStepData.
source

TimeSeries

InfrastructureSystems.TimeSeriesData — Type

Abstract type for time series stored in the system. Components store references to these through TimeSeriesMetadata values so that data can reside on storage media instead of memory.

InfrastructureSystems.Deterministic — Type
mutable struct Deterministic <: AbstractDeterministic
+    name::String
+    data::SortedDict
+    resolution::Dates.Period
+    scaling_factor_multiplier::Union{Nothing, Function}
+    internal::InfrastructureSystemsInternal
+end

A deterministic forecast for a particular data field in a Component.

Arguments

  • name::String: user-defined name
  • data::SortedDict: timestamp - scalingfactor
  • resolution::Dates.Period: forecast resolution
  • scaling_factor_multiplier::Union{Nothing, Function}: Applicable when the time series data are scaling factors. Called on the associated component to convert the values.
  • internal::InfrastructureSystemsInternal
InfrastructureSystems.Deterministic — Method
Deterministic(
+    name::AbstractString,
+    input_data::AbstractDict{Dates.DateTime, <:TimeSeries.TimeArray};
+    normalization_factor,
+    scaling_factor_multiplier
+) -> Deterministic
+

Construct Deterministic from a Dict of TimeArrays.

Arguments

  • name::AbstractString: user-defined name
  • input_data::AbstractDict{Dates.DateTime, TimeSeries.TimeArray}: time series data.
  • normalization_factor::NormalizationFactor = 1.0: optional normalization factor to apply to each data entry
  • scaling_factor_multiplier::Union{Nothing, Function} = nothing: If the data are scaling factors then this function will be called on the component and applied to the data when get_time_series_array is called.
  • timestamp = :timestamp: If the values are DataFrames is passed then this must be the column name that contains timestamps.
InfrastructureSystems.Deterministic — Method
Deterministic(
+    name::AbstractString,
+    filename::AbstractString,
+    component::InfrastructureSystems.InfrastructureSystemsComponent,
+    resolution::Dates.Period;
+    normalization_factor,
+    scaling_factor_multiplier
+) -> Deterministic
+

Construct Deterministic from a CSV file. The first column must be a timestamp in DateTime format and the columns the values in the forecast window.

Arguments

  • name::AbstractString: user-defined name
  • filename::AbstractString: name of CSV file containing data
  • component::InfrastructureSystemsComponent: component associated with the data
  • normalization_factor::NormalizationFactor = 1.0: optional normalization factor to apply to each data entry
  • scaling_factor_multiplier::Union{Nothing, Function} = nothing: If the data are scaling factors then this function will be called on the component and applied to the data when get_time_series_array is called.
InfrastructureSystems.Deterministic — Method
Deterministic(
+    name::AbstractString,
+    series_data::InfrastructureSystems.RawTimeSeries,
+    resolution::Dates.Period;
+    normalization_factor,
+    scaling_factor_multiplier
+) -> Deterministic
+

Construct Deterministic from RawTimeSeries.

InfrastructureSystems.Deterministic — Method
Deterministic(
+    src::Deterministic,
+    name::AbstractString;
+    scaling_factor_multiplier
+) -> Deterministic
+

Construct Deterministic that shares the data from an existing instance.

This is useful in cases where you want a component to use the same time series data for two different attributes.

Examples

resolution = Dates.Hour(1)
+data = Dict(
+    DateTime("2020-01-01T00:00:00") => ones(24),
+    DateTime("2020-01-01T01:00:00") => ones(24),
+)
+# Define a Deterministic for the first attribute
+forecast_max_active_power = Deterministic(
+    "max_active_power",
+    data,
+    resolution,
+    scaling_factor_multiplier = get_max_active_power,
+)
+add_time_series!(sys, generator, forecast_max_active_power)
+# Reuse time series for second attribute
+forecast_max_reactive_power = Deterministic(
+    forecast_max_active_power,
+    "max_reactive_power"
+    scaling_factor_multiplier = get_max_reactive_power,
+)
+add_time_series!(sys, generator, forecast_max_reactive_power)
InfrastructureSystems.Deterministic — Method
Deterministic(
+    forecast::Deterministic,
+    data
+) -> Deterministic
+

Construct a new Deterministic from an existing instance and a subset of data.

InfrastructureSystems.iterate_windows — Method
iterate_windows(
+    forecast::Deterministic
+) -> Base.Generator{I, InfrastructureSystems.var"#107#108"{Deterministic}} where I<:(DataStructures.SDMKeyIteration{T} where T<:DataStructures.SortedDict)
+

Iterate over the windows in a forecast

Examples

for window in iterate_windows(forecast)
+    @show values(maximum(window))
+end
InfrastructureSystems.Probabilistic — Type
mutable struct Probabilistic <: Forecast
+    name::String
+    resolution::Dates.Period
+    percentiles::Vector{Float64}
+    data::SortedDict
+    scaling_factor_multiplier::Union{Nothing, Function}
+    internal::InfrastructureSystemsInternal
+end

A Probabilistic forecast for a particular data field in a Component.

Arguments

  • name::String: user-defined name
  • resolution::Dates.Period: forecast resolution
  • percentiles::Vector{Float64}: Percentiles for the probabilistic forecast
  • data::SortedDict: timestamp - scalingfactor
  • scaling_factor_multiplier::Union{Nothing, Function}: Applicable when the time series data are scaling factors. Called on the associated component to convert the values.
  • internal::InfrastructureSystemsInternal
InfrastructureSystems.Probabilistic — Method
Probabilistic(
+    name::AbstractString,
+    input_data::AbstractDict,
+    percentiles::Vector,
+    resolution::Dates.Period;
+    normalization_factor,
+    scaling_factor_multiplier
+) -> Probabilistic
+

Construct Probabilistic from a SortedDict of Arrays.

Arguments

  • name::AbstractString: user-defined name
  • input_data::AbstractDict{Dates.DateTime, Matrix{Float64}}: time series data.
  • percentiles: Percentiles represented in the probabilistic forecast
  • resolution::Dates.Period: The resolution of the forecast in Dates.Period`
  • normalization_factor::NormalizationFactor = 1.0: optional normalization factor to apply to each data entry
  • scaling_factor_multiplier::Union{Nothing, Function} = nothing: If the data are scaling factors then this function will be called on the component and applied to the data when get_time_series_array is called.
InfrastructureSystems.Probabilistic — Method
Probabilistic(
+    name::AbstractString,
+    input_data::AbstractDict{Dates.DateTime, <:TimeSeries.TimeArray},
+    percentiles::Vector{Float64};
+    normalization_factor,
+    scaling_factor_multiplier
+) -> Probabilistic
+

Construct Probabilistic from a Dict of TimeArrays.

Arguments

  • name::AbstractString: user-defined name
  • input_data::AbstractDict{Dates.DateTime, TimeSeries.TimeArray}: time series data.
  • percentiles: Percentiles represented in the probabilistic forecast
  • normalization_factor::NormalizationFactor = 1.0: optional normalization factor to apply to each data entry
  • scaling_factor_multiplier::Union{Nothing, Function} = nothing: If the data are scaling factors then this function will be called on the component and applied to the data when get_time_series_array is called.
  • timestamp = :timestamp: If the values are DataFrames is passed then this must be the column name that contains timestamps.
InfrastructureSystems.Probabilistic — Method
Probabilistic(
+    name::AbstractString,
+    series_data::InfrastructureSystems.RawTimeSeries,
+    percentiles::Vector,
+    resolution::Dates.Period;
+    normalization_factor,
+    scaling_factor_multiplier
+) -> Probabilistic
+

Construct Deterministic from RawTimeSeries.

InfrastructureSystems.Probabilistic — Method
Probabilistic(
+    src::Probabilistic,
+    name::AbstractString;
+    scaling_factor_multiplier
+) -> Probabilistic
+

Construct a Probabilistic that shares the data from an existing instance.

This is useful in cases where you want a component to use the same time series data for two different attributes.

InfrastructureSystems.iterate_windows — Method
iterate_windows(
+    forecast::Probabilistic
+) -> Base.Generator{I, InfrastructureSystems.var"#107#108"{Probabilistic}} where I<:(DataStructures.SDMKeyIteration{T} where T<:DataStructures.SortedDict)
+

Iterate over the windows in a forecast

Examples

for window in iterate_windows(forecast)
+    @show values(maximum(window))
+end
InfrastructureSystems.Scenarios — Type
mutable struct Scenarios <: Forecast
+    name::String
+    resolution::Dates.Period
+    scenario_count::Int64
+    data::SortedDict
+    scaling_factor_multiplier::Union{Nothing, Function}
+    internal::InfrastructureSystemsInternal
+end

A Discrete Scenario Based time series for a particular data field in a Component.

Arguments

  • name::String: user-defined name
  • resolution::Dates.Period: forecast resolution
  • scenario_count::Int64: Number of scenarios
  • data::SortedDict: timestamp - scalingfactor
  • scaling_factor_multiplier::Union{Nothing, Function}: Applicable when the time series data are scaling factors. Called on the associated component to convert the values.
  • internal::InfrastructureSystemsInternal
InfrastructureSystems.Scenarios — Method
Scenarios(
+    name::AbstractString,
+    input_data::AbstractDict,
+    resolution::Dates.Period;
+    normalization_factor,
+    scaling_factor_multiplier
+) -> Scenarios
+

Construct Scenarios from a SortedDict of Arrays.

Arguments

  • name::AbstractString: user-defined name
  • input_data::AbstractDict{Dates.DateTime, Matrix{Float64}}: time series data.
  • resolution::Dates.Period: The resolution of the forecast in Dates.Period`
  • normalization_factor::NormalizationFactor = 1.0: optional normalization factor to apply to each data entry
  • scaling_factor_multiplier::Union{Nothing, Function} = nothing: If the data are scaling factors then this function will be called on the component and applied to the data when get_time_series_array is called.
InfrastructureSystems.Scenarios — Method
Scenarios(
+    name::AbstractString,
+    input_data::AbstractDict{Dates.DateTime, <:TimeSeries.TimeArray};
+    normalization_factor,
+    scaling_factor_multiplier
+) -> Scenarios
+

Construct Scenarios from a Dict of TimeArrays.

Arguments

  • name::AbstractString: user-defined name
  • input_data::AbstractDict{Dates.DateTime, TimeSeries.TimeArray}: time series data.
  • normalization_factor::NormalizationFactor = 1.0: optional normalization factor to apply to each data entry
  • scaling_factor_multiplier::Union{Nothing, Function} = nothing: If the data are scaling factors then this function will be called on the component and applied to the data when get_time_series_array is called.
  • timestamp = :timestamp: If the values are DataFrames is passed then this must be the column name that contains timestamps.
InfrastructureSystems.Scenarios — Method
Scenarios(
+    src::Scenarios,
+    name::AbstractString;
+    scaling_factor_multiplier
+) -> Scenarios
+

Construct Scenarios that shares the data from an existing instance.

This is useful in cases where you want a component to use the same time series data for two different attributes.

InfrastructureSystems.iterate_windows — Method
iterate_windows(
+    forecast::Scenarios
+) -> Base.Generator{I, InfrastructureSystems.var"#107#108"{Scenarios}} where I<:(DataStructures.SDMKeyIteration{T} where T<:DataStructures.SortedDict)
+

Iterate over the windows in a forecast

Examples

for window in iterate_windows(forecast)
+    @show values(maximum(window))
+end
InfrastructureSystems.DeterministicSingleTimeSeries — Type
mutable struct DeterministicSingleTimeSeries <: AbstractDeterministic
+    single_time_series::SingleTimeSeries
+    initial_timestamp::Dates.DateTime
+    interval::Dates.Period
+    count::Int
+    horizon::Int
+end

A deterministic forecast that wraps a SingleTimeSeries

DeterministicSingleTimeSeries behaves exactly like a Deterministic, but instead of storing windows at each initial time it provides a view into the existing SingleTimeSeries at incrementing offsets. This avoids large data duplications when there are the overlapping windows between forecasts.

Can be used as a perfect forecast based on historical data when real forecast data is unavailable.

Arguments

  • single_time_series::SingleTimeSeries: wrapped SingleTimeSeries object
  • initial_timestamp::Dates.DateTime: time series availability time
  • interval::Dates.Period: time step between forecast windows
  • count::Int: number of forecast windows
  • horizon::Int: length of this time series
InfrastructureSystems.SingleTimeSeries — Type
mutable struct SingleTimeSeries <: StaticTimeSeries
+    name::String
+    data::TimeSeries.TimeArray
+    scaling_factor_multiplier::Union{Nothing, Function}
+    internal::InfrastructureSystemsInternal
+end

A single column of time series data for a particular data field in a Component.

In contrast with a forecast, this can represent one continual time series, such as a series of historical measurements or realizations or a single scenario (e.g. a weather year or different input assumptions).

Arguments

  • name::String: user-defined name
  • data::TimeSeries.TimeArray: timestamp - scalingfactor
  • resolution::Dates.Period: Time duration between steps in the time series. The resolution must be the same throughout the time series
  • scaling_factor_multiplier::Union{Nothing, Function}: Applicable when the time series data are scaling factors. Called on the associated component to convert the values.
  • internal::InfrastructureSystemsInternal
InfrastructureSystems.SingleTimeSeries — Method
SingleTimeSeries(
+    name::AbstractString,
+    filename::AbstractString,
+    component::InfrastructureSystems.InfrastructureSystemsComponent,
+    resolution::Dates.Period;
+    normalization_factor,
+    scaling_factor_multiplier
+) -> SingleTimeSeries
+

Construct SingleTimeSeries from a CSV file. The file must have a column that is the name of the component.

Arguments

  • name::AbstractString: user-defined name
  • filename::AbstractString: name of CSV file containing data
  • component::InfrastructureSystemsComponent: component associated with the data
  • resolution::Dates.Period: resolution of the time series
  • normalization_factor::NormalizationFactor = 1.0: optional normalization factor to apply to each data entry
  • scaling_factor_multiplier::Union{Nothing, Function} = nothing: If the data are scaling factors then this function will be called on the component and applied to the data when get_time_series_array is called.
InfrastructureSystems.SingleTimeSeries — Method
SingleTimeSeries(
+    name::AbstractString,
+    data::Union{DataFrames.DataFrame, TimeSeries.TimeArray};
+    normalization_factor,
+    scaling_factor_multiplier,
+    timestamp
+) -> SingleTimeSeries
+

Construct SingleTimeSeries from a TimeArray or DataFrame.

Arguments

  • name::AbstractString: user-defined name
  • data::Union{TimeSeries.TimeArray, DataFrames.DataFrame}: time series data
  • normalization_factor::NormalizationFactor = 1.0: optional normalization factor to apply to each data entry
  • scaling_factor_multiplier::Union{Nothing, Function} = nothing: If the data are scaling factors then this function will be called on the component and applied to the data when get_time_series_array is called.
  • timestamp = :timestamp: If a DataFrame is passed then this must be the column name that contains timestamps.
InfrastructureSystems.SingleTimeSeries — Method
SingleTimeSeries(
+    src::SingleTimeSeries,
+    name::AbstractString;
+    scaling_factor_multiplier
+) -> SingleTimeSeries
+

Construct SingleTimeSeries that shares the data from an existing instance.

This is useful in cases where you want a component to use the same time series data for two different attribtues.

InfrastructureSystems.SingleTimeSeries — Method
SingleTimeSeries(
+    time_series::SingleTimeSeries,
+    data::TimeSeries.TimeArray
+) -> Any
+

Creates a new SingleTimeSeries from an existing instance and a subset of data.

InfrastructureSystems.SingleTimeSeries — Method
SingleTimeSeries(
+    name::String,
+    resolution::Dates.Period,
+    initial_time::Dates.DateTime,
+    time_steps::Int64
+) -> SingleTimeSeries
+

Construct SingleTimeSeries after constructing a TimeArray from initial_time and time_steps.

InfrastructureSystems.from — Method
from(
+    time_series::SingleTimeSeries,
+    timestamp
+) -> SingleTimeSeries
+

Return a time_series truncated starting with timestamp.

InfrastructureSystems.head — Method
head(time_series::SingleTimeSeries) -> Any
+

Return a time_series with only the first num values.

InfrastructureSystems.iterate_windows — Method
iterate_windows(
+    forecast::DeterministicSingleTimeSeries
+) -> Any
+

Iterate over the windows in a forecast

Examples

for window in iterate_windows(forecast)
+    @show values(maximum(window))
+end
InfrastructureSystems.tail — Method
tail(time_series::SingleTimeSeries) -> Any
+

Return a time_series with only the ending num values.

InfrastructureSystems.to — Method
to(
+    time_series::SingleTimeSeries,
+    timestamp
+) -> SingleTimeSeries
+

Return a time_series truncated after timestamp.

InfrastructureSystems.when — Method
when(
+    time_series::SingleTimeSeries,
+    period::Function,
+    t::Integer
+) -> Any
+

Refer to TimeSeries.when(). Underlying data is copied.

InfrastructureSystems.get_initial_times — Method
get_initial_times(
+    f::Forecast
+) -> DataStructures.SDMKeyIteration{T} where T<:DataStructures.SortedDict
+

Return the initial times in the forecast.

InfrastructureSystems.get_window — Method
get_window(forecast::Forecast, index::Int64; len) -> Any
+

Return the forecast window corresponsing to interval index.

InfrastructureSystems.make_time_array — Method
make_time_array(
+    forecast::Forecast,
+    start_time::Dates.DateTime;
+    len
+) -> Any
+

Return a TimeSeries.TimeArray for one forecast window.

InfrastructureSystems.get_next_time_series_array! — Method
get_next_time_series_array!(
+    cache::InfrastructureSystems.TimeSeriesCache
+) -> Any
+

Return the next TimeSeries.TimeArray.

Returns nothing when all data has been read. Call reset! to restart. Call get_next_time to check the start time.

Reads from storage if the data is not already in cache.

Arguments

  • cache::StaticTimeSeriesCache: cached instance

Examples

cache = ForecastCache(Deterministic, component, "max_active_power")
+window1 = get_next_time_series_array!(cache)
+window2 = get_next_time_series_array!(cache)

System

PowerSystems.System — Type

A power system

System is the main data container in PowerSystems.jl, including basic metadata (base power, frequency), components (network topology, loads, generators, and services), and time series data.

System(base_power)
+System(base_power, buses, components...)
+System(base_power, buses, generators, loads, branches, storage, services; kwargs...)
+System(base_power, buses, generators, loads; kwargs...)
+System(file; kwargs...)
+System(; buses, generators, loads, branches, storage, base_power, services, kwargs...)
+System(; kwargs...)

Arguments

  • base_power::Float64: the base power value for the system
  • buses::Vector{ACBus}: an array of buses
  • components...: Each element (e.g., buses, generators, ...) must be an iterable containing subtypes of Component.

Keyword arguments

  • ext::Dict: Contains user-defined parameters. Should only contain standard types.
  • frequency::Float64: (default = 60.0) Operating frequency (Hz)
  • runchecks::Bool: Run available checks on input fields and when add_component! is called. Throws InvalidValue if an error is found.
  • time_series_in_memory::Bool=false: Store time series data in memory instead of HDF5.
  • time_series_directory::Union{Nothing, String}: Directory for the time series HDF5 file. Defaults to the tmp file system
  • enable_compression::Bool=false: Enable compression of time series data in HDF5.
  • compression::CompressionSettings: Allows customization of HDF5 compression settings.
  • config_path::String: specify path to validation config file
  • unit_system::String: (Default = "SYSTEM_BASE") Set the unit system for per-unitization while getting and setting data ("SYSTEM_BASE", "DEVICE_BASE", or "NATURAL_UNITS")

By default, time series data is stored in an HDF5 file in the tmp file system to prevent large datasets from overwhelming system memory (see Data Storage). If the system's time series data will be larger than the amount of tmp space available, use the time_series_directory parameter to change its location. You can also override the location by setting the environment variable SIENNA_TIME_SERIES_DIRECTORY to another directory.

HDF5 compression is not enabled by default, but you can enable it with enable_compression to get significant storage savings at the cost of CPU time. CompressionSettings can be used to customize the HDF5 compression.

If you know that your dataset will fit in your computer's memory, then you can increase performance by storing it in memory with time_series_in_memory.

Examples

sys = System(100.0; enable_compression = true)
+sys = System(100.0; compression = CompressionSettings(
+    enabled = true,
+    type = CompressionTypes.DEFLATE,  # BLOSC is also supported
+    level = 3,
+    shuffle = true)
+)
+sys = System(100.0; time_series_in_memory = true)
source
PowerSystems.System — Method
System(
+    sys_file::AbstractString,
+    dyr_file::AbstractString;
+    kwargs...
+) -> Any
+

Parse static and dynamic data directly from PSS/e text files. Automatically generates all the relationships between the available dynamic injection models and the static counterpart

Each dictionary indexed by id contains a vector with 5 of its components:

  • Machine
  • Shaft
  • AVR
  • TurbineGov
  • PSS

Files must be parsed from a .raw file (PTI data format) and a .dyr file.

Examples:

raw_file = "Example.raw"
+dyr_file = "Example.dyr"
+sys = System(raw_file, dyr_file)
source
PowerSystems.System — Method
System(
+    file_path::AbstractString;
+    assign_new_uuids,
+    kwargs...
+) -> Any
+

Constructs a System from a file path ending with .m, .RAW, or .json

If the file is JSON then assignnewuuids = true will generate new UUIDs for the system and all components.

source
PowerSystems.System — Method
System(
+    data,
+    base_power::Number;
+    internal,
+    kwargs...
+) -> System
+

Construct a System from InfrastructureSystems.SystemData

source
PowerSystems.System — Method
System(
+    base_power::Float64,
+    buses::Vector{ACBus},
+    components...;
+    kwargs...
+) -> System
+

System constructor when components are constructed externally.

source
PowerSystems.System — Method
System(
+    ::Nothing;
+    buses,
+    generators,
+    loads,
+    branches,
+    storage,
+    base_power,
+    services,
+    kwargs...
+) -> System
+

Constructs a non-functional System for demo purposes.

source
PowerSystems.System — Method
System(base_power::Number; kwargs...) -> System
+

Construct an empty System. Useful for building a System while parsing raw data.

source
PowerSystems.System — Method
System(
+    data::PowerSystemTableData;
+    time_series_resolution,
+    time_series_in_memory,
+    time_series_directory,
+    runchecks,
+    kwargs...
+) -> System
+

Construct a System from PowerSystemTableData data.

Arguments

  • time_series_resolution::Union{DateTime, Nothing}=nothing: only store time_series that match this resolution.
  • time_series_in_memory::Bool=false: Store time series data in memory instead of HDF5 file
  • time_series_directory=nothing: Store time series data in directory instead of tmpfs
  • runchecks::Bool=true: Validate struct fields.

Throws DataFormatError if time_series with multiple resolutions are detected.

  • A time_series has a different resolution than others.
  • A time_series has a different horizon than others.
source
PowerSystems.System — Method
System(pm_data::PowerModelsData; kwargs...) -> Any
+

Constructs a System from PowerModelsData.

Arguments

  • pm_data::Union{PowerModelsData, Union{String, IO}}: PowerModels data object or supported

load flow case (*.m, *.raw)

Keyword arguments

  • ext::Dict: Contains user-defined parameters. Should only contain standard types.
  • runchecks::Bool: Run available checks on input fields and when add_component! is called. Throws InvalidValue if an error is found.
  • time_series_in_memory::Bool=false: Store time series data in memory instead of HDF5.
  • config_path::String: specify path to validation config file
  • pm_data_corrections::Bool=true : Run the PowerModels data corrections (aka :validate in PowerModels)
  • import_all:Bool=false : Import all fields from PTI files

Examples

sys = System(
+    pm_data, config_path = "ACTIVSg25k_validation.json",
+    bus_name_formatter = x->string(x["name"]*"-"*string(x["index"])),
+    load_name_formatter = x->strip(join(x["source_id"], "_"))
+)
source
InfrastructureSystems.from_json — Method
from_json(
+    io::Union{IO, String},
+    ::Type{System};
+    runchecks,
+    assign_new_uuids,
+    kwargs...
+) -> System
+

If assignnewuuids = true, generate new UUIDs for the system and all components.

Warning: time series data is not restored by this method. If that is needed, use the normal process to construct the system from a serialized JSON file instead, such as with System("sys.json").

source
InfrastructureSystems.get_supplemental_attributes — Method
get_supplemental_attributes(
+    filter_func::Function,
+    _::Type{T<:SupplementalAttribute},
+    sys::System
+) -> InfrastructureSystems.FlattenIteratorWrapper{T, I} where {T<:SupplementalAttribute, I<:(Vector)}
+

Returns an iterator of supplemental attributes. T can be concrete or abstract. Call collect on the result if an array is desired.

Examples

iter = get_supplemental_attributes(GeometricDistributionForcedOutage, sys)
+iter = get_supplemental_attributes(Outage, sys)
+iter = get_supplemental_attributes(x -> get_mean_time_to_recovery(x) ==  >= 0.5, GeometricDistributionForcedOutage, sys)
+outages = get_supplemental_attributes(GeometricDistributionForcedOutage, sys) do outage
+    get_mean_time_to_recovery(x) ==  >= 0.5
+end
+outages = collect(get_supplemental_attributes(GeometricDistributionForcedOutage, sys))

See also: iterate_supplemental_attributes

source
InfrastructureSystems.get_time_series_multiple — Function
get_time_series_multiple(sys::System; ...) -> Channel{Any}
+get_time_series_multiple(
+    sys::System,
+    filter_func;
+    type,
+    name
+) -> Channel{Any}
+

Return an iterator of time series in order of initial time.

Note that passing a filter function can be much slower than the other filtering parameters because it reads time series data from media.

Call collect on the result to get an array.

Arguments

  • data::SystemData: system
  • filter_func = nothing: Only return time series for which this returns true.
  • type = nothing: Only return time series with this type.
  • name = nothing: Only return time series matching this value.

Examples

for time_series in get_time_series_multiple(sys)
+    @show time_series
+end
+
+ts = collect(get_time_series_multiple(sys; type = SingleTimeSeries))
source
InfrastructureSystems.set_name! — Method
set_name!(
+    component::Component,
+    name::AbstractString
+) -> AbstractString
+

Set the name of a component.

Throws an exception if the component is attached to a system.

source
InfrastructureSystems.set_name! — Method
set_name!(
+    sys::System,
+    component::Component,
+    name::AbstractString
+)
+

Set the name for a component that is attached to the system.

source
InfrastructureSystems.to_json — Method
to_json(
+    sys::System,
+    filename::AbstractString;
+    user_data,
+    pretty,
+    force,
+    runchecks
+)
+

Serializes a system to a JSON file and saves time series to an HDF5 file.

Arguments

  • sys::System: system
  • filename::AbstractString: filename to write

Keyword arguments

  • user_data::Union{Nothing, Dict} = nothing: optional metadata to record
  • pretty::Bool = false: whether to pretty-print the JSON
  • force::Bool = false: whether to overwrite existing files
  • check::Bool = false: whether to run system validation checks

Refer to check_component for exceptions thrown if check = true.

source
PowerSystems.add_component! — Method
add_component!(
+    sys::System,
+    dyn_injector::DynamicInjection,
+    static_injector::StaticInjection;
+    kwargs...
+)
+

Add a dynamic injector to the system.

A component cannot be added to more than one System. Throws ArgumentError if the name does not match the static_injector name. Throws ArgumentError if the static_injector is not attached to the system.

All rules for the generic add_component! method also apply.

source
PowerSystems.add_component! — Method
add_component!(
+    sys::System,
+    component::Component;
+    skip_validation,
+    kwargs...
+)
+

Add a component to the system.

A component cannot be added to more than one System. Throws ArgumentError if the component's name is already stored for its concrete type. Throws ArgumentError if any Component-specific rule is violated. Throws InvalidValue if any of the component's field values are outside of defined valid range.

Examples

sys = System(100.0)
+
+# Add a single component.
+add_component!(sys, bus)
+
+# Add many at once.
+buses = [bus1, bus2, bus3]
+generators = [gen1, gen2, gen3]
+foreach(x -> add_component!(sys, x), Iterators.flatten((buses, generators)))

See also add_components!.

source
PowerSystems.add_components! — Method
add_components!(sys::System, components)
+

Add many components to the system at once.

A component cannot be added to more than one System. Throws ArgumentError if the component's name is already stored for its concrete type. Throws ArgumentError if any Component-specific rule is violated. Throws InvalidValue if any of the component's field values are outside of defined valid range.

Examples

sys = System(100.0)
+
+buses = [bus1, bus2, bus3]
+generators = [gen1, gen2, gen3]
+add_components!(sys, Iterators.flatten((buses, generators))
source
PowerSystems.add_service! — Method
add_service!(device::Device, service::Service, sys::System)
+

Similar to add_service! but for Service and Device already stored in the system. Performs validation checks on the device and the system

Arguments

  • device::Device: Device
  • service::Service: Service
  • sys::System: system
source
PowerSystems.add_service! — Method
add_service!(
+    sys::System,
+    service::ConstantReserveGroup,
+    contributing_services::Vector{<:Service};
+    skip_validation,
+    kwargs...
+)
+

Similar to add_component! but for ConstantReserveGroup.

Arguments

  • sys::System: system
  • service::ConstantReserveGroup: service to add
  • contributing_services: contributing services to the group
source
PowerSystems.add_service! — Method
add_service!(
+    sys::System,
+    service::ConstantReserveGroup;
+    skip_validation,
+    kwargs...
+)
+

Similar to add_component! but for ConstantReserveGroup.

Arguments

  • sys::System: system
  • service::ConstantReserveGroup: service to add
source
PowerSystems.add_service! — Method
add_service!(
+    sys::System,
+    service::Service,
+    contributing_devices;
+    kwargs...
+)
+

Similar to add_component! but for services.

Arguments

  • sys::System: system
  • service::Service: service to add
  • contributing_devices: Must be an iterable of type Device
source
PowerSystems.add_service! — Method
add_service!(
+    sys::System,
+    service::Service,
+    contributing_device::Device;
+    kwargs...
+)
+

Similar to add_component! but for services.

Arguments

  • sys::System: system
  • service::Service: service to add
  • contributing_device::Device: Valid Device
source
PowerSystems.add_supplemental_attribute! — Method
add_supplemental_attribute!(
+    sys::System,
+    component::Component,
+    attribute::SupplementalAttribute
+)
+

Add a supplemental attribute to the component. The attribute may already be attached to a different component.

source
PowerSystems.add_time_series! — Method
add_time_series!(
+    sys::System,
+    metadata_file::AbstractString;
+    resolution
+) -> Vector{TimeSeriesKey}
+

Add time series data from a metadata file or metadata descriptors.

Arguments

  • sys::System: system
  • metadata_file::AbstractString: metadata file for timeseries that includes an array of IS.TimeSeriesFileMetadata instances or a vector.
  • resolution::DateTime.Period=nothing: skip time series that don't match this resolution.
source
PowerSystems.add_time_series! — Method
add_time_series!(
+    sys::System,
+    components,
+    time_series::TimeSeriesData;
+    features...
+) -> TimeSeriesKey
+

Add the same time series data to multiple components.

This function stores a single copy of the data. Each component will store a reference to that data. This is significantly more efficent than calling add_time_series! for each component individually with the same data because in this case, only one time series array is stored.

Throws ArgumentError if a component is not stored in the system.

source
PowerSystems.add_time_series! — Method
add_time_series!(
+    sys::System,
+    component::Component,
+    time_series::TimeSeriesData;
+    features...
+) -> TimeSeriesKey
+

Add time series data to a component.

Throws ArgumentError if the component is not stored in the system.

source
PowerSystems.add_time_series! — Method
add_time_series!(
+    sys::System,
+    file_metadata::Vector{InfrastructureSystems.TimeSeriesFileMetadata};
+    resolution
+) -> Vector{TimeSeriesKey}
+

Add time series data from a metadata file or metadata descriptors.

Arguments

  • sys::System: system
  • timeseries_metadata::Vector{IS.TimeSeriesFileMetadata}: metadata for timeseries
  • resolution::DateTime.Period=nothing: skip time series that don't match this resolution.
source
PowerSystems.bulk_add_time_series! — Method
bulk_add_time_series!(
+    sys::System,
+    associations;
+    batch_size
+) -> Vector{TimeSeriesKey}
+

Add many time series in bulk

This method is advantageous when adding thousands of time series arrays because of the overhead in writing the time series to the underlying storage.

Arguments

  • sys::System: system
  • associations: Iterable of TimeSeriesAssociation instances. Using a Vector is not recommended. Pass a Generator or Iterator to avoid loading all time series data into system memory at once.
  • batch_size::Int: (Default = 100) Number of time series to add per batch.

Examples

# Assumes `read_time_series` will return data appropriate for Deterministic forecasts
+# based on the generator name and the filenames match the component and time series names.
+resolution = Dates.Hour(1)
+associations = (
+    IS.TimeSeriesAssociation(
+        gen,
+        Deterministic(
+            data = read_time_series(get_name(gen) * ".csv"),
+            name = "get_max_active_power",
+            resolution=resolution),
+    )
+    for gen in get_components(ThermalStandard, sys)
+)
+bulk_add_time_series!(sys, associations)

See also: open_time_series_store! to minimize HDF5 file handle overhead if you must add time series arrays one at a time

source
PowerSystems.check_component — Method
check_component(sys::System, component::Component)
+

Check the values of a component.

Throws InvalidValue if any of the component's field values are outside of defined valid range or if the custom validate method for the type fails its check.

source
PowerSystems.check_time_series_consistency — Method
check_time_series_consistency(
+    sys::System,
+    _::Type{T<:TimeSeriesData}
+) -> Union{Nothing, Tuple{Any, Any}}
+

Checks time series in the system for inconsistencies.

For SingleTimeSeries, returns a Tuple of initial_timestamp and length.

This is a no-op for subtypes of Forecast because those are already guaranteed to be consistent.

Throws InfrastructureSystems.InvalidValue if any time series is inconsistent.

source
PowerSystems.convert_component! — Method
convert_component!(
+    sys::System,
+    line::Line,
+    linetype::Type{MonitoredLine};
+    kwargs...
+)
+

Converts a Line component to a MonitoredLine component and replaces the original in the system

source
PowerSystems.convert_component! — Method
convert_component!(
+    sys::System,
+    line::MonitoredLine,
+    linetype::Type{Line};
+    kwargs...
+)
+

Converts a MonitoredLine component to a Line component and replaces the original in the system.

source
PowerSystems.convert_component! — Method
convert_component!(
+    sys::System,
+    old_load::PowerLoad,
+    new_type::Type{StandardLoad};
+    kwargs...
+)
+

Converts a PowerLoad component to a StandardLoad component and replaces the original in the system. Does not set any fields in StandardLoad that lack a PowerLoad equivalent.

source
PowerSystems.from_subsystem — Method
from_subsystem(
+    sys::System,
+    subsystem::AbstractString;
+    runchecks
+) -> System
+

Construct a System from a subsystem of an existing system.

source
PowerSystems.get_available_components — Method
get_available_components(
+    _::Type{T<:Component},
+    sys::System
+) -> InfrastructureSystems.FlattenIteratorWrapper{T, I} where {T<:Component, I<:(Vector)}
+

Gets components availability. Requires type T to have the method get_available implemented.

source
PowerSystems.get_bus — Method
get_bus(
+    sys::System,
+    name::AbstractString
+) -> Union{Nothing, InfrastructureSystems.InfrastructureSystemsComponent}
+

Return bus with name.

source
PowerSystems.get_buses — Method
get_buses(
+    sys::System,
+    aggregator::AggregationTopology
+) -> Vector{ACBus}
+

Return a vector of buses contained within the AggregationTopology.

source
PowerSystems.get_buses — Method
get_buses(
+    sys::System,
+    bus_numbers::Set{Int64}
+) -> Vector{ACBus}
+

Return all buses values with bus_numbers.

source
PowerSystems.get_component — Method
get_component(
+    sys::System,
+    uuid::Base.UUID
+) -> InfrastructureSystems.InfrastructureSystemsComponent
+

Get the component by UUID.

source
PowerSystems.get_component — Method
get_component(
+    _::Type{T<:Component},
+    sys::System,
+    name::AbstractString
+) -> Union{Nothing, InfrastructureSystems.InfrastructureSystemsComponent}
+

Get the component of type T with name. Returns nothing if no component matches. If T is an abstract type then the names of components across all subtypes of T must be unique.

See get_components_by_name for abstract types with non-unique names across subtypes.

Throws ArgumentError if T is not a concrete type and there is more than one component with requested name

source
PowerSystems.get_components — Method
get_components(
+    sys::System,
+    attribute::SupplementalAttribute
+) -> Any
+

Return a vector of components that are attached to the supplemental attribute.

source
PowerSystems.get_components — Method
get_components(
+    ::Type{T<:Component},
+    sys::System;
+    subsystem_name
+) -> InfrastructureSystems.FlattenIteratorWrapper{T, I} where {T<:Component, I<:(Vector)}
+

Returns an iterator of components. T can be concrete or abstract. Call collect on the result if an array is desired.

Examples

iter = PowerSystems.get_components(ThermalStandard, sys)
+iter = PowerSystems.get_components(Generator, sys)
+iter = PowerSystems.get_components(x -> PowerSystems.get_available(x), Generator, sys)
+thermal_gens = get_components(ThermalStandard, sys) do gen
+    get_available(gen)
+end
+generators = collect(PowerSystems.get_components(Generator, sys))
+

See also: iterate_components

source
PowerSystems.get_components_by_name — Method
get_components_by_name(
+    _::Type{T<:Component},
+    sys::System,
+    name::AbstractString
+) -> Vector{T} where T<:InfrastructureSystems.InfrastructureSystemsComponent
+

Get the components of abstract type T with name. Note that PowerSystems enforces unique names on each concrete type but not across concrete types.

See get_component if the concrete type is known.

Throws ArgumentError if T is not an abstract type.

source
PowerSystems.get_components_in_aggregation_topology — Method
get_components_in_aggregation_topology(
+    _::Type{T<:StaticInjection},
+    sys::System,
+    aggregator::AggregationTopology
+) -> Vector{T} where T<:StaticInjection
+

Return a vector of components with buses in the AggregationTopology.

source
PowerSystems.get_ext — Method
get_ext(sys::System) -> Union{Nothing, Dict{String, Any}}
+

Return a user-modifiable dictionary to store extra information.

source
PowerSystems.get_time_series_resolutions — Method
get_time_series_resolutions(
+    sys::System;
+    time_series_type
+) -> Any
+

Return a sorted Vector of distinct resolutions for all time series of the given type (or all types).

source
PowerSystems.has_component — Method
has_component(
+    sys::System,
+    T::Type{<:Component},
+    name::AbstractString
+) -> Bool
+

Check to see if the component of type T with name exists.

source
PowerSystems.iterate_components — Method
iterate_components(
+    sys::System
+) -> Base.Iterators.Flatten{Base.Generator{Base.ValueIterator{Dict{DataType, Dict{String, <:InfrastructureSystems.InfrastructureSystemsComponent}}}, InfrastructureSystems.var"#112#113"}}
+

Iterates over all components.

Examples

for component in iterate_components(sys)
+    @show component
+end

See also: get_components

source
PowerSystems.iterate_supplemental_attributes — Method
iterate_supplemental_attributes(
+    sys::System
+) -> Base.Iterators.Flatten{Base.Generator{Base.ValueIterator{Dict{DataType, Dict{Base.UUID, <:SupplementalAttribute}}}, InfrastructureSystems.var"#112#113"}}
+

Iterates over all supplemental_attributes.

Examples

for supplemental_attribute in iterate_supplemental_attributes(sys)
+    @show supplemental_attribute
+end

See also: get_supplemental_attributes

source
PowerSystems.open_time_series_store! — Function
open_time_series_store!(
+    func::Function,
+    sys::System;
+    ...
+) -> Any
+open_time_series_store!(
+    func::Function,
+    sys::System,
+    mode,
+    args...;
+    kwargs...
+) -> Any
+

Open the time series store for bulk additions or reads

This is recommended before calling add_time_series! many times because of the overhead associated with opening and closing an HDF5 file.

This is not necessary for an in-memory time series store.

Examples

# Assume there is a system with an array of Components and SingleTimeSeries
+# stored in the variables components and single_time_series, respectively
+open_time_series_store!(sys, "r+") do
+    for (component, ts) in zip(components, single_time_series)
+        add_time_series!(sys, component, ts)
+    end
+end

You can also use this function to make reads faster. Change the mode from "r+" to "r" to open the file read-only.

See also: bulk_add_time_series!

source
PowerSystems.remove_component! — Method
remove_component!(sys::System, component::Component)
+

Remove a component from the system by its value.

Throws ArgumentError if the component is not stored.

source
PowerSystems.remove_component! — Method
remove_component!(
+    _::Type{T<:Component},
+    sys::System,
+    name::AbstractString
+)
+

Remove a component from the system by its name.

Throws ArgumentError if the component is not stored.

source
PowerSystems.remove_supplemental_attribute! — Method
remove_supplemental_attribute!(
+    sys::System,
+    component::Component,
+    attribute::SupplementalAttribute
+)
+

Remove the supplemental attribute from the component. The attribute will be removed from the system if it is not attached to any other component.

source
PowerSystems.remove_time_series! — Method
remove_time_series!(
+    sys::System,
+    _::Type{T<:TimeSeriesData},
+    component::Component,
+    name::String
+)
+

Remove the time series data for a component and time series type.

source
PowerSystems.remove_time_series! — Method
remove_time_series!(sys::System, _::Type{T<:TimeSeriesData})
+

Remove all the time series data for a time series type.

See also: clear_time_series!

If you are storing time series data in an HDF5 file, remove_time_series! does not actually free up file space (HDF5 behavior). If you want to remove all or most time series instances then consider using clear_time_series!. It will delete the HDF5 file and create a new one. PowerSystems has plans to automate this type of workflow.

source
PowerSystems.set_runchecks! — Method
set_runchecks!(sys::System, value::Bool)
+

Enable or disable system checks. Applies to component addition as well as overall system consistency.

source
PowerSystems.set_units_base_system! — Method
set_units_base_system!(system::System, settings::String)
+

Sets the units base for the getter functions on the devices. It modifies the behavior of all getter functions

source
PowerSystems.transform_single_time_series! — Method
transform_single_time_series!(
+    sys::System,
+    horizon::Dates.Period,
+    interval::Dates.Period
+)
+

Transform all instances of SingleTimeSeries in a System to DeterministicSingleTimeSeries

This can be used to generate a perfect forecast from historical measurements or realizations when actual forecasts are unavailable, without unnecessarily duplicating data.

If all SingleTimeSeries instances cannot be transformed then none will be.

Any existing DeterministicSingleTimeSeries forecasts will be deleted even if the inputs are invalid.

Arguments

  • sys::System: System containing the components.
  • horizon::Dates.Period: desired horizon of each forecast window
  • interval::Dates.Period: desired interval between forecast windows
source
PowerSystems.show_components — Function
show_components(
+    sys::System,
+    component_type::Type{<:Component};
+    ...
+)
+show_components(
+    sys::System,
+    component_type::Type{<:Component},
+    additional_columns::Union{Dict, Vector};
+    kwargs...
+)
+

Show all components of the given type in a table.

Arguments

  • sys::System: System containing the components.
  • component_type::Type{<:Component}: Type to display. Must be a concrete type.
  • additional_columns::Union{Dict, Vector}: Additional columns to display. The Dict option is a mapping of column name to function. The function must accept a component. The Vector option is an array of field names for the component_type.

Extra keyword arguments are forwarded to PrettyTables.pretty_table.

Examples

show_components(sys, ThermalStandard)
+show_components(sys, ThermalStandard, Dict("has_time_series" => x -> has_time_series(x)))
+show_components(sys, ThermalStandard, [:active_power, :reactive_power])
source

Additional Component Methods

PowerSystems.get_max_reactive_power — Method
get_max_reactive_power(d::RenewableDispatch) -> Any
+

Return the max reactive power for the Renewable Generation calculated as the rating * powerfactor if reactivepower_limits is nothing

source
InfrastructureSystems.get_time_series — Function
get_time_series(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    key::TimeSeriesKey
+) -> Any
+get_time_series(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    key::TimeSeriesKey,
+    start_time::Union{Nothing, Dates.DateTime}
+) -> Any
+get_time_series(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    key::TimeSeriesKey,
+    start_time::Union{Nothing, Dates.DateTime},
+    len::Union{Nothing, Int64}
+) -> Any
+get_time_series(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    key::TimeSeriesKey,
+    start_time::Union{Nothing, Dates.DateTime},
+    len::Union{Nothing, Int64},
+    count::Union{Nothing, Int64}
+) -> Any
+

Return the exact stored data in a time series, using a time series key look up

This will load all forecast windows into memory by default. Be aware of how much data is stored.

Specify start_time and len if you only need a subset of data.

Does not apply a scaling factor multiplier.

Arguments

  • owner::TimeSeriesOwners: Component or attribute containing the time series
  • key::TimeSeriesKey: the time series' key
  • start_time::Union{Nothing, Dates.DateTime} = nothing: If nothing, use the initial_timestamp of the time series. If the time series is a subtype of Forecast then start_time must be the first timestamp of a window.
  • len::Union{Nothing, Int} = nothing: Length in the time dimension. If nothing, use the entire length.
  • count::Union{Nothing, Int} = nothing: Only applicable to subtypes of Forecast. Number of forecast windows starting at start_time to return. Defaults to all available.
  • features...: User-defined tags that differentiate multiple time series arrays for the same component attribute, such as different arrays for different scenarios or years
InfrastructureSystems.get_time_series — Method
get_time_series(
+    ::Type{T<:TimeSeriesData},
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    name::AbstractString;
+    start_time,
+    len,
+    count,
+    features...
+) -> Any
+

Return the exact stored data in a time series

This will load all forecast windows into memory by default. Be aware of how much data is stored.

Specify start_time and len if you only need a subset of data.

Does not apply a scaling factor multiplier.

Arguments

  • ::Type{T}: Concrete subtype of TimeSeriesData to return
  • owner::TimeSeriesOwners: Component or attribute containing the time series
  • name::AbstractString: name of time series
  • start_time::Union{Nothing, Dates.DateTime} = nothing: If nothing, use the initial_timestamp of the time series. If T is a subtype of Forecast then start_time must be the first timestamp of a window.
  • len::Union{Nothing, Int} = nothing: Length in the time dimension. If nothing, use the entire length.
  • count::Union{Nothing, Int} = nothing: Only applicable to subtypes of Forecast. Number of forecast windows starting at start_time to return. Defaults to all available.
  • features...: User-defined tags that differentiate multiple time series arrays for the same component attribute, such as different arrays for different scenarios or years

See also: get_time_series_array, get_time_series_values.

InfrastructureSystems.get_time_series_array — Function
get_time_series_array(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    time_series::StaticTimeSeries;
+    ...
+) -> Any
+get_time_series_array(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    time_series::StaticTimeSeries,
+    start_time::Union{Nothing, Dates.DateTime};
+    len,
+    ignore_scaling_factors
+) -> Any
+

Return a TimeSeries.TimeArray from a cached StaticTimeSeries instance.

If the time series data are scaling factors, the returned data will be scaled by the scaling factor multiplier by default.

Arguments

  • owner::TimeSeriesOwners: Component or attribute containing the time series
  • time_series::StaticTimeSeries: subtype of StaticTimeSeries (e.g., SingleTimeSeries)
  • start_time::Union{Nothing, Dates.DateTime} = nothing: the first timestamp to retrieve. If nothing, use the initial_timestamp of the time series.
  • len::Union{Nothing, Int} = nothing: Length of time-series to retrieve (i.e. number of timestamps). If nothing, use the entire length
  • ignore_scaling_factors = false: If true, the time-series data will be multiplied by the result of calling the stored scaling_factor_multiplier function on the owner

See also: get_time_series_values, get_time_series_timestamps, StaticTimeSeriesCache.

InfrastructureSystems.get_time_series_array — Method
get_time_series_array(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    forecast::Forecast,
+    start_time::Dates.DateTime;
+    len,
+    ignore_scaling_factors
+) -> Any
+

Return a TimeSeries.TimeArray for one forecast window from a cached Forecast instance

If the time series data are scaling factors, the returned data will be scaled by the scaling factor multiplier by default.

Arguments

  • owner::TimeSeriesOwners: Component or attribute containing the time series
  • forecast::Forecast: a concrete subtype of Forecast
  • start_time::Union{Nothing, Dates.DateTime} = nothing: the first timestamp of one of the forecast windows
  • len::Union{Nothing, Int} = nothing: Length of time-series to retrieve (i.e. number of timestamps). If nothing, use the entire length.
  • ignore_scaling_factors = false: If true, the time-series data will be multiplied by the result of calling the stored scaling_factor_multiplier function on the owner

See also get_time_series_values, get_time_series_timestamps, ForecastCache.

InfrastructureSystems.get_time_series_array — Method
get_time_series_array(
+    ::Type{T<:TimeSeriesData},
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    name::AbstractString;
+    start_time,
+    len,
+    ignore_scaling_factors,
+    features...
+) -> Any
+

Return a TimeSeries.TimeArray from storage for the given time series parameters.

If the time series data are scaling factors, the returned data will be scaled by the scaling factor multiplier by default.

This will load all forecast windows into memory by default. Be aware of how much data is stored.

Specify start_time and len if you only need a subset of data.

Arguments

  • ::Type{T}: the type of time series (a concrete subtype of TimeSeriesData)
  • owner::TimeSeriesOwners: Component or attribute containing the time series
  • name::AbstractString: name of time series
  • start_time::Union{Nothing, Dates.DateTime} = nothing: If nothing, use the initial_timestamp of the time series. If T is a subtype of Forecast then start_time must be the first timestamp of a window.
  • len::Union{Nothing, Int} = nothing: Length of time-series to retrieve (i.e. number of timestamps). If nothing, use the entire length.
  • ignore_scaling_factors = false: If true, the time-series data will be multiplied by the result of calling the stored scaling_factor_multiplier function on the owner
  • features...: User-defined tags that differentiate multiple time series arrays for the same component attribute, such as different arrays for different scenarios or years

See also: get_time_series_values, get_time_series_timestamps, get_time_series

InfrastructureSystems.get_time_series_timestamps — Function
get_time_series_timestamps(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    time_series::StaticTimeSeries;
+    ...
+) -> Vector{D} where D<:Dates.TimeType
+get_time_series_timestamps(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    time_series::StaticTimeSeries,
+    start_time::Union{Nothing, Dates.DateTime};
+    len
+) -> Vector{D} where D<:Dates.TimeType
+

Return a vector of timestamps from a cached StaticTimeSeries instance.

Arguments

  • owner::TimeSeriesOwners: Component or attribute containing the time series
  • time_series::StaticTimeSeries: subtype of StaticTimeSeries (e.g., SingleTimeSeries)
  • start_time::Union{Nothing, Dates.DateTime} = nothing: the first timestamp to retrieve. If nothing, use the initial_timestamp of the time series.
  • len::Union{Nothing, Int} = nothing: Length of time-series to retrieve (i.e. number of timestamps). If nothing, use the entire length

See also: get_time_series_array, get_time_series_values, StaticTimeSeriesCache.

InfrastructureSystems.get_time_series_timestamps — Function
get_time_series_timestamps(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    forecast::Forecast;
+    ...
+)
+get_time_series_timestamps(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    forecast::Forecast,
+    start_time::Union{Nothing, Dates.DateTime};
+    len
+) -> Vector{D} where D<:Dates.TimeType
+

Return a vector of timestamps from a cached Forecast instance.

Arguments

  • owner::TimeSeriesOwners: Component or attribute containing the time series
  • forecast::Forecast: a concrete subtype of Forecast
  • start_time::Union{Nothing, Dates.DateTime} = nothing: the first timestamp of one of the forecast windows
  • len::Union{Nothing, Int} = nothing: Length of time-series to retrieve (i.e. number of timestamps). If nothing, use the entire length.

See also: get_time_series_array, get_time_series_values, ForecastCache.

InfrastructureSystems.get_time_series_timestamps — Method
get_time_series_timestamps(
+    ::Type{T<:TimeSeriesData},
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    name::AbstractString;
+    start_time,
+    len,
+    features...
+) -> Vector{D} where D<:Dates.TimeType
+

Return a vector of timestamps from storage for the given time series parameters.

Arguments

  • ::Type{T}: the type of time series (a concrete subtype of TimeSeriesData)
  • owner::TimeSeriesOwners: Component or attribute containing the time series
  • name::AbstractString: name of time series
  • start_time::Union{Nothing, Dates.DateTime} = nothing: If nothing, use the initial_timestamp of the time series. If T is a subtype of Forecast then start_time must be the first timestamp of a window.
  • len::Union{Nothing, Int} = nothing: Length of time-series to retrieve (i.e. number of timestamps). If nothing, use the entire length.
  • features...: User-defined tags that differentiate multiple time series arrays for the same component attribute, such as different arrays for different scenarios or years

See also: get_time_series_array, get_time_series_values

InfrastructureSystems.get_time_series_values — Function
get_time_series_values(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    time_series::StaticTimeSeries;
+    ...
+) -> Any
+get_time_series_values(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    time_series::StaticTimeSeries,
+    start_time::Union{Nothing, Dates.DateTime};
+    len,
+    ignore_scaling_factors
+) -> Any
+

Return an vector of timeseries data without timestamps from a cached StaticTimeSeries instance

Arguments

  • owner::TimeSeriesOwners: Component or attribute containing the time series
  • time_series::StaticTimeSeries: subtype of StaticTimeSeries (e.g., SingleTimeSeries)
  • start_time::Union{Nothing, Dates.DateTime} = nothing: the first timestamp to retrieve. If nothing, use the initial_timestamp of the time series.
  • len::Union{Nothing, Int} = nothing: Length of time-series to retrieve (i.e. number of timestamps). If nothing, use the entire length
  • ignore_scaling_factors = false: If true, the time-series data will be multiplied by the result of calling the stored scaling_factor_multiplier function on the owner

See also: get_time_series_array, get_time_series_timestamps, StaticTimeSeriesCache.

InfrastructureSystems.get_time_series_values — Method
get_time_series_values(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    forecast::Forecast,
+    start_time::Dates.DateTime;
+    len,
+    ignore_scaling_factors
+) -> Any
+

Return an vector of timeseries data without timestamps for one forecast window from a cached Forecast instance.

Arguments

  • owner::TimeSeriesOwners: Component or attribute containing the time series
  • forecast::Forecast: a concrete subtype of Forecast
  • start_time::Union{Nothing, Dates.DateTime} = nothing: the first timestamp of one of the forecast windows
  • len::Union{Nothing, Int} = nothing: Length of time-series to retrieve (i.e. number of timestamps). If nothing, use the entire length.
  • ignore_scaling_factors = false: If true, the time-series data will be multiplied by the result of calling the stored scaling_factor_multiplier function on the owner

See also: get_time_series_array, get_time_series_timestamps, ForecastCache.

InfrastructureSystems.get_time_series_values — Method
get_time_series_values(
+    ::Type{T<:TimeSeriesData},
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute},
+    name::AbstractString;
+    start_time,
+    len,
+    ignore_scaling_factors,
+    features...
+) -> Any
+

Return an vector of timeseries data without timestamps from storage

If the data size is small and this will be called many times, consider using the version that accepts a cached TimeSeriesData instance.

Arguments

  • ::Type{T}: type of the time series (a concrete subtype of TimeSeriesData)
  • owner::TimeSeriesOwners: Component or attribute containing the time series
  • name::AbstractString: name of time series
  • start_time::Union{Nothing, Dates.DateTime} = nothing: If nothing, use the initial_timestamp of the time series. If T is a subtype of Forecast then start_time must be the first timestamp of a window.
  • len::Union{Nothing, Int} = nothing: Length of time-series to retrieve (i.e. number of timestamps). If nothing, use the entire length.
  • ignore_scaling_factors = false: If true, the time-series data will be multiplied by the result of calling the stored scaling_factor_multiplier function on the owner
  • features...: User-defined tags that differentiate multiple time series arrays for the same component attribute, such as different arrays for different scenarios or years

See also: get_time_series_array, get_time_series_timestamps, get_time_series

InfrastructureSystems.TimeSeriesAssociation — Type

Defines an association between a time series owner (component or supplemental attribute) and the time series metadata.

Examples

association1 = TimeSeriesAssociation(component, time_series)
+association2 = TimeSeriesAssociation(component, time_series, scenario = "high")
InfrastructureSystems.CompressionSettings — Type
CompressionSettings(enabled, type, level, shuffle)

Provides customization of HDF5 compression settings.

  • enabled::Bool: Controls whether compression is enabled.

  • type::CompressionTypes: Specifies the type of compression to use.

  • level::Int64: Supported values are 0-9. Higher values deliver better compression ratios but take longer.

  • shuffle::Bool: Controls whether to enable the shuffle filter. Used with DEFLATE.

Refer to the HDF5.jl and HDF5 documentation for more details on the options.

Example

settings = CompressionSettings(
+    enabled = true,
+    type = CompressionTypes.DEFLATE,  # BLOSC is also supported
+    level = 3,
+    shuffle = true,
+)
InfrastructureSystems.show_time_series — Method
show_time_series(
+    owner::Union{InfrastructureSystems.InfrastructureSystemsComponent, SupplementalAttribute}
+)
+

Show a table with time series data attached to the component.

InfrastructureSystems.ForecastCache — Method

Construct ForecastCache to automatically control caching of forecast data. Maintains some count of forecast windows in memory based on cache_size_bytes.

Call Base.iterate or get_next_time_series_array! to retrieve data. Each iteration will return a TimeSeries.TimeArray covering one forecast window of length horizon_count.

Arguments

  • ::Type{T}: subtype of Forecast
  • component::InfrastructureSystemsComponent: component
  • name::AbstractString: forecast name
  • start_time::Union{Nothing, Dates.DateTime} = nothing: forecast start time
  • horizon_count::Union{Nothing, Int} = nothing: forecast horizon count
  • cache_size_bytes = TIME_SERIES_CACHE_SIZE_BYTES: maximum size of data to keep in memory
  • ignore_scaling_factors = false: controls whether to ignore scaling_factor_multiplier in the time series instance
InfrastructureSystems.StaticTimeSeriesCache — Method

Construct StaticTimeSeriesCache to automatically control caching of time series data. Maintains rows of data in memory based on cache_size_bytes.

Call Base.iterate or get_time_series_array to retrieve data. Each iteration will return a TimeSeries.TimeArray of size 1.

Arguments

  • ::Type{T}: subtype of StaticTimeSeries
  • component::InfrastructureSystemsComponent: component
  • name::AbstractString: time series name
  • cache_size_bytes = TIME_SERIES_CACHE_SIZE_BYTES: maximum size of data to keep in memory
  • ignore_scaling_factors = false: controls whether to ignore scalingfactormultiplier in the time series instance

Parsing

PowerSystems.PowerSystemTableData — Method
PowerSystemTableData(
+    directory::AbstractString,
+    base_power::Float64,
+    user_descriptor_file::AbstractString;
+    descriptor_file,
+    generator_mapping_file,
+    timeseries_metadata_file
+) -> PowerSystemTableData
+

Reads in all the data stored in csv files The general format for data is folder: gen.csv branch.csv bus.csv .. load.csv

Arguments

  • directory::AbstractString: directory containing CSV files
  • base_power::Float64: base power for System
  • user_descriptor_file::AbstractString: customized input descriptor file
  • descriptor_file=POWER_SYSTEM_DESCRIPTOR_FILE: PowerSystems descriptor file
  • generator_mapping_file=GENERATOR_MAPPING_FILE: generator mapping configuration file
source
PowerSystems.PowerModelsData — Method
PowerModelsData(
+    file::Union{IO, String};
+    kwargs...
+) -> PowerModelsData
+

Constructs PowerModelsData from a raw file. Currently Supports MATPOWER and PSSE data files parsed by PowerModels.

source
PowerSystems.TamuSystem — Method
TamuSystem(tamu_folder::AbstractString; kwargs...) -> Any
+

Creates a system from a PSS/e .RAW (v33) load flow case, and an associated .csv with MW load time series data. The format is established by the Texas A&M University Test Case Archive

The general format for data is folder: [casename].raw [casename]loadtimeseriesMW.csv

Arguments

  • directory::AbstractString: directory containing RAW and CSV files

Examples

sys = TamuSystem(
+    "./ACTIVSg25k",
+    config_path = "ACTIVSg25k_validation.json",
+    bus_name_formatter = x->string(x["name"]*"-"*string(x["index"])),
+    load_name_formatter = x->strip(join(x["source_id"], "_"))
+)
source
PowerSystems.add_dyn_injectors! — Method
add_dyn_injectors!(sys::System, dyr_file::AbstractString)
+

Add to a system already created the dynamic components. The system should already be parsed from a .raw file.

Examples:

dyr_file = "Example.dyr"
+add_dyn_injectors!(sys, dyr_file)
source

Logging

PowerSystems.configure_logging — Method
configure_logging(
+;
+    console_level,
+    file_level,
+    filename
+) -> MultiLogger
+

Creates console and file loggers.

Note: Log messages may not be written to the file until flush() or close() is called on the returned logger.

Arguments

  • console_level = Logging.Error: level for console messages
  • file_level = Logging.Info: level for file messages
  • filename::Union{Nothing, AbstractString} = "power-systems.log": log file; pass nothing to disable file logging

Example

logger = configure_logging(console_level = Logging.Info)
+@info "log message"
+close(logger)
source
diff --git a/previews/PR1171/api/type_tree/index.html b/previews/PR1171/api/type_tree/index.html new file mode 100644 index 0000000000..c26a8aecff --- /dev/null +++ b/previews/PR1171/api/type_tree/index.html @@ -0,0 +1,230 @@ + +Type Hierarchy · PowerSystems.jl
Edit on GitHub

Type Hierarchy

Here is the complete PowerSystems.jl type hierarchy:

InfrastructureSystems.InfrastructureSystemsType
+ ├─ InfrastructureSystems.AbstractTimeSeriesParameters
+ │   ├─ InfrastructureSystems.ForecastParameters
+ │   └─ InfrastructureSystems.StaticTimeSeriesParameters
+ ├─ InfrastructureSystems.ComponentUUIDs
+ ├─ InfrastructureSystems.DeviceParameter
+ │   ├─ DynamicComponent
+ │   │   ├─ PowerSystems.DynamicGeneratorComponent
+ │   │   │   ├─ AVR
+ │   │   │   │   ├─ AVRFixed
+ │   │   │   │   ├─ AVRSimple
+ │   │   │   │   ├─ AVRTypeI
+ │   │   │   │   ├─ AVRTypeII
+ │   │   │   │   ├─ ESAC1A
+ │   │   │   │   ├─ ESAC6A
+ │   │   │   │   ├─ ESAC8B
+ │   │   │   │   ├─ ESDC1A
+ │   │   │   │   ├─ ESDC2A
+ │   │   │   │   ├─ ESST1A
+ │   │   │   │   ├─ ESST4B
+ │   │   │   │   ├─ EXAC1
+ │   │   │   │   ├─ EXAC1A
+ │   │   │   │   ├─ EXAC2
+ │   │   │   │   ├─ EXPIC1
+ │   │   │   │   ├─ IEEET1
+ │   │   │   │   ├─ PowerSystems.EX4VSA
+ │   │   │   │   ├─ PowerSystems.EXST1
+ │   │   │   │   ├─ SCRX
+ │   │   │   │   ├─ SEXS
+ │   │   │   │   └─ ST6B
+ │   │   │   ├─ Machine
+ │   │   │   │   ├─ AndersonFouadMachine
+ │   │   │   │   ├─ BaseMachine
+ │   │   │   │   ├─ FullMachine
+ │   │   │   │   ├─ MarconatoMachine
+ │   │   │   │   ├─ OneDOneQMachine
+ │   │   │   │   ├─ RoundRotorExponential
+ │   │   │   │   ├─ RoundRotorMachine
+ │   │   │   │   ├─ RoundRotorQuadratic
+ │   │   │   │   ├─ SalientPoleExponential
+ │   │   │   │   ├─ SalientPoleMachine
+ │   │   │   │   ├─ SalientPoleQuadratic
+ │   │   │   │   ├─ SauerPaiMachine
+ │   │   │   │   ├─ SimpleAFMachine
+ │   │   │   │   ├─ SimpleFullMachine
+ │   │   │   │   └─ SimpleMarconatoMachine
+ │   │   │   ├─ PSS
+ │   │   │   │   ├─ IEEEST
+ │   │   │   │   ├─ PSS2A
+ │   │   │   │   ├─ PSS2B
+ │   │   │   │   ├─ PSS2C
+ │   │   │   │   ├─ PSSFixed
+ │   │   │   │   ├─ PSSSimple
+ │   │   │   │   └─ STAB1
+ │   │   │   ├─ Shaft
+ │   │   │   │   ├─ FiveMassShaft
+ │   │   │   │   └─ SingleMass
+ │   │   │   └─ TurbineGov
+ │   │   │       ├─ DEGOV
+ │   │   │       ├─ DEGOV1
+ │   │   │       ├─ GasTG
+ │   │   │       ├─ GeneralGovModel
+ │   │   │       ├─ HydroTurbineGov
+ │   │   │       ├─ IEEETurbineGov1
+ │   │   │       ├─ PIDGOV
+ │   │   │       ├─ SteamTurbineGov1
+ │   │   │       ├─ TGFixed
+ │   │   │       ├─ TGTypeI
+ │   │   │       ├─ TGTypeII
+ │   │   │       └─ WPIDHY
+ │   │   ├─ PowerSystems.DynamicInverterComponent
+ │   │   │   ├─ Converter
+ │   │   │   │   ├─ AverageConverter
+ │   │   │   │   ├─ RenewableEnergyConverterTypeA
+ │   │   │   │   └─ RenewableEnergyVoltageConverterTypeA
+ │   │   │   ├─ DCSource
+ │   │   │   │   ├─ FixedDCSource
+ │   │   │   │   └─ ZeroOrderBESS
+ │   │   │   ├─ Filter
+ │   │   │   │   ├─ LCFilter
+ │   │   │   │   ├─ LCLFilter
+ │   │   │   │   └─ RLFilter
+ │   │   │   ├─ FrequencyEstimator
+ │   │   │   │   ├─ FixedFrequency
+ │   │   │   │   ├─ KauraPLL
+ │   │   │   │   └─ ReducedOrderPLL
+ │   │   │   ├─ InnerControl
+ │   │   │   │   ├─ CurrentModeControl
+ │   │   │   │   ├─ RECurrentControlB
+ │   │   │   │   └─ VoltageModeControl
+ │   │   │   ├─ OuterControl
+ │   │   │   └─ PowerSystems.OutputCurrentLimiter
+ │   │   │       ├─ HybridOutputCurrentLimiter
+ │   │   │       ├─ InstantaneousOutputCurrentLimiter
+ │   │   │       ├─ MagnitudeOutputCurrentLimiter
+ │   │   │       ├─ PriorityOutputCurrentLimiter
+ │   │   │       └─ SaturationOutputCurrentLimiter
+ │   │   └─ PowerSystems.InverterComponent
+ │   ├─ OperationalCost
+ │   │   ├─ HydroGenerationCost
+ │   │   ├─ LoadCost
+ │   │   ├─ MarketBidCost
+ │   │   ├─ RenewableGenerationCost
+ │   │   ├─ StorageCost
+ │   │   └─ ThermalGenerationCost
+ │   ├─ PowerSystems.ActivePowerControl
+ │   │   ├─ ActivePowerDroop
+ │   │   ├─ ActivePowerPI
+ │   │   ├─ ActiveRenewableControllerAB
+ │   │   ├─ ActiveVirtualOscillator
+ │   │   └─ VirtualInertia
+ │   └─ PowerSystems.ReactivePowerControl
+ │       ├─ ReactivePowerDroop
+ │       ├─ ReactivePowerPI
+ │       ├─ ReactiveRenewableControllerAB
+ │       └─ ReactiveVirtualOscillator
+ ├─ InfrastructureSystems.InfrastructureSystemsComponent
+ │   ├─ Component
+ │   │   ├─ Device
+ │   │   │   ├─ Branch
+ │   │   │   │   ├─ ACBranch
+ │   │   │   │   │   ├─ DynamicBranch
+ │   │   │   │   │   ├─ Line
+ │   │   │   │   │   ├─ MonitoredLine
+ │   │   │   │   │   ├─ PhaseShiftingTransformer
+ │   │   │   │   │   ├─ TapTransformer
+ │   │   │   │   │   ├─ Transformer2W
+ │   │   │   │   │   ├─ TwoTerminalHVDCLine
+ │   │   │   │   │   └─ TwoTerminalVSCDCLine
+ │   │   │   │   ├─ AreaInterchange
+ │   │   │   │   └─ DCBranch
+ │   │   │   │       └─ TModelHVDCLine
+ │   │   │   ├─ DynamicInjection
+ │   │   │   │   ├─ ActiveConstantPowerLoad
+ │   │   │   │   ├─ AggregateDistributedGenerationA
+ │   │   │   │   ├─ CSVGN1
+ │   │   │   │   ├─ DynamicExponentialLoad
+ │   │   │   │   ├─ DynamicGenerator
+ │   │   │   │   ├─ DynamicInverter
+ │   │   │   │   ├─ GenericDER
+ │   │   │   │   ├─ PeriodicVariableSource
+ │   │   │   │   ├─ SimplifiedSingleCageInductionMachine
+ │   │   │   │   └─ SingleCageInductionMachine
+ │   │   │   └─ StaticInjection
+ │   │   │       ├─ ElectricLoad
+ │   │   │       │   ├─ FixedAdmittance
+ │   │   │       │   ├─ StaticLoad
+ │   │   │       │   │   ├─ ControllableLoad
+ │   │   │       │   │   │   └─ InterruptiblePowerLoad
+ │   │   │       │   │   ├─ ExponentialLoad
+ │   │   │       │   │   ├─ PowerLoad
+ │   │   │       │   │   └─ StandardLoad
+ │   │   │       │   └─ SwitchedAdmittance
+ │   │   │       ├─ Generator
+ │   │   │       │   ├─ HydroGen
+ │   │   │       │   │   ├─ HydroDispatch
+ │   │   │       │   │   ├─ HydroEnergyReservoir
+ │   │   │       │   │   └─ HydroPumpedStorage
+ │   │   │       │   ├─ RenewableGen
+ │   │   │       │   │   ├─ RenewableDispatch
+ │   │   │       │   │   └─ RenewableNonDispatch
+ │   │   │       │   └─ ThermalGen
+ │   │   │       │       ├─ ThermalMultiStart
+ │   │   │       │       └─ ThermalStandard
+ │   │   │       ├─ InterconnectingConverter
+ │   │   │       ├─ Source
+ │   │   │       ├─ StaticInjectionSubsystem
+ │   │   │       │   └─ HybridSystem
+ │   │   │       └─ Storage
+ │   │   │           └─ EnergyReservoirStorage
+ │   │   ├─ Service
+ │   │   │   ├─ AGC
+ │   │   │   ├─ AbstractReserve
+ │   │   │   │   ├─ Reserve
+ │   │   │   │   │   ├─ ConstantReserve
+ │   │   │   │   │   ├─ ReserveDemandCurve
+ │   │   │   │   │   └─ VariableReserve
+ │   │   │   │   └─ ReserveNonSpinning
+ │   │   │   │       ├─ ConstantReserveNonSpinning
+ │   │   │   │       └─ VariableReserveNonSpinning
+ │   │   │   ├─ ConstantReserveGroup
+ │   │   │   └─ TransmissionInterface
+ │   │   └─ Topology
+ │   │       ├─ AggregationTopology
+ │   │       │   ├─ Area
+ │   │       │   └─ LoadZone
+ │   │       ├─ Arc
+ │   │       └─ Bus
+ │   │           ├─ ACBus
+ │   │           └─ DCBus
+ │   ├─ InfrastructureSystems.AdditionalTestComponent
+ │   ├─ InfrastructureSystems.SimpleTestComponent
+ │   └─ InfrastructureSystems.TestComponent
+ ├─ InfrastructureSystems.InfrastructureSystemsContainer
+ │   ├─ InfrastructureSystems.Components
+ │   └─ InfrastructureSystems.SupplementalAttributeManager
+ ├─ InfrastructureSystems.InfrastructureSystemsInternal
+ ├─ InfrastructureSystems.SharedSystemReferences
+ ├─ InfrastructureSystems.SystemData
+ ├─ InfrastructureSystems.TimeSeriesManager
+ ├─ InfrastructureSystems.TimeSeriesMetadata
+ │   ├─ InfrastructureSystems.ForecastMetadata
+ │   │   ├─ InfrastructureSystems.DeterministicMetadata
+ │   │   ├─ InfrastructureSystems.ProbabilisticMetadata
+ │   │   └─ InfrastructureSystems.ScenariosMetadata
+ │   └─ InfrastructureSystems.StaticTimeSeriesMetadata
+ │       └─ InfrastructureSystems.SingleTimeSeriesMetadata
+ ├─ PowerSystems.SystemMetadata
+ ├─ SupplementalAttribute
+ │   ├─ Contingency
+ │   │   └─ Outage
+ │   │       ├─ GeometricDistributionForcedOutage
+ │   │       ├─ PlannedOutage
+ │   │       └─ TimeSeriesForcedOutage
+ │   ├─ GeographicInfo
+ │   └─ InfrastructureSystems.TestSupplemental
+ ├─ System
+ ├─ TimeSeriesData
+ │   ├─ Forecast
+ │   │   ├─ AbstractDeterministic
+ │   │   │   ├─ Deterministic
+ │   │   │   └─ DeterministicSingleTimeSeries
+ │   │   ├─ Probabilistic
+ │   │   └─ Scenarios
+ │   └─ StaticTimeSeries
+ │       └─ SingleTimeSeries
+ └─ TimeSeriesKey
+     ├─ ForecastKey
+     └─ StaticTimeSeriesKey
diff --git a/previews/PR1171/api/valuecurve_options/index.html b/previews/PR1171/api/valuecurve_options/index.html new file mode 100644 index 0000000000..438c8e18da --- /dev/null +++ b/previews/PR1171/api/valuecurve_options/index.html @@ -0,0 +1,2 @@ + +ValueCurve Options · PowerSystems.jl
Edit on GitHub

ValueCurve Options

Operating cost data typically includes both fixed and variable costs. See the how-to on Adding an Operating Cost for a demonstration of defining an operating cost.

In PowerSystems.jl, the variable portion of the operating cost can be represented as linear, quadratic, or piecewise input-output curves; potentially piecewise marginal heat rates; average heat rates; and more, as best fits the input data. This is done by constructing various subtypes of ValueCurve.

This summary table shows each way to construct a ValueCurve with the user-friendly subtype aliases. The ValueCurves make no assumption about units; the example interpretation given here assumes that the variable cost ValueCurve will be wrapped in a CostCurve with natural units. Note that all four Piecewise options here fundamentally represent the same curve. More information and explanatory plots are provided for each subtype alias in the subheadings below.

DescriptionExampleExample interpretation
Linear input-output curve with zero no-load cost (constant average rate)LinearCurve(5.0)$5/MWh
Linear input-output curve with potentially nonzero no-load cost (constant marginal rate)LinearCurve(5.0, 15.0)$5/MWh + $15/hr
Quadratic input-output curve with potentially nonzero no-load costQuadraticCurve(1.0, 1.0, 18.0)$C(P) = 1 P^2 + 1 P + 18$ where $C$ is $/hr, $P$ is MW
Piecewise linear curve specified by cost values at production pointsPiecewisePointCurve([(1.0, 20.0), (2.0, 24.0), (3.0, 30.0)])$20/hr @ 1 MW, $24/hr @ 2 MW, $30/hr @ 3 MW, linear $/hr interpolation between these points
Piecewise linear curve specified by initial value and marginal rates (slopes) between production pointsPiecewiseIncrementalCurve(20.0, [1.0, 2.0, 3.0], [4.0, 6.0])$20/hr @ 1 MW plus additional $4/MWh from 1 MW to 2 MW plus additional $6/MWh from 2 MW to 3 MW
No-load cost plus piecewise linear curve specified by initial value and marginal rates (slopes) between production pointsPiecewiseIncrementalCurve(18.0, 20.0, [1.0, 2.0, 3.0], [4.0, 6.0])$18/hr no-load cost; $20/hr @ 1 MW plus additional $4/MWh from 1 MW to 2 MW plus additional $6/MWh from 2 MW to 3 MW
Piecewise linear curve specified by initial value and average rates between production pointsPiecewiseAverageCurve(20.0, [1.0, 2.0, 3.0], [12.0, 10.0])$20/hr @ 1 MW, $12/MWh @ 2 MW, $10/MWh @ 3 MW, linear $/hr interpolation between these points

LinearCurve

Specify the marginal cost of production $M$ and optionally the no-load cost $C$, which defaults to zero. Here is a graphical representation:

QuadraticCurve

Specify the quadratic ($Q$), proportional ($M$), and constant ($C$) terms of a function that defines the input-output curve:

PiecewisePointCurve

Specify a vector of $K$ (production, cost) pairs (i.e., $(P_k, C_k)$ for $k = 1, \dots, K$) to define the input-output curve:

PiecewiseIncrementalCurve

Specify the cost $C_1$ at the least production point given (NOT the cost at zero production), a vector of $K$ production points $P_1, \dots, P_k$, and a vector of $K-1$ marginal rates $M_1, \dots, M_{k-1}$, that represent the slopes of the curve segments between the points. $C_1$ may be nothing, which results in a not-fully-defined curve. The no-load cost $C_0$ can optionally be specified as a first argument; it is not part of the representation of the curve, just another piece of data that may be stored:

PiecewiseAverageCurve

Specify the cost $C_1$ at the least production point given (NOT the cost at zero production), a vector of $K$ production points $P_1, \dots, P_k$, and a vector of $K-1$ average rates $R_1, \dots, R_{k-1}$ at the $K-1$ latter production points:

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