matlab_loadflow_newton-raphson

This is a newton-raphson powerflow solution which I wrote in MATLAB for a Power Systems Analysis course at University of Washington. The algorithm is not super sophisticated. It can handle three bus-types:

• Slack - voltage magnitude and angle specified
• PQ - real and reactive power specified
• PV - real power and voltage magnitude specified

Test Systems

There are two test systems preprogrammed. To run both of them, use the command

runall

Viewing the contents of the runall.m file will show the order to call functions in.

Data Inputs

Inputs are expected in two matrixes. Examples are availabe in the two test system files tsa.m and tsb.m. Branch Data Columns:

• From Bus Number
• To Bus Number
• Branch Resistance
• Branch Reactance
• Branch Shunt Resistance (not sure I have terminology correct on this one)
• Branch Shunt Capacitance (not sure I have terminology correct on this one)

Bus Data Columns:

• Bus Number
• Type: 1 = slack, 2 = PQ, 3 = PV
• Bus Generated Real Power: 0 if unknown
• Bus Generated Reactive Power: 0 if unknown
• Bus Real Power Load: 0 if unknown
• Bus Reactive Power Load: 0 if unknown
• Bus Volage Magnitude: set to start value if unknown (1.0 for flat start)
• Bus Voltage Angle in radians: set to start value if unknown (0.0 for flat start)
• Bus Conductance (G of the admittance Y=G+jB)
• Bus Susceptance (B of the admittance Y=G+jB)

Running NRPF

Once the bus and branch data are read in, the main Newton-Raphson Power Flow (NRPF) function can be called. It has several optional inputs shown in all caps:

[results]=nrpf(busdata,branchdata,PRINT_ITERS,THRESH,ITER_MAX,FREEZE_JAC)
[results]=nrpf(busdata,branchdata,PRINT_ITERS,THRESH,ITER_MAX)
[results]=nrpf(busdata,branchdata,PRINT_ITERS,THRESH)
[results]=nrpf(busdata,branchdata,PRINT_ITERS)
[results]=nrpf(busdata,branchdata)

• PRINT_ITERS will print all iteration data if set to 1, defaults to 0
• THRESH is the power mismatch threshold, defaults to 0.001
• ITER_MAX is the maximum number of iterations, defaults to 10
• FREEZE_JAC only calculates the jacobian the first time around. This was to answer a specific question in the final project really.

Interpreting Results

The results returned from the nrpf function is a MATLAB containers.Map object. It contains the following keyed data:

• ybus - ybus matrix
• pmatrix - if PRINT_ITERS is set to 1, this contains the matrix that is printed for the last iteration
• iter_ - a nested map containing data for each iteration where the _ is the number of the iteration
  • jacobian - the jacobian for that iteration
  • Pmm - the real power mismatch for that iteration
  • Qmm - the reactive power mismatch for that iteration
  • V - the new voltage magnitude for that iteration
  • T - the new voltage angle (in radians) for that iteration

Sample Data Run

Get data from Test System A and run powerflow on it.

[busdata,branchdata]=tsa(); 
[results]=nrpf(busdata,branchdata);

Display the ybus matrix:

results('ybus')

Display the jacobian from the second iteration:

iter2=results('iter2');
iter2('jacobian')

Print all results data to the console:

print_nrpf(results);

Regression Test

A regression test along with data for the test allows verifying that changes to the algorithm do not break it.

nrpf_test();

A successful run will print:

Regression test passed!