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@@ -16,14 +16,22 @@ This tool was developed as part of a PhD, "Modelling and Design of Local Energy | |
git clone [email protected]:andrewlyden/PyLESA.git | ||
``` | ||
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3. Install the `PyLESA` python virtual environment: | ||
3. Install the `PyLESA` python virtual environment. If using Linux: | ||
``` | ||
python3.10 -m venv venv | ||
source venv/bin/activate | ||
python -m pip install --upgrade pip | ||
python -m pip install -r requirements.txt | ||
``` | ||
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If using Windows and Powershell: | ||
``` | ||
python -m venv venv | ||
.\venv\Scripts\activate.ps1 | ||
python -m pip install --upgrade pip | ||
python -m pip install -r requirements.txt | ||
``` | ||
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4. Define and gather data on the local energy system to be modelled including resources, demands, supply, storage, grid connection, and control strategy. Define the increments and ranges to be modelled within the required parametric design. Input all this data using one of the template Excel Workbooks from the [inputs](./inputs) folder. | ||
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5. Optionally run the demand ([heat_demand.py](./pylesa/demand/heat_demand.py) and [electricity_demand.py](./pylesa/demand/electricity_demand.py)) and resource assessment methods (see PhD thesis for details) to generate hourly profiles depending on available data. Input generated profiles into the Excel Workbook. | ||
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