Merged master into branch

README.md

@@ -12,29 +12,50 @@ This tool was developed as part of a PhD, "Modelling and Design of Local Energy
 1. Install [Python 3.10](https://www.python.org/downloads/) and [Git](https://git-scm.com/).
 
 2. Clone this git repo onto your machine:
-```
-git clone git@github.com:andrewlyden/PyLESA.git
-```
+    ```
+    git clone git@github.com:andrewlyden/PyLESA.git
+    ```
 
-3. Install the `PyLESA` python virtual environment:
-```
-python3.10 -m venv venv
-source venv/bin/activate
-python -m pip install --upgrade pip
-python -m pip install -r requirements.txt
-```
+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
+    ```
+
+    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
+    ```
 
 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.
 
 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.
 
 6. Using a terminal (e.g. PowerShell) within the clone of the `PyLESA` git repo, run:
 
+    If using Linux:
+
     ```python
     source venv/bin/activate
     python -m pylesa --help # to display help messages
     python -m pylesa ./inputs/{name of Excel input file}.xlsx my/existing/output/directory --overwrite
     ```
+
+    If using Windows and Powershell:
+
+    ```python
+    .\venv\Scripts\activate.ps1
+    python -m pylesa --help # to display help messages
+    python -m pylesa ./inputs/{name of Excel input file}.xlsx my/existing/output/directory --overwrite
+    ```
+
     Running `python -m pylesa --help` will display the following help message:
     ![pylesa usage](./img/pylesa_usage.png)
 
@@ -45,38 +66,31 @@ python -m pip install -r requirements.txt
 7. After the run is complete, open the outpus folder in your chosen run directory to view the KPI 3D plots and/or operational graphs, as well as .csv outputs (note that an error will be raised if only one simulation combination is run, as 3D plots cannot be processed). There are also raw outputs.pkl files for each simulation combination which contains a vast range of raw outputs.
 
     Information about the run is written to a `pylesa.log` file located in the output folder. This
-    file contains details of run progress and any warning or error messages that may have occurred. E.g.:
-
-    ```python
-    2024-06-10 09:13:35,749: INFO: Reading MS Excel file: performance_test.xlsx
-    2024-06-10 09:13:41,651: INFO: Completed reading MS Excel file: performance_test.xlsx
-    2024-06-10 09:13:41,693: INFO: Input complete. Time taken: 6 seconds
-    2024-06-10 09:13:41,693: INFO: Running 4 combinations of heat pump power / storage size
-    2024-06-10 09:13:55,635: INFO: Ran fixed order controller: hp_1000_ts_500000. Time taken: 14 seconds
-    2024-06-10 09:14:01,983: INFO: Written output files for: hp_1000_ts_500000. Time taken: 6 seconds
-    2024-06-10 09:14:09,506: INFO: Ran fixed order controller: hp_1000_ts_1000000. Time taken: 14 seconds
-    2024-06-10 09:14:16,391: INFO: Written output files for: hp_1000_ts_1000000. Time taken: 7 seconds
-    2024-06-10 09:14:24,403: INFO: Ran fixed order controller: hp_2000_ts_500000. Time taken: 15 seconds
-    2024-06-10 09:14:31,716: INFO: Written output files for: hp_2000_ts_500000. Time taken: 7 seconds
-    2024-06-10 09:14:39,682: INFO: Ran fixed order controller: hp_2000_ts_1000000. Time taken: 15 seconds
-    2024-06-10 09:14:45,924: INFO: Written output files for: hp_2000_ts_1000000. Time taken: 6 seconds
-    2024-06-10 09:14:48,969: INFO: Wrote KPIs. Time taken: 3 seconds
-    2024-06-10 09:14:48,969: INFO: Simulations and outputs complete. Time taken: 1.12 minutes
-    2024-06-10 09:14:48,969: INFO: Run complete. Time taken: 1.22 minutes
-    ```
+    file contains details of run progress and any warning or error messages that may have occurred.
 
 A video discussing how to run `PyLESA` is available here: https://youtu.be/QsJut9ftCT4
 
 ## Testing
 The `PyLESA` source code is tested using [pytest](https://docs.pytest.org/en/8.2.x/). The tests can be run locally by running the following command:
 
+If using Linux:
+
 ```python
 source venv/bin/activate
 python -m pytest -svv
 # for test coverage reporting run:
 python -m pytest --cov=pylesa -svv --cov-report term-missing
 ```
 
+If using Windows and Powershell:
+
+```python
+.\venv\Scripts\activate.ps1
+python -m pytest -svv
+# for test coverage reporting run:
+python -m pytest --cov=pylesa -svv --cov-report term-missing
+```
+
 ## References
 
 PhD Thesis - Modelling and design of local energy systems incorporating heat pumps, thermal storage, future tariffs, and model predictive control (https://doi.org/10.48730/8nz5-xb46)