Merge branch 'main' of https://github.com/ebalogun01/EV-EcoSim

README.md

@@ -179,12 +179,12 @@ from the simulation.
 ## How to run
 
 For quick-run, it is recommended to use MacOS or Linux. All Native Windows from windows 11 come with WSL2. Older windows 
-users can install WSL2. See [here](https://docs.microsoft.com/en-us/windows/wsl/install-win10) for more details.
+users can install WSL2. See [here](https://docs.microsoft.com/en-us/windows/wsl/install-win10) for more details. Read [requirements](#requirements) for how to setup the environment and skip to item #3.
 
 1. If you do not have conda installed and want to use conda, please follow the instructions [here](https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html) to install conda.
 
 2. Create a new environment using `conda env create --name <your env name> -f environment.yml`OR 
-install packages listed in the environment manually. You can also use the `requirements.txt` file and [pip](https://packaging.python.org/en/latest/guides/installing-using-pip-and-virtual-environments/) to install the required packages Some users may find pip to be more convenient.
+install packages listed in the environment manually. You can also use the `requirements.txt` file and [pip](https://packaging.python.org/en/latest/guides/installing-using-pip-and-virtual-environments/) to install the required packages using the command `pip install -r requirements.txt`.
 
 3. Ensure gridlabd is installed by following recommended installation method if using the online (MPC) power system co-simulation functionality.
 
@@ -211,10 +211,13 @@ install packages listed in the environment manually. You can also use the `requi
       * Now navigate one level of out `/feeder_population` and run scenarios.py using `python3 scenarios.py` or `gridlabd python scenarios.py` (recommended).
 
 6. For base case (Requires GridLAB-D install):
-   * Navigate to `./test_cases/base_case/feeder_population` and run `feeder_population.py`. This uses the 
-     `./test_cases/base_case/feeder_population/config.txt` settings to prepare the power system and populate the secondary distribution network \
-     with time-varying base loads
-   * Navigate back one directory to `./test_cases/base_case` and run master_sim.py using `python3 master_sim.py`
+   * **If using Unix based system or Windows Subsystem for Linux (WSL) [RECOMMENDED]**: Make sure you are in the project root directory and run `python3 evecosim.py --mode base-case-grid` or `python3 evecosim.py --mode=base-case-grid`. The base-case simulation without any EV Charging nor Distrbuted Energy Resources will run. Results will be in the `test_cases/base_case` folder.
+
+   * **If using Native Windows**
+      * Navigate to `./test_cases/base_case/feeder_population` and run `feeder_population.py`. This uses the 
+        `./test_cases/base_case/feeder_population/config.txt` settings to prepare the power system and populate the secondary distribution network \
+        with time-varying base loads
+      * Navigate back one directory to `./test_cases/base_case` and run master_sim.py using `python3 master_sim.py`
 
 ## Post-simulation analysis
  * This is done with the modules in the `analysis` folder. Please see the `analysis` folder section  for more details.