- Purici Marius @markus-17
- Moisei Liviu @MoiseiLiviu
- Gilca Constantina @LadyConstantina
- Babcinetchi Egor @Egor0000
- Covalevschi Andreea @AndreeaCvl
EES is a system that predicts the efficiency of the solar panels in producing energy for the next 7 days. The system uses Machine Learning to forecast the energy production.
- The server is written in Python 3.7
- The real data from the invertor are saved on AWS cloud
- The ML model used is from the facebook's kats library. The installation is not required for a working solution, but may be required for model retraining and forecasting past may 2024.
- Dependent on the subscription at api.weatherapi.com.
- Clone the repository
git clone https://github.com/clubmicrolab/Solar-Sense.git- Run the command to install all python dependencies.
cd pbl-prediction-api
pip install -r requirements.txt- Start the server.
python main.py- Open
http://localhost:8080/and check out our solution.
To visualize the real data and real time statistics from the solar panels, follow the steps below:
- Access the link
http://18.197.198.110:3000/?orgId=1 - Login: guest
- Password: 2023Password_for_guest_user