Solarcast-ML: Per Node GraphCast Extension for Solar Energy Production

TL;DR

This paper extends the GraphCast weather forecasting model to predict solar energy production by integrating a neural network that estimates solar radiation based on weather forecasts, aiding renewable energy planning.

Contribution

The work introduces a novel extension of GraphCast for solar energy forecasting, combining weather predictions with a neural network to estimate solar radiation.

Findings

Accurately predicts solar radiation patterns.

Demonstrates effective convergence and low training loss.

Provides insights for renewable energy planning.

Abstract

This project presents an extension to the GraphCast model, a state-of-the-art graph neural network (GNN) for global weather forecasting, by integrating solar energy production forecasting capabilities. The proposed approach leverages the weather forecasts generated by GraphCast and trains a neural network model to predict the ratio of actual solar output to potential solar output based on various weather conditions. The model architecture consists of an input layer corresponding to weather features (temperature, humidity, dew point, wind speed, rain, barometric pressure, and altitude), two hidden layers with ReLU activations, and an output layer predicting solar radiation. The model is trained using a mean absolute error loss function and Adam optimizer. The results demonstrate the model's effectiveness in accurately predicting solar radiation, with its convergence behavior, decreasing training loss, and accurate prediction of solar radiation patterns suggesting successful learning of the underlying relationships between weather conditions and solar radiation. The integration of solar energy production forecasting with GraphCast offers valuable insights for the renewable energy sector, enabling better planning and decision-making based on expected solar energy production. Future work could explore further model refinements, incorporation of additional weather variables, and extension to other renewable energy sources.