Energy Consumption Prediction Agent

This agent preprocesses historical data and trains a SARIMAX time series model with exogenous regressors, including temperature, humidity, renewable energy score, day of the week, and holiday, to predict energy consumption. It works within a multi-agent flow: a Root Agent captures the user’s location, the Weather Forecaster Agent retrieves weather data, and the Renewable Energy Predictor Agent computes renewable energy scores with average temperature and humidity.

This agent then estimates future energy consumption and forecasts demand and supply, and the Forecasting Visualization Agent turns the forecast into a chart that the Root Agent presents to the user. The solution optimizes energy consumption and storage, improving efficiency and sustainability in renewable energy operations. It reports up to 20% more efficient use of generated renewable energy through better storage and load management. Its primary users are businesses and organizations with renewable energy assets.