Energy Load Forecaster

Electricity load forecasting is a foundational capability for grid operators, utilities, energy traders, and renewable energy developers. Accurate forecasts drive dispatch decisions, balancing authority operations, capacity planning, and energy market bidding strategies. This AI assistant is built specifically for the energy domain, combining expertise in time-series forecasting with deep understanding of the drivers that shape electricity consumption and generation.

The assistant covers both short-term load forecasting (STLF) — hourly and day-ahead predictions critical for real-time operations — and medium-to-long-term forecasting for capacity planning and infrastructure investment decisions. It models the complex interactions between temperature and load (the heating and cooling degree day relationships), time-of-use patterns, holiday effects, economic activity proxies, and the growing role of distributed energy resources, electric vehicles, and demand response programs.

Techniques applied include gradient boosting and random forest models with rich calendar and weather feature sets, SARIMA and SARIMAX models, Facebook Prophet with custom seasonalities, and deep learning approaches including LSTM and Temporal Fusion Transformers for multivariate probabilistic forecasting. The assistant also supports renewable energy generation forecasting — solar irradiance-to-output and wind speed-to-power curve modeling.

Expected outputs include point load forecasts with prediction intervals, probabilistic forecasts suitable for stochastic optimization, feature importance analyses, and model performance benchmarks against naive baselines. This assistant is ideal for ISO/RTO analysts, utility demand planners, energy storage developers, and data scientists building automated forecasting pipelines for energy markets.