Demand Forecasting for Utilities AI

Accurate, DER-aware, weather-sensitive load forecasts for operations

Load forecasts are crucial for managing electricity generation, procurement strategies, and the overall operation of the power grid. Artificial intelligence leverages weather data, the behavior of distributed energy resources (DERs), socio-economic factors, and historical usage patterns to produce highly accurate short-term and long-term forecasts.

By reducing forecast errors, utilities can enhance operational reliability, optimize procurement decisions, and provide transparent ranges for uncertainty, leading to more efficient grid management.

AMI/SCADA loads, weather, DER telemetry, events/holidays, tariffs, mar

Short-term load forecasting is a key component, utilizing probabilistic forecasts to account for the inherent uncertainty in energy demand. This system also disaggregates Distributed Energy Resources (DERs) – like solar panels and battery storage – and performs scenario modeling alongside anomaly detection capabilities.

Operator dashboards and APIs enable seamless integration with Energy Management Systems (EMS), Advanced Distribution Management Systems (ADMS), and market bidding platforms, while automated alerts notify operators of any demand deviations.

DER-Aware Forecasting

When forecasting electricity demand, it’s essential to account for the unique characteristics of distributed energy resources. This includes considering the impact of photovoltaic (PV) solar generation and battery storage systems, as well as electric vehicle (EV) load and shifting behaviors.

The system can detect abnormal demand patterns that might otherwise be missed, providing a more robust and accurate picture of future energy needs.

Frequently asked questions