A software platform designed to optimize energy flow and increase efficiency within microgrids. Microgrids are self-contained power networks that operate independently, often with distributed energy resources (DERs) like solar, wind, and energy storage. One could use ML to:
1. Predict energy demand and renewable generation: Integrating forecasts for weather, consumption patterns, and building data.
2. Optimize DER coordination: Create energy schedules for batteries, solar, controllable loads, and grid interactions to reduce costs and peak demand.
3. Adapt to real-time conditions: The AI reacts to unforeseen disruptions and grid constraints.
4. Enable peer-to-peer (P2P) energy trading: Provide users flexibility and create secondary markets for locally produced energy.
This caters to a growing European market driven by rising energy prices, policy support for localized energy, and a desire for resilience. The platform targets energy cooperatives, housing communities, industrial campuses, and commercial developers seeking autonomous energy management.