System for machine learning, optimizing and managing local multi-asset flexibility of distributed energy storage sources

摘要

Optimize and manage distributed energy storage and flexible resources based on localization and group synthesis, especially around the determination, analysis and predictive learning of local data patterns, optimization of energy supply and behind the meter storage resources, and community, low voltage networks. , Systems, devices and methods for scoring availability for flexibility and risk profiles to inform local clusters of co-located or near resources within a supplier, neighborhood or building. The optimization involves scheduled, responsive and active management of local clusters of data sources and resources for a set of purposes such as price, energy supply, renewable leverage, asset value, constraints or risk management. Or the optimization offsets and assists in local balancing or constraint management of larger local suppliers and loads, or local energy demands and renewable supplies, storage resources, electric heat resources, electric vehicle charging resources or Achieve local goals such as providing resources to assist in active management of flexible loads in buildings, clusters of electric vehicle chargers.