Energy Process Intelligence (EPI) is not a generic AI application for renewable energy. Grounded in Object-Centric Process Mining (OCPM), it focuses on operational processes within and across source–grid–load–storage systems. By linking energy objects, events, constraints, and lifecycles, EPI transforms multi-object operations involving turbines, plants, storage assets, dispatch commands, alarms, work orders, and market transactions into object-centric process representations for discovery, explanation, prediction, and optimization.
Different from adjacent directions
A coherent chain: representation, explanation, optimization
Research Directions
Direction 01
Object-Centric Energy Process Mining
How can business activities, physical operations, information interactions, and decision-control behaviors involving source-grid-load-storage objects be eventized, object-centric, process-aware, and constraint-aware from heterogeneous data?
Object-Centric Process MiningEnergy Event LogsPhysics-Constrained Process ModelsConformance CheckingEnergy Process Digital Twins
Direction 02
Energy Process Explanation and Risk Analysis
How can business deviations, physical anomalies, information mismatches, and decision risks in energy operational processes be jointly discovered, attributed, evaluated, and predictively modeled?
Human-in-the-loop Safe Energy Process Optimization
How can process knowledge be transformed into verifiable, reversible, and executable human-in-the-loop optimization decisions under operational rules, physical constraints, information trustworthiness, and safety boundaries?
Safe Reinforcement LearningProcess-Aware AgentsHuman-in-the-Loop OptimizationTrustworthy Decision-MakingReversible ExecutionVirtual Power PlantsStorage SchedulingSource-Grid-Load-Storage Operations and Coordination