Proposal of Hierarchical EMS with Robust Distributed Coordinated Control and Constrained Real-Time Control and its Performance Evaluation for Balancing Market Response

Distributed energy resources (DERs) have attracted attention in recent years as new regulating power sources for wholesale and balancing market. To maximize the market value of these DERs, group control performance of DERs that combines responsiveness and economic efficiency is required. As a group control method for DERs, distributed coordinated control enables total energy optimization by small-scale edge computers as consumer side energy management systems (EMSs). However, it has limitations in terms of real-time control achieving high-speed response performance for market requirement. In this study, a hierarchical EMS method with the combination of forecasting function, robust operation planning function with distributed coordinated optimization and constrained real-time control function is proposed. The robust operation planning function learns the optimal trade-off point between robustness against forecasting errors and cost increase from historical data. In the real-time control functions, model predictive control with constrained conditions is applied, which minimizes the end point imbalance of operation planning interval (30minutes). As a use case, demonstrated a good control performance in the balancing market and clarified the trade-off relationship between the robustness for uncertainty and operation cost.