Event-Triggered Multiagent Optimization for Two-Layered Model of Hybrid Energy System With Price Bidding-Based Demand Response

Due to uncertainty and dynamic characteristics from intermittent energy load demand response (DR), the optimal operation of hybrid system is a great challenge. This article proposes an event-triggered multiagent coordinated optimization strategy with two-layered architecture. First, price-bidding-based DR model proposed different stakeholders, it also deduces bidding price Nash equilibrium theory. Then, four agents are designed control kinds resources: agent 1 mainly analyzes or randomness caused by power, 2 takes charge economic dispatch (DED) within thermal units, 3 manages scheduling storage, 4 undertakes load-shifting consumers. In upper-layer level, all coordinate together ensure stability mechanism, intelligent approach depends on switching ON/OFF power generators curtailing load, consensus algorithm utilized optimize subsystem problem in lower-layer level. Furthermore, simulation results can further verify efficiency method, reveals that be promising way solve problem.