A new decentralized control structure for generation scheduling in a multi-energy virtual power plant considering its interactions with an electric vehicle aggregator and a demand response provider

This paper presents a new hierarchical structure for decentralized decision-making in a Multi-Energy Virtual Power Plant (MEVPP). The proposed framework identifies three main stakeholders: the MEVPP authority, an Electric Vehicles Aggregator (EVA), and a Demand Response Provider (DRP), to clarify their roles in MEVPP generation scheduling. A bi-level optimization model is developed to illustrate the hierarchical relationships among these agents. The MEVPP authority, acting as the leader, manages daily energy generation scheduling for distributed energy resources and sets energy prices. The EVA and DRP agents serve as followers, aiming to optimize their operations based on energy prices and collaborate within the context of home energy capacity management. The EVA determines the optimal charging and discharging schedules for electric vehicles and assigns them to different charging stations via the Vehicle-to-Home (V2H) mechanism. The DRP makes decisions on the consumers’ participation rate in the demand response program and adjusts household energy consumption accordingly. A new Internal System Marginal Pricing (ISMP) scheme is used in the pricing strategy set by the MEVPP authority for energy transactions with the two consuming agents. An iterative algorithm is designed to solve the bi-level model with interconnected followers to find a Stackelberg-Nash equilibrium. To compare the centralized and decentralized control structures, we implement six structural scenarios and analyze their results. The proposed bi-level model addresses existing challenges related to consumer decision-making authority and information privacy. Additionally, it reduces the consumers’ costs up to 30 % and lowers peak energy demand up to 9 %, compared to single-level centralized models.