Research on multi-objective optimization dispatch of typical demand side flexible resource aggregation participating in peak shaving auxiliary services

The renewable energy power generation industry represented by wind power and photovoltaics (PV) is booming in China. Due to the randomness and intermittency of new energy power generation, its large-scale generation has brought major challenges to the safe and economic operation of power systems. Aggregating demand side flexible resource (DSFR) represented by decentralized electric heating, electric vehicles and distributed energy storage to participate in power grid dispatch can reduce the load peak-valley difference, which is an effective way to improve the safe and economic operation of the power system. This study selects decentralized electric heating, electric vehicles, and distributed energy storage as research objects, takes the minimum dispatch compensation cost, the minimum curtailment of wind and PV, and the minimum load variance as optimization objectives combines with various constraints of DSFR participating in the dispatching process, and establishes the multi-objective optimal dispatch model of typical DSFR. The dispatch results of DSFR and the cost-benefit of load aggregators (LAs) and DSFR users in different dispatch scenarios are compared and analyzed through the simulation example. The results show that the proposed model can effectively smooth load fluctuations, achieve peak shifting and valley filling, further promote new energy consumption, and significantly improve the economy of DSFR users and LAs. The research broadens the framework of DSFR participating in power grid operation regulation and provides references for the development of DSFR dispatching.