Research on an optimal scheduling strategy for a virtual power plant participating in primary frequency regulation

Abstract

As a new energy system that integrates multiple energy sources， virtual power plants （VPPs） play an increasingly important role in participating in primary frequency regulation of the power grid. In response， this paper proposes an optimal scheduling strategy for the VPP using the improved multi-objective particle swarm optimization （MOPSO） and an integral power assessment method for primary frequency regulation. To effectively evaluate the stability and economy of primary frequency regulation， an economic benefit assessment model is introduced for the VPP， using the integral power assessment method， to penalize power that fails to meet performance criteria. The multi-objective function with minimum grid frequency deviation and maximum overall economic efficiency of the VPP is set. The improved MOPSO is employed to optimize the operational states and frequency correction power of wind energy， solar energy， energy storage， and alkaline water electrolysis （AWE） within the VPP， further reducing frequency deviations and enhancing economic returns. Simulation results analyze the frequency regulation outcomes of the VPP containing wind energy， solar energy， energy storage， and hydrogen energy， as well as output performance of each component， validating the feasibility and effectiveness of the proposed scheduling strategy.

Keywords

• vpp
• primary frequency regulation
• integral power assessment
• multi-objective optimization