Enhancing virtual power plant efficiency: three-stage optimization with energy storage integration

Abstract

This study presents a three-stage scheduling optimization model for Virtual Power Plants (VPPs) that integrates energy storage systems to enhance operational efficiency and economic viability. The model addresses the challenges posed by the increasing integration of distributed renewable energy sources, such as wind and solar power, which often lead to fluctuations in power generation and grid instability. By employing a systematic approach, the model establishes a framework for day-ahead, intraday, and real-time scheduling, considering the response speed and timing of different energy storage devices. It uses comprehensive wind and solar power forecasts to formulate the declared output plan in the Day-Ahead Stage (DAS), adjusts scheduling plans in the Intraday Stage (IS) with pumped storage combined with thermal power plants, and employs the rapid response characteristics of energy storage batteries in the Real-Time Stage (RTS) to smooth deviations in real-time wind and solar scenarios. Simulations verify the model’s rationality and the feasibility of its operational strategy, demonstrating that multi-stage scheduling and the synergistic effect of energy storage effectively reduce deviations between real-time and declared outputs, thereby improving economic benefits.