基于改进减法平均优化算法的虚拟电厂系统优化调度策略研究

Research on the Optimal Scheduling Strategy of Virtual Power Plant Systems Based on an Improved Subtractive-Average-Based Optimizer

中文关键词:虚拟电厂  氢储能  主从博弈模型  改进减法平均优化算法  多市场交易

keywords:virtual power plants  hydrogen energy storage  master-slave game model  improved subtractive-average-based optimizer  multi-market trading

中文摘要:针对动态电价下含氢储能的虚拟电厂（virtual power plant，VPP）多市场协同优化问题，提出了一种主从博弈模型及融合黄金正弦的减法平均优化算法（golden sine with subtraction average based optimizer，GSABO）。上层以运营商净收益最大为目标制定多市场竞标策略，下层通过协调风光-氢储-灵活负荷实现成本最小化。GSABO算法融合黄金正弦策略，有效提升了全局寻优能力。基于某区域电网数据的仿真结果表明，相较于传统算法，该策略可降低运营成本18.7%，平抑峰谷差率24.3%，为VPP参与电-氢-辅助服务市场提供了新思路。

Abstract:To address the multi-market coordinated optimization problem of virtual power plant（VPP） with hydrogen energy storage under dynamic electricity prices，a Stackelberg leader-follower game model and a golden sine with subtraction-average-based optimizer （GSABO） are proposed. The upper layer formulates multi-market bidding strategies with the goal of maximizing the operator's net profit，while the lower layer minimizes costs by coordinating wind-solar generation，hydrogen energy storage，and flexible loads. The GSABO algorithm integrates the golden sine strategy，which effectively enhances the global optimization capability. Simulations based on regional power grid data show that compared with traditional algorithms，the proposed strategy can reduce operating costs by 18.7% and reduce the peak-valley difference rate by 24.3%，providing a new approach for VPP to participate in the electricity-hydrogen-ancillary service market.