为解决虚拟电厂参与电力调峰时的资源聚合与投标决策优化问题，提出一种基于资源响应能力及信息间隙决策理论（IGDT）的决策优化模型。考虑响应潜力、波动程度、持续时间和响应速度 4 个维度构建分布式资源聚合指标体系，建立了兼顾期望响应收益最大化与偏差惩罚风险最小化的多目标聚合优化模型，筛选最优资源组合。设计虚拟电厂参与电力调峰的市场交易框架与投标决策机制，引入 IGDT 理论以刻画调峰补偿价格的不确定性，构建风险规避（RA）模型以优化投标策略。仿真结果表明，虚拟电厂聚合多目标优化模型可兼顾经济性和风险性的考量，可以为虚拟电厂聚合商筛选资源提供理论方法，使虚拟电厂偏差惩罚风险降低，基于 IGDT 的投标决策优化模型可帮助规避调峰补偿价格不确定性带来的交易风险，使虚拟电厂获得合理的响应收益。

To address the optimization problem of resource aggregation and bidding decision-making for virtual power plants (VPPs) participating in power peak shaving, a decision optimization model based on resource response capability and information gap decision theory (IGDT) is proposed. Considering four dimensions—response potential,fluctuation degree, duration, and response speed—an aggregation indicator system for distributed resources is constructed. A multi-objective aggregation optimization model is established, balancing the maximization of expected response revenue and the minimization of deviation penalty risk, to screen the optimal resource portfolio. The market transaction framework and bidding decision mechanism for VPPs participating in power peak shaving are designed. The IGDT theory is introduced to characterize the uncertainty of peak shaving compensation prices, and a risk-averse (RA) model is constructed to optimize bidding strategies.The simulation results show that the multi-objective optimization model of virtual power plant aggregation can take into account both economic and risk considerations. It can provide a theoretical method for virtual power plant aggregators to screen resources and reduce the risk of deviation punishment of virtual power plants. The IGDT-based bidding decision optimization model can help avoid the transaction risk caused by the uncertainty of peak compensation price, so that the virtual power plant can obtain reasonable response benefits.