在“双碳”目标的背景下，电力行业已成为碳减排中的重要组成部分。虚拟电厂(virtual power plant，VPP)通过整合和聚集分布式资源等参与碳市场，可进一步提升整体效益；然而，分布式新能源出力的不确定性给其运营管理带来了许多挑战。为此，在利用基于拉丁超立方抽样的场景生成与场景削减法处理风电、光伏出力不确定性问题的基础上，将多单元聚合并考虑到用户侧需求响应的VPP作为一个整体去参与电能量市场以及碳市场，构建VPP总成本最小的优化调度模型，然后利用改进灰狼优化算法对其进行求解。通过对不同场景算例进行对比分析，可以得出：碳市场及需求响应的存在，加强了风光等清洁能源的消纳，减少了温室气体的排放，也减少了VPP的运行成本，经济性和环保性得到了兼顾。

Against the backdrop of the "dual carbon" target, the power sector has become an important part of carbon reduction. Virtual power plants (VPP) can further improve their overall efficiency by integrating and aggregating distributed resources to participate in the carbon market. However, the uncertainty of distributed new energy output poses many challenges for their operation and management. Therefore, on the basis of using the scenario generation and scenario reduction method based on Latin hypercubic sampling to deal with the uncertainty problem of wind power and photovoltaic output of distributed energy, the VPP, which aggregates multiple units and takes into account the user-side demand response, participates in electric energy market as well as the carbon market as a whole, and the optimal scheduling model with the minimum total cost of the VPP is constructed, which is finally solved by using the improved gray wolf optimization algorithm. Through comparative analysis of different scenarios, it can be concluded that the existence of carbon market and demand response enhances the consumption of clean energy such as wind power and photovoltaic, and reduces greenhouse gas emissions, and reduces the operating cost of the VPPs, and takes into account its economy and environmental protection.