【摘要】 随着分布式能源渗透率的逐步提高，虚拟电厂成为解决可再生能源规模化发展难题的关键技术。为减轻风能和光伏发电的波动性对虚拟电厂稳定运行的影响，构建了计及风光不确定性和并网波动性的虚拟电厂多目标优化模型。首先，将风电机组、光伏机组、储能装置、燃气轮机和需求响应等集成虚拟电厂，采用一种拉丁超立方抽样与曼哈顿概率距离削减相结合的场景法对风光出力不确定性进行建模。然后，以虚拟电厂运行成本最小、并网波动性最小和用户满意度最大为优化目标，建立虚拟电厂优化调度模型。最后通过算例分析验证所提模型能够实现虚拟电厂综合效益最优。研究结果为虚拟电厂制定兼顾自身和用户利益的日前调度计划提供参考。更多还原

【Abstract】 With the gradual increase in the penetration rate of distributed energy, the virtual power plant has become a key technology to solve the problem of large-scale development of renewable energy. To mitigate the impact of wind and photovoltaic power generation volatility on the stable operation of virtual power plants, a multi-objective optimization model for virtual power plants was constructed, taking into account wind and solar uncertainty and grid connection volatility. Firstly, wind turbines, photovoltaic units, energy storage devices, gas turbines, and demand response were integrated into a virtual power plant, and a scenario method combining Latin Hypercube Sampling and Manhattan probability distance reduction were used to model the uncertainty of wind and solar power output. Then, with the optimization objectives of minimizing the operating cost, minimizing grid fluctuation, and maximizing user satisfaction of the virtual power plant, a virtual power plant optimization scheduling model was established. Finally, the proposed model was verified through case analysis to achieve the optimal comprehensive benefits of virtual power plants. According to the research results, it provides a reference for virtual power plants to formulate a day ahead scheduling plan that takes into account their own and user interests.更多还原