计及风光不确定性的虚拟电厂多目标随机调度优化模型

Multi-Objective Stochastic Scheduling Optimization Model for Virtual Power Plant Considering Uncertainty of Wind and Photovoltaic Power

为缓解风电和光伏发电不确定性对虚拟电厂稳定运行的影响,引入鲁棒随机优化理论,建立了计及不确定性和需求响应的虚拟电厂随机调度优化模型。首先,风力发电、光伏发电、燃气轮机发电,以及储能系统和需求响应集成为虚拟电厂,然后最大化虚拟电厂运营收益、最小化系统运行成本和弃能成本被作为目标函数,建立虚拟电厂调度优化模型。再应用鲁棒随机优化理论来转换光伏发电以及风力发电不确定性变量的约束条件,建立了虚拟电厂随机调度模型。最后,选择中国国电云南分布式电源示范工程为实例分析对象。分析结果显示:所提模型能够降低系统运行成本,双重鲁棒系数的引入能够为不同风险态度决策者提供灵活的虚拟电厂调度决策工具,协助应对风电和光伏发电的随机特性。储能系统能够借助自身充放电特性,替代燃气轮机发电机组为风电和光伏发电提供备用服务,促进风电和光伏发电并网。将需求响应纳入虚拟电厂能够实现发电侧与用电侧联动优化目标,平缓化用电负荷曲线,系统整体运营效益达到最佳。

In order to mitigate wind and photovoltaic power generation uncertainty on stable operation of virtual power plant, a muhi- objective stochastic scheduling optimization model with consideration of uncertainty and demand response is proposed with robust stochastic optimization theory. Firstly, wind power, photovoltaic power generation, gas turbine （GT） power generation, energy storage systems （ESS） and demand response are integrated into a virtual power plant. Secondly, maximize operational benefits of virtual power plant and minimize system operating cost and abandoned energy costs are selected as objective functions. Then by application of robust stochastic optimization theory, a virtual power plant （VPP） scheduling optimization model is established. The proposed method is applied to distributed power demonstration project in Yunnan, China as an example. The results show that the proposed model can reduce system power shortage penalty cost. The introduction of dual Robust coefficients can provide flexible VPP scheduling decision tools for different risk attitudes of decision makers and respond to wind power and photovohaic power generation stochastic characteristics effectively. ESS can replace GT unit to provide backup services for wind power and photovohaic power generation because of its charge and discharge characteristics. It can also smooth VPP output power curve and promote grid connection between wind power and photovoltaic power generation. Demand response is incorporate into VPP to realize power generation side and power side linkage optimization, smooth electric load curve and improve overall operational effectiveness.