含电动汽车的虚拟电厂鲁棒随机优化调度

随着电动汽车和分布式电源接入电网的比例不断提升,虚拟电厂为有效解决电动汽车、分布式电源并网提供了新思路。由于可调度充放电的电动汽车数量和分布式电源出力存在明显的不确定性,因此虚拟电厂优化调度时必须考虑这些不确定性。在此背景下,采用场景模拟技术处理风电出力的不确定性,形成经典场景。针对可调度电动汽车数量的随机性与不确定性,利用鲁棒优化方法建立了原模型的对偶模型,构建含电动汽车的虚拟电厂鲁棒随机优化调度模型。算例分析证明了所提模型具有实用性和有效性,在优化调度模型中考虑不确定性的影响,可减小实际日运行成本,提高优化策略的鲁棒性。结果表明鲁棒系数和置信水平影响了日运行成本,通过合理制定燃气轮机等常规机组的发电计划可以减小日运行成本。

Robust Stochastic Optimal Dispatching of Virtual Power Plant Containing Plug-in Electric Vehicles

With unceasing increase of plug-in electric vehicles and distributed generators integrated into power grid, virtual power plant(VPP)provides an idea for solving grid-integration problems of plug-in electric vehicles and distributed generators. The uncertainties containing the number of dispatchable plug-in electric vehicles and the output of distributed generators should be considered in optimal dispatching of VPP. Given this background, the uncertainty of wind output is described by typical scenarios produced by scenario generation and reduction techniques. Considering the uncertain and stochastic nature of dispatchable plug-in electric vehicles, a dual model of the original one is constructed based on robust optimization, and a robust stochastic optimal dispatching model of a VPP including plug-in electric vehicles is proposed. Case study shows the effectiveness and feasibility of the proposed model, and the consideration of uncertainties in optimal dispatching model reduces daily operation cost and improves the robustness of the optimal schemes. The results show that confidence level and robust coefficients have effects on operation costs. Operation costs can be reduced by making rational generation plan of conventional generating units such as gas turbine.