储能应急车优化调度的模糊机会约束方法

Fuzzy Chance Constrained Method for Optimal Scheduling of Mobile Energy Storage System in Emergency Support of Power Systems

移动储能技术作为一种新型的灵活性资源,其在电力系统的防灾与应急支援等多种场景中发挥了非常重要作用。在此背景下,提出了基于模糊机会约束规划的储能应急车优化调度模型,以最大程度地恢复重要电力用户的供电并减少停电损失。首先,介绍了储能应急车的工作原理,提出了考虑负荷分级和行驶时间不确定性的储能应急车优化调度的模糊机会约束规划模型,该模型以最小化总停电损失为优化目标,实现对一级负荷的持续供电。然后,针对行驶时间的不确定性,采用模糊理论中的模糊参数表示行驶时间,并采用梯形隶属度参数的清晰等价类将含模糊参数的机会约束清晰化,便于对模糊机会约束模型进行求解,最后采用了遗传算法对所提的模型进行求解。算例分析结果表明,所提出的储能应急车优化调度模型较好地处理了电力应急过程中行驶时间的不确定性,实现了储能应急车的优化分配与调度,确保了重要电力用户的供电恢复,有效地降低了停电损失。

Mobile energy storage technology,as a new type of flexible resources,plays an important role in many sce-narios of power systems such as disaster prevention and emergency support.On this background,an optimal schedul-ing method of mobile energy storage systems in emergency based on fuzzy chance constrained is proposed to recoverthe power supply of important customers and minimize outage losses.First of all,the operation principle of the mobileenergy storage systems is introduced and fuzzy chance constrained plan model of the optimal scheduling of the mo-bile energy storage system,which takes into account the load classification and the uncertainty of the travel time ofmobile energy storage systems,is proposed to minimize the total outage losses as optimization target and achieve thecontinuous power supply of the first level load.Then,for the uncertainty of the travel time,the fuzzy parameter in thefuzzy theory is adopted to represent the travel time and the clear equivalent forms of trapezoidal membership parame-ters are used to convert the opportunity constraints with fuzzy parameters into clear ones.Finally,a genetic algorithmis applied to solve the proposed model.It is shown by the result of calculation and analysis that the proposed optimalschedule model of the mobile storage system can deal with the uncertainty of the travel time during the emergency pe-riod,achieve the optimal distribution and scheduling of mobile energy storage systems and then reduce the lossescaused by the blackout.