计及风电条件风险价值的负荷恢复双层优化

发布时间：2018-05-16 19:02

本文选题：负荷 + 可再生能源　；参考：《中国电机工程学报》2017年18期

【摘要】：在高风电渗透率电网的负荷恢复过程中,适当时机接入一定比例风电有利于提高负荷恢复效率,但同时会增加发生二次停电的风险。考虑负荷恢复过程风电参与的不确定性,建立同时考虑负荷恢复收益与风险的恢复策略价值量优化模型。利用条件风险价值(conditional value at risk,CVa R)方法对负荷恢复过程中的不确定性因素进行定量计算和风险衡量,从而将具有不确定性风电参与的模型转化为风电出力满足一定置信水平的确定性多目标混合整数非线性规划(multi-objective mixed integer non-linear programming,MMINP)模型。为实现模型简洁、快速求解,通过潮流线性化近似(linear programming of AC,LPAC)以及分层序列法(lexicographic optimization method,LOM)将MMINP转化为双层单目标线性规划(bi-level single-objective linear programming,Bi-SLP)问题,在实际应用中可以通过时步递进的方式反复调用所提方法实现负荷恢复优化。仿真结果表明,所构建的方法能够根据恢复需求通过多阶段决策实现风电在负荷恢复过程中的有计划接入,提高恢复效率。
[Abstract]:In the process of load recovery of high permeability power grid, the appropriate time to connect a certain proportion of wind power is beneficial to improve the efficiency of load recovery, but at the same time it will increase the risk of secondary power outages. Considering the uncertainty of wind power participation in the process of load recovery, an optimal value optimization model of recovery strategy is established, which considers both the return and risk of load recovery. The method of conditional value at riskat CVa Rmethod is used to quantitatively calculate and measure the uncertain factors in the process of load recovery. Thus, the model with uncertain wind power participation is transformed into a deterministic multi-objective mixed integer nonlinear programming model with multi-objective mixed integer nonlinear programming (MMINPP), in which wind power output satisfies a certain confidence level. In order to achieve simple and fast solution of the model, MMINP is transformed into bi-level single-objective linear programming Bi-SLP problem by using power flow linearization approximation linear programming of acid LPAC) and stratified sequence method lexicographic optimization method. In practical application, the proposed method can be repeatedly called to realize load recovery optimization. The simulation results show that the proposed method can realize the planned access of wind power in the process of load recovery according to the recovery demand and improve the recovery efficiency.
【作者单位】：电网智能化调度与控制教育部重点实验室(山东大学);
【基金】：国家重点研发计划项目(2016YFB0900105)~~
【分类号】：TM614;TM732

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