摘要
考虑风电出力不确定性的合闸角最优调整策略制定对促进高风电渗透率系统安全、快速恢复具有重要现实意义。首先,以盒式集合表征风电场出力的不确定性,并结合基于直接优化法的区间潮流算法分析风电出力不确定性对合闸角的影响。然后,以调整常规机组出力和机端电压、恢复部分负荷作为减小合闸角的调控措施,建立以参与出力调整的常规机组尽量少、出力调整量尽可能少以及优先恢复重要负荷为目标的两阶段鲁棒优化模型,保证合闸角调整策略在复杂风电出力环境下的可靠性。为实现模型的高效求解,采用近似线性化潮流方法进行线性化处理,将模型转化成混合整数线性规划模型,并结合二分法和列与约束生成算法迭代求解。算例结果验证所提两阶段鲁棒优化模型和迭代求解方法的有效性和可行性。
The optimal control strategy of standing phase angle(SPA)considering the uncertainty of wind power output is of great practical significance to promote the safe and rapid restoration of high wind power penetration system.Firstly,the uncertainty of wind power output is represented by the cassette set,and the influence of the uncertainty on the SPA is analyzed with the interval power flow algorithm based on the direct optimization method.Then,by adjusting the output and terminal voltage of synchronous generators and restoring some load as the control measures,a two-stage robust optimization model is established to reduce the SPA.The aims of the model are to minimize the number of synchronous generators whose output is adjusted and the adjustment amount of these generators,and prioritize the restoration of important loads in order to ensure the reliability of the SPA.In order to solve the model efficiently,the linear-programming approximation of AC power flow is used to transform the original model into a mixed integer linear programming model,which is solved iteratively by the combination of the dichotomy method and the column-and-constraint generation method.Last,the numerical results verify the effectiveness and feasibility of the proposed model and method.
作者
周光奇
顾雪平
李少岩
柴文化
ZHOU Guangqi;GU Xueping;LI Shaoyan;CHAI Wenhua(School of Electrical&Electronic Engineering,North China Electric Power University,Baoding 071003,Hebei Province,China)
出处
《电网技术》
EI
CSCD
北大核心
2021年第6期2201-2209,共9页
Power System Technology
基金
国家自然科学基金项目(51677071)
河北省自然科学基金项目(E2019502195)
中央高校基本科研业务费专项资金项目(2018MS085)。
关键词
环网并列
风电
区间潮流
合闸角
两阶段鲁棒优化模型
列与约束生成算法
transmission loop paralleling
wind power
interval power flow
standing phase angle
two-stage robust optimization model
column-and-constraint generation method