摘要
为应对负荷恢复过程中源荷双重不确定性问题,提出了基于仿射可调鲁棒优化的配电网负荷恢复调整策略。第1阶段基于净负荷预测场景,建立一个以最大化加权负荷恢复量为目标函数的优化模型,决策最优的负荷恢复量;第2阶段采用仿射策略,利用预算不确定集来描述净负荷的不确定性,构建考虑净负荷误差的负荷恢复调整方案。在求解过程中,对双线性变量进行对偶变换得到可快速求解的线性规划模型。最后,在改进33节点和123节点配电系统进行仿真验证,结果表明:相比于传统的鲁棒优化方法,该方法降低了优化结果的保守性,有助于加快负荷恢复,减小停电损失。
To address the problem of double uncertainties of source and load in the process of load restoration,this paper proposes a load restoration adjustment strategy for distribution network based on affine adjustable robust optimization.First,based on the net load forecasting scenario,an optimization model with the maximum weighted load restoration as the objective function is built,and the optimal load restoration base value is determined.Second,the affine strategy is adopted,and the budget uncertainty set is employed to describe the uncertainty of the net load,and a load restoration adjustment scheme considering the net load error is built.In the solution process,a mixed integer linear programming model with quick resolution is obtained by dual transformation of bilinear variables.Finally,the improved 33-node system is employed for simulation.Our results show compared with the traditional robust optimization method,the proposed method reduces the conservatism of the optimization results and is helpful to accelerate the load restoration and reduce the losses caused by power outages.
作者
徐天奇
孙闯
李琰
李晓兰
崔琳
赵鑫
XU Tianqi;SUN Chuang;LI Yan;LI Xiaolan;CUI Lin;ZHAO Xin(School of Electrical and Information Engineering,Yunnan Minzu University,Kunming 650504,China;Yunnan Key Laboratory of Unmanned Autonomous System,Kunming 650504,China)
出处
《重庆理工大学学报（自然科学）》
CAS
北大核心
2024年第6期274-280,共7页
Journal of Chongqing University of Technology：Natural Science
基金
国家自然科学基金项目(62062068)。
关键词
源荷不确定性
净负荷
配电网
负荷恢复
预算不确定集
仿射可调鲁棒优化
source load uncertainty
net load
distribution network
load restoration
budget uncertainty set
affine adjustable robust optimization
