摘要
采用非序贯Monte Carlo仿真法抽取输电系统的故障状态,并采用连接矩阵存储和广度优先搜索技术实现网络拓扑分析,从而高效解决了多重故障识别和孤岛处理问题,并节省了状态抽取的时间。同时建立了最优负荷削减非线性规划模型,用非线性原对偶内点法求解。利用故障状态抽样概率和最优负荷削减量加权的方法对严重故障状态进行筛选和排序,找出系统运行风险和薄弱环节。IEEE-RTS实例的评估结果证明了所提算法的正确性和有效性。
The non-sequential Monte Carlo simulation algorithm is applied to sample failure states of transmission systems,and network topology analysis is realized by means of the storage based on connection matrix and breadth first search techniques so that multiple failures and islanding are identified efficiently and sampling time of failure states is reduced.Also an optimal load shedding non-linear programming model is estabilished which is solved by primal-dual interior point algorithm.Futhermore,the severe failure states are filtered and sorted through weighting the sampling probability of failure states and optimal load shedding quantity to find out operational risks and weaknesses of transmission systems.The correctness and effectiveness of the proposed method have been verified on IEEE-RTS system.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2010年第20期45-50,56,共7页
Power System Protection and Control
基金
国家自然科学基金项目(50777021
50907023)~~
关键词
充裕度评估
蒙特卡罗仿真
最优负荷削减
广度优先搜索
非线性规划
adequacy evaluation
Monte Carlo simulation
optimal load shedding
breadth first search
nonlinear programming
