基于图论的智能配电网故障恢复智能优化方法

• Format: Patent
• Language: Chinese
• Published: 04.05.2018
• Subjects: CALCULATING; CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION ORPROCESSING OF GOODS; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; PHYSICS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS; TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINSTCLIMATE CHANGE

基于图论的智能配电网故障恢复智能优化方法，包括如下步骤：1)输入网络参数：配电网络的原始结构，各条支路的线路参数，各个节点的负荷、DG数据等参数；2)输入当前发生故障的线路编号，将其相应的开关状态量零；3)设置量子离散粒子群算法的维度、迭代次数以及相应的参数值；4)初始化各个粒子的位置值x、量子比特位、旋转角、局部最优向量xp和全局最优向量xg；5)基于图论的粒子位置值修正；6)依次更新量子旋转角引导值、量子旋转角和量子粒子的比特位；7)更新量子粒子的位置值x；8)更新粒子的局部最优向量和全局最优向量；9)收敛性检验；10)输出最优粒子位置值x，得出相应的故障恢复策略。 The invention discloses a graph-theory-based intelligent optimization method for failure recovery of a smart distribution grid. The method comprises the following steps of 1) inputting network parameters including an original structure of a distribution network, line parameters of each branch, load of each node, DG (Distributed Generation) data and other parameters; 2) inputting a number of the current faulty line and zeroing the corresponding switching state thereof; 3) setting dimensionality, iterations and corresponding parameter values of a quantum particle swarm optimization algorithm; 4) initializing a position value xk, a quantum bit, a rotation angle, a local optimal vector xp and a global optimal vector xg of each pa