为了加快内点法求解电力系统最优潮流OPF(optimal power flow)问题的计算速度,通过在有载调压变压器LTC(load tap changing transformer)支路模型中增加虚拟节点,其支路功率方程由该节点的电压来表达,使其不含有变压器变比这个变量,由...为了加快内点法求解电力系统最优潮流OPF(optimal power flow)问题的计算速度,通过在有载调压变压器LTC(load tap changing transformer)支路模型中增加虚拟节点,其支路功率方程由该节点的电压来表达,使其不含有变压器变比这个变量,由此在直角坐标系中建立了电力系统最优潮流问题的二阶新模型。该模型的海森矩阵在优化过程中是恒常矩阵,只需要计算1次,缩短了内点法的计算总时间。利用列近似最小度法COLAMD(column approximate minimum degree)对内点法牛顿方程的系数矩阵进行节点优化排序,以减少三角分解注入元的产生,从而进一步减少优化时间。通过对IEEE14到IEEE300的5个测试系统进行了仿真计算,结果验证了所建模型与方法的正确性与有效性。展开更多
A hybrid learning method combining immune algorithm and least square method is proposed to design the radial basis function(RBF) networks. The immune algorithm based on information entropy is used to determine the str...A hybrid learning method combining immune algorithm and least square method is proposed to design the radial basis function(RBF) networks. The immune algorithm based on information entropy is used to determine the structure and parameters of RBF nonlinear hidden layer, and weights of RBF linear output layer are computed with least square method. By introducing the diversity control and immune memory mechanism, the algorithm improves the efficiency and overcomes the immature problem in genetic algorithm. Computer simulations demonstrate that the RBF networks designed in this method have fast convergence speed with good performances.展开更多
文摘为了加快内点法求解电力系统最优潮流OPF(optimal power flow)问题的计算速度,通过在有载调压变压器LTC(load tap changing transformer)支路模型中增加虚拟节点,其支路功率方程由该节点的电压来表达,使其不含有变压器变比这个变量,由此在直角坐标系中建立了电力系统最优潮流问题的二阶新模型。该模型的海森矩阵在优化过程中是恒常矩阵,只需要计算1次,缩短了内点法的计算总时间。利用列近似最小度法COLAMD(column approximate minimum degree)对内点法牛顿方程的系数矩阵进行节点优化排序,以减少三角分解注入元的产生,从而进一步减少优化时间。通过对IEEE14到IEEE300的5个测试系统进行了仿真计算,结果验证了所建模型与方法的正确性与有效性。
文摘A hybrid learning method combining immune algorithm and least square method is proposed to design the radial basis function(RBF) networks. The immune algorithm based on information entropy is used to determine the structure and parameters of RBF nonlinear hidden layer, and weights of RBF linear output layer are computed with least square method. By introducing the diversity control and immune memory mechanism, the algorithm improves the efficiency and overcomes the immature problem in genetic algorithm. Computer simulations demonstrate that the RBF networks designed in this method have fast convergence speed with good performances.
