为加快电力系统优化潮流(optimal power flow,OPF)问题的求解,提出了利用凝聚函数法代理非线性不等式约束的优化潮流算法。鉴于优化潮流的数学模型中包括了大量的非线性不等式约束条件,尤其在计算大规模电力系统优化潮流时,对非线性不...为加快电力系统优化潮流(optimal power flow,OPF)问题的求解,提出了利用凝聚函数法代理非线性不等式约束的优化潮流算法。鉴于优化潮流的数学模型中包括了大量的非线性不等式约束条件,尤其在计算大规模电力系统优化潮流时,对非线性不等式约束条件的处理耗费了大量的计算时间。文中将多个非线性不等式约束用一个凝聚函数代替,极大地减少了大规模电力系统优化潮流计算矩阵的维数,然后利用内点法进行求解。对IEEE大规模测试系统进行仿真,结果表明该混合算法具有收敛速度快、迭代迅速的优点。展开更多
In this paper, first the convergence of the coherent function method is given.Then we discuss the error of solutions for detail. The best and "almost" best error bounds are obtained. Finally we examine some ...In this paper, first the convergence of the coherent function method is given.Then we discuss the error of solutions for detail. The best and "almost" best error bounds are obtained. Finally we examine some numerical examples by using previous theoretical resalts.展开更多
In this paper, we present a homotopy continuation method for a class of large constraints convex programming problems. The first step, the constraints are ap-proximated by a family of smooth aggregate constraints, the...In this paper, we present a homotopy continuation method for a class of large constraints convex programming problems. The first step, the constraints are ap-proximated by a family of smooth aggregate constraints, the second step, we con-struct a homotopy method for globally finding convex programming problems with one constraint.展开更多
文摘为加快电力系统优化潮流(optimal power flow,OPF)问题的求解,提出了利用凝聚函数法代理非线性不等式约束的优化潮流算法。鉴于优化潮流的数学模型中包括了大量的非线性不等式约束条件,尤其在计算大规模电力系统优化潮流时,对非线性不等式约束条件的处理耗费了大量的计算时间。文中将多个非线性不等式约束用一个凝聚函数代替,极大地减少了大规模电力系统优化潮流计算矩阵的维数,然后利用内点法进行求解。对IEEE大规模测试系统进行仿真,结果表明该混合算法具有收敛速度快、迭代迅速的优点。
文摘In this paper, first the convergence of the coherent function method is given.Then we discuss the error of solutions for detail. The best and "almost" best error bounds are obtained. Finally we examine some numerical examples by using previous theoretical resalts.
文摘In this paper, we present a homotopy continuation method for a class of large constraints convex programming problems. The first step, the constraints are ap-proximated by a family of smooth aggregate constraints, the second step, we con-struct a homotopy method for globally finding convex programming problems with one constraint.