基于最优中心参数的多中心校正内点最优潮流算法

为加快最优潮流(optimal power flow,OPF)问题的求解,基于最优中心参数(optimal centering parameter,OCP)及改进多中心校正(improved multiple centrality corrections,IMCC)技术,提出一种求解最优潮流(optimal power flow,OPF)问题的新型快速内点算法(OCP-IMCC interior point method,OCP-IMCCIPM)。结合均衡距离–评价函数(equilibrium distance-quality function,ED-QF),给出最优中心参数评价模型,采用线性化技术对模型近似,以降低模型计算量。利用线搜索技术实现近似模型求解以确定最优中心参数,该参数使得所提算法具有更多的优势步和更少的迭代次数。IMCC技术可进一步拉大迭代步(尤其是非优势步)步长,实现算法更快收敛。14—1047节点系统的仿真结果表明,与其他多种内点算法相比,所提OCP-IMCCIPM算法具有更大的迭代步长和更快的收敛速度以及更好的计算效果。

Multiple Centrality Corrections Interior Point Optimal Power Flow Algorithm Based on Optimal Centering Parameter

Aim to improve the efficiency of solving optimal power flow(OPF) problem,a new quickly interior point method(IPM) was presented based on the techniques of optimal centering parameter(OCP) and improved multiple centrality corrections(IMCC).Named as OCP-IMCCIPM,the proposed method integrates equilibrium distance-quality function(ED-QF) to establish a mathematical model for evaluating centering parameter.And the approximate expression of this model,which can be solved with fewer computations than the original one,was proposed using the linearization technique.After solving the approximate model with the line search technique,the OCPs could be obtained for the proposed method to owning more dominant steps and less number of iterations than other IPMs.With using IMCC,iteration step length,especially for no dominant step,could be pulling long to accelerate the convergence of iteration.The simulation results for systems that range in size from 14 to 1047 buses show that the proposed algorithm provides longer iteration step length,better speed and results than many other existing IPMs.