基于预测-校正内点法的最优潮流算法研究.doc

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  • 更新时间:2014-03-20
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摘要:电力是国民经济的重要基础产业,电力系统的发展关乎千家万户、国计民生。如何优化电力系统运作,提高电力系统运行效率,从而构建资源节约型和环境友好型社会,一直以来都是学者们致力研究和探讨的热点问题。随着全球资源环境压力的不断增大和电力市场化进程的持续深入,电力工业正面临前所未有的机遇和挑战。应用新的管理和技术,建设更加安全、可靠、经济的电力系统, 已经成为各国电力行业的共同目标。最优潮流作为电力系统不可或缺的分析和定价工具,在当前的电力市场环境中扮演着越来越重要的角色。而在众多的求解最优潮流的方法中,内点法正受到越来越多的关注。内点法的最大特点是收敛速度快且对等式和不等式约束的处理十分方便,这也使其成为求解大型优化问题的实用方法之一。

   本文通过对原-对偶内点法的研究,对高阶内点法中的预测-校正内点法进行了详细分析,通过与原对偶内点算法的比较,证实了预测-校正内点法的收敛性优于原对偶内点算法。

关键词:电力系统,最优潮流,原-对偶内点法,预测-校正内点法

 

Abstract:Electric power industry is an important basic industry of national economy and its development is closely related to the national economy and the people's living. Scholars have been dedicated to improving and optimizing the operating efficiency of power system so as to build a resource thrift and environment friendly society. As the increase of pressure on resources and environment and the development of power marketing course, power industry is facing the unprecedented opportunity and the challenge. To build a secure, reliable and economic power system, application of new management method and technology is the goal of power industry all around the world. Optimal power flow (OPF), as an indispensable analysis and pricing tool, is now playing more and more role in the current electricity markets environment. Among most optimization methods for OPF, interior point methods (IPMs) have enjoyed increasing popularity. The most attractive features of IPM are its speed of convergence and its robust capability of handling equality and inequality constraints; making itself a practical tool for solving large-scale optimization problems.

   Based on the research of primal-dual interior point methods and PC-IPM and through dual interior point algorithm comparison,PC-IPM within a point of the convergence than the primal-dual interior point methods was confirmed.

Key Words: power system, optimal power flow, primal-dual interior point method predictor-corrector interior point method


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