更新时间：03-20 （Tesla）提供原创文章
摘要：现代社会的发展离不开电力的支持，人们对电力工业的依赖越来越强。即使我国的装机容量与日俱增，仍满足不了人们日益增长的电力需求。同时人们对电能质量的关注度越来越高。电力系统的无功优化作为节能降损和提高电能质量的重要手段之一，受到越来越多的研究人员的重视。本文分析了无功补偿改善电压质量和降低损耗的原理，采用遗传算法确定无功补偿接入点和其补偿容量。本文对一般遗传算法作了一些改进，提高了算法的运算速度和全局寻优能力。
本文利用matlab软件对IEEE33节点系统进行了仿真测试，从优化结果上看，遗传算法能切实解决无功优化问题，有效减少电网有功损耗和提高节点电压质量,具有良好的应用前景。
关键词：无功优化；遗传算法；电压质量；有功网损
ABSTRACT：Electric power, with people’s increasing dependence on electric industry, plays a crucial role in the sustainable development of modern society. Though the installed capacity of power system of China has been enlarging massively during the past decades, it still lags behind the growing demand of this huge society. Simultaneously, individuals are paying closer attention to the electric quality. As an effective technique to improve voltage quality and lessen power loss, reactive power optimization (RPO) is always a hotspot for electric researchers. this paper analyze the function of reactive compensation. We utilize Genetic Algorithm to fix compensation locations and their corresponding compensation capacity. We introduce some methods to improve GA for quicker convergence and better global search ability.
Simulation results, in matlab environment, of IEEE 33-bus system show that GA can solve the RPO problem cogently. GA has a promising prospect of practical application.
KEYWORDS: Reactive Power Optimization; Genetic Algorithm; Voltage Quality; Power Loss