摘 要
配电网无功补偿优化问题已经成为影响电网系统稳定运行的重要环节之一，针对配电网无功补偿的算法和方式的研究层出不穷，在未来面对智能化电网的基本条件下，如何实现配电网无功补偿优化的自动化与智能化控制是至关重要的，特别是针对配电网无功补偿设备的一系列控制方式，是实现智能化的基础。
本文以配电网无功补偿的基本理论为基础，对配电网无功补偿的潮流计算、遗传算法以及配电网无功补偿管理系统进行了研究。首先文中对潮流计算的各种算法展开探讨，指出潮流计算的速度和收敛程度在很大程度上会影响无功补偿优化的最终效果，并以改进的牛顿法、前推回代法以及回路法进行了分析；然后对传统的遗传算法进行分析，并结合配电网多变量的特点，对传统遗传算法进行了改进，改进的主要内容包括有采取十进制编码的方式、建立适应度函数、采取自适应的方式确定交叉概率和变异概率、对交叉与变异操作实现改进，最终确定了改进遗传算法在配电网无功补偿中的应用流程；最后提出了配电网无功补偿管理系统的总体结构，认为采取多机控制的三级结构模式较为合理，能够满足当前智能化电网发展的基本需求，能够较好地解决传统SCADA控制系统的局限性，并取得了直观、高效及扩展性强的功效，之后将该系统与秦皇岛青龙地区的无功补偿运行实践结合，给出了主要的操作实现功能。
从整个研究过程来看，改进的遗传算法更能够有效地实现对配电网无功补偿效率的提升，同时以此为基础的配电网无功补偿管理系统的设计，实现了降低电网损耗，提升电网运行稳定性的目标，基本上满足了当前配电网无功补偿优化的实际需求。
关键词：配电网；无功补偿优化；潮流计算；遗传算法；控制系统
Abstract
The reactive power compensation problem has become an important part of the stable operation of the grid system for the distribution of reactive power compensation algorithm and the way research emerging， under the basic conditions for the future face of the intelligent grid， distribution network optimized automation and intelligent control of reactive power compensation is vital， especially for a series of control methods with reactive power compensation devices， intelligent basis.
Based on the theory of the distribution network， this article reactive power compensation， reactive power compensation of flow calculation of the distribution network reactive power compensation， genetic algorithms and distribution network management system has been studied. Flow calculation algorithm first paper discusses that the speed of the flow calculation and the convergence of the degree will largely affect the final results of optimization of reactive power compensation， and to improve Newton’s method， the former backward substitution method and loop method analysis; traditional genetic algorithm， combined with the distribution network variable characteristics of the traditional genetic algorithm has been improved， and improved take the decimal encoding of the way， the establishment of the fitness function， and to take adaptive way to determine the crossover probability and mutation probability， crossover and mutation operation to improve， to finalize the application process improved Genetic Algorithm in reactive Power compensation; Finally， the overall structure of the management system with reactive power compensation that take the tertiary structure of multi-machine control model is more reasonable， able to meet the basic needs of the development of intelligent power grid， which can solve the limitations of traditional SCADA control system， and intuitive， efficient and scalable efficacy after the system with the a region of the reactive power compensation operation practice， given the major operating functions.
The entire course of the study， the genetic algorithm can effectively enhance the efficiency of Reactive Power Compensation as a distribution network based on reactive power compensation system design， reduce network losses， upgrade power grid run stability of the target， basically to meet the actual needs of the current distribution network optimization of reactive power compensation.
Keywords: distribution network; optimization of reactive power compensation; flow calculation; genetic algorithm; control system
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