基于多目标的主动配电网有功无功协调优化  

Multi-Objective Based Optimization on Active and Reactive Power Coordinated Control in Active Distribution Network

作　　者：吴富杰 苏小林[1] 阎晓霞[1] 刘孝杰[1] 

机构地区：[1]山西大学,山西太原030013

出　　处：《自动化技术与应用》2015年第11期59-65,共7页Techniques of Automation and Applications

摘　　要：大量间歇性分布式电源接入配电网会引发电压越限,限制系统消纳分布式能源的能力。基于节点电压对注入功率的灵敏度分析,揭示了配电网注入有功功率和无功功率对节点电压皆具有调控作用。提出通过对分布式发电(DG)、储能装置(ESS)等的有功功率和无功补偿装置的无功功率的协调控制,实现主动配电网消纳间歇性分布式能源最大化、网损最小化和电压质量优质的综合优化目标。文中建立了主动配电网的多目标优化数学模型,应用判断矩阵法确定出多目标的权重系数,构建成一个综合优化的目标函数。应用粒子群算法进行寻优求解,可得到主动配电网的优化运行方案和调控策略。在IEEE33节点测试系统上进行了多场景仿真分析和研究,结果表明:应用文中所提出的主动多目标优化调控方法 ,既可满足安全约束条件,又能实现有效地降低DG切机量、降低有功网损、保持良好电压质量的综合效应。As massive intermittent distributed generation （DG） access to distribution network, may lead to the voltage beyond the safety limitation, and further restricts the output ability of DG. Based on the sensitivity analysis, both the injected active or reactive power could have a regulation effect on the node voltage. By the coordinated control of DG, energy storage equipment（ESS） and reactive power compensation devices, a comprehensive optimization goal is attained, which aims to maximize the utilization rate of DG, minimizes the transmission loss and maintain better voltage level.In this paper, a multi- objective optimization mathematical model is established in ADN to obtain an objective fimction by determine the weight coefficient of different objective using judgment matrix method. The particle swarm optimization（PSO） is used to optimize the model in ADN, and then the optimized operation schemes and control strategies are attained. Multi-scenario simulation and research on the IEEE 33-bus test system, indicate that the proposed active multi-objective optimization control method can not only satisfy the security constraints, but also achieve a comprehensive effect of minimizing the capacity of DG＇s curtailment and active power loss and keeping good voltage quality.

关 键 词：主动配电网 分布式发电 优化 协调控制 粒子群算法 

分 类 号：TM72[电气工程—电力系统及自动化]