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含柔性负荷的主动配电网优化模型研究 被引量:18

Study on optimal model of active distribution network with flexible load
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摘要 随着主动配电网的迅速发展和大量的分布式电源并入配电网,使得电网的优化调度越来越趋向于复杂化,对电网进行优化时需要对多个目标进行优化。而将柔性负荷引入主动配电网的优化调度使主动配电网优化调度更具有灵活性。文中根据分时电价机制将柔性负荷分为可转移负荷和可中断负荷两种类型;以柔性负荷调度量和分布式电源有功出力为决策变量建立含有柔性负荷的主动配电网优化调度二层模型。最后以IEEE-33节点模型作为算例,通过构造遗传算法和模拟退火算法的混合算法计算柔性负荷不同的调度量对主动配电网系统运行成本,验证将柔性负荷引入主动配电网优化调度中的方法,能够有效的降低系统运行成本,减小网络损耗。 With the rapid development of active distribution networks and the incorporation of a large number of distributed power sources into the distribution network,the optimization and dispatching of power grids tends to become more and more complicated. When optimizing the power grid,multiple objectives need to be optimized. It makes the optimal scheduling of the active distribution network more flexible by introducing the flexible load into the optimal distribution of the active distribution network. In this paper,according to spot price mechanism,the flexible load is divided into two types:transferable load and interruptible load. This paper establishes a two-layer model of active distribution network optimization scheduling with flexible load,which introduces decision variables of flexible load scheduling and distributed power supply active power. Finally,taking the IEEE-33 node model as example,the hybrid algorithm of constructing genetic algorithm and simulated annealing algorithm is used to calculate the different scheduling load of flexible load to the operating cost of active distribution network system. It is verified that the method of introducing flexible load into the optimal distribution of active distribution network can effectively reduce the operating cost of the system and reduce the network loss.
作者 贾先平 邹晓松 袁旭峰 熊炜 Jia Xianping;Zou Xiaosong;Yuan Xufeng;Xiong Wei(School of Electrical Engineering,Guizhou University,Guiyang 550025,Chin)
出处 《电测与仪表》 北大核心 2018年第13期46-52,116,共8页 Electrical Measurement & Instrumentation
基金 国家自然科学基金资助项目(51667007)
关键词 柔性负荷 二层模型 遗传算法 模拟退火算法 flexible loading two-layer model genetic algorithm simulated annealing algorithm
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