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计及储能和空调负荷的主动配电网多目标优化调度
引用本文:韩笑,周明,李庚银. 计及储能和空调负荷的主动配电网多目标优化调度[J]. 电力系统保护与控制, 2018, 46(7): 14-23
作者姓名:韩笑  周明  李庚银
作者单位:新能源电力系统国家重点实验室华北电力大学,北京102206,新能源电力系统国家重点实验室华北电力大学,北京102206,新能源电力系统国家重点实验室华北电力大学,北京102206
基金项目:国家重点研发计划项目(2016YFB0900100)
摘    要:为了实现可再生分布式能源的充分消纳以及配网负荷峰谷差的降低,提出了一种考虑储能系统和空调负荷的主动配电网多目标调度优化方法。首先,基于空调负荷等效热参数模型和状态列队控制方法,给出了空调负荷虚拟电厂运行参数的计算方法。在此基础上,构建了一种以可再生能源功率削减量最小、配网运行费用最小和负荷曲线方差最小为目标的主动配电网优化调度模型。最后,采用多目标粒子群算法在改进的IEEE 33节点测试系统上对所提模型进行求解和仿真分析。仿真结果表明,所建模型可以有效地提升可再生能源的消纳能力,优化负荷曲线。

关 键 词:空调负荷;储能系统;主动配电网;多目标优化;可再生能源消纳
收稿时间:2018-01-05
修稿时间:2018-02-25

Multi-objective optimal dispatching of active distribution networks considering energy storage systems and air-conditioning loads
HAN Xiao,ZHOU Ming and LI Gengyin. Multi-objective optimal dispatching of active distribution networks considering energy storage systems and air-conditioning loads[J]. Power System Protection and Control, 2018, 46(7): 14-23
Authors:HAN Xiao  ZHOU Ming  LI Gengyin
Affiliation:State Key Laboratory of New Energy Power System North China Electric Power University, Beijing 102206, China,State Key Laboratory of New Energy Power System North China Electric Power University, Beijing 102206, China and State Key Laboratory of New Energy Power System North China Electric Power University, Beijing 102206, China
Abstract:In order to achieve the sufficient consumption of renewable distributed energy and the reduction of the load peak-valley difference in distribution networks, this paper proposes a novel multi-objective optimal dispatching method of active distribution networks considering energy storage systems and air-conditioning loads. Firstly, based on the equivalent thermal parameter model for air-conditioning loads and the state-queue control method, a calculation method for virtual power plant operating characteristics is proposed. Accordingly, a multi-objective optimal dispatching model of active distribution networks is built, aiming to minimize renewable energy curtailment, the operational costs, and load curve variance. Finally, the proposed model is solved and examined on transformed IEEE 33-bus test system by using the multi-objective particle swarm algorithm. Our findings show that our proposed model can effectively increase the consumption of renewable distributed energy and improve the load curve. This work is supported by National Key Research and Development Program of China (No. 2016YFB0900100).
Keywords:air conditioning loads   energy storage systems   active distribution networks   multi-objective optimization   renewable energy consumption
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