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文章摘要
基于改进QPSO算法的主动配电网削峰填谷策略研究
Research on peak load shifting in active distribution network based on improved QPSD algorithm
Received:December 25, 2019  Revised:January 09, 2020
DOI:10.19753/j.issn1001-1390.2022.02.017
中文关键词: 主动配电网  量子粒子群算法  削峰填谷  多目标优化
英文关键词: active distribution network, quantum particle swarm optimization algorithm, peak load shifting, multi-objective optimization
基金项目:基于网源荷柔性多端互联直流配电中心的城市配电网运行控制技术研究;适用于分散式DF接入的低压配电网多源供电关键技术研究;模块化多电平直流融冰装置提高配电网供电可靠性应用研究
Author NameAffiliationE-mail
Li Xingchen Guizhou University College of electrical engineering 357383713@qq.com 
Yuan Xufeng* Guizhou University College of electrical engineering 17015676@qq.com 
Li Peiran Guizhou University College of electrical engineering 2691621171@qq.com 
Shao Zhen Guizhou University College of electrical engineering 331212049@qq.com 
XiongWei Guizhou University College of electrical engineering 420034562@qq.com 
BanGuobang Guizhou Power Grid Co., Ltd. Institute of Electric Power Science 7393839@qq.com 
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中文摘要:
      相较于传统配电网,主动配电网具有分布式电源利用率高、网损低、可控性强等特点,其优化运行为典型的多目标优化问题。文中同时考虑储能系统削峰填谷在平滑负荷曲线和分布式电源运行经济性两方面的性能,建立了典型主动配电网多目标优化模型;考虑该模型具有多维非线性特点,提出了一种基于量子粒子群(QPSO)的改进算法,利用量子理论中的量子行为和概率表达特性,在算法的全局寻优能力和种群多样性方面得到明显提升。最后,算例分析验证了该方法的可行性。
英文摘要:
      Compared with the traditional distribution network, the active distribution network (ADN) has the advantages of high utilization of distributed generation, low network loss and strong controllability, and its optimal operation is a typical multi-objective optimization problem. This paper considers peak load shifting strategy of energy storage system in smoothing load curve and healthy economy simultaneously and establishes a typical multi-objective ADN model; considering the multi-dimensional and nonlinear characteristics, this paper proposes an improved algorithm based on quantum particle swarm optimization (QPSD),which adopts the superposition state and probability expression characteristics of quantum theory to increase the population diversity and global optimization. Finally, a typical active distribution network is taken as an example to verify the feasibility of the method.
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