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文章摘要
考虑多个分布式电源接入配电网的多目标无功优化调度
Multi-objective reactive power optimization of the Distribution Network considering a Large Number of DGs Connected
Received:April 23, 2018  Revised:April 23, 2018
DOI:10.19753/j.issn1001-1390.2019.013.007
中文关键词: 配电网  分布式电源  无功优化  鲸鱼优化算法  有功网损
英文关键词: distribution network  distributed generation  reactive power optimization  Whale optimization algorithm  active power loss
基金项目:
Author NameAffiliationE-mail
Teng Deyun* Intelligent Electric Power Grid Key Laboratory of Sichuan Province Sichuan University 1938654044@qq.com 
Teng Huan Intelligent Electric Power Grid Key Laboratory of Sichuan Province Sichuan University 1938654044@qq.com 
Liu Xin Intelligent Electric Power Grid Key Laboratory of Sichuan Province Sichuan University 1938654044@qq.com 
Kuang Da state grid meishan power supply company 624584671@qq.com 
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中文摘要:
      坚强智能电网的建设促进了分布式电源(Distributed Generation,DG)并网技术的发展,DG并网对配网进行无功优化不仅能够提高电压质量、降低有功网损,还增加了配网运行的灵活性、经济性与安全性。本文以系统有功功率损耗最低与电压偏压量最小为双目标函数,建立无功优化模型。针对目前无功优化问题尚缺乏一种能兼顾求解的高效性与全局搜索最优性的方法,文中将一种新的启发式算法-鲸鱼优化算法(WOA)运用到电网无功优化调度中,对多个DG接入的IEEE-33节点系统进行无功优化仿真分析,研究表明DG并网增加了配网的稳定性,WOA算法在迭代次数、搜索能力上的鲁棒性和有效性。
英文摘要:
      The construction of a strong smart grid has promoted the development of distributed power grid technologies. DG grid-connecting has not only improved voltage quality, reduced active power losses, but also increased the flexibility, economy, and security of distribution network operations. In this paper, the reactive power optimization model is established with the minimum active power loss and the minimum voltage bias as the objective function. Aiming at the current reactive power optimization problem, there is still a lack of a method that can take into account both the efficiency of the solution and the optimality of the global search. A new heuristic algorithm, the Whale Optimization Algorithm (WOA), is applied to reactive power optimization scheduling and performed on IEEE-33 node systems with a largeos DGs accesses. Research shows that DG integration increases the stability of distribution networks, and WOA algorithm robustness and effectiveness in iteration times, search capabilities.
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