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一种基于智能改进算法的定制电力设备优化配置策略
  • ISSN号:1674-3415
  • 期刊名称:《电力系统保护与控制》
  • 时间:0
  • 分类:TM761[电气工程—电力系统及自动化]
  • 作者机构:中国石油大学(华东)信息与控制工程学院,山东青岛266580
  • 相关基金:国家自然科学基金项目(51477184,61271001);中央高校基本科研业务费专项资金项目(14CX02085A)
中文摘要:

为了更好地治理配电网谐波污染、低功率因数以及电力系统电压波动所带来的敏感负荷不能正常工作问题,研究了配电网多种定制电力设备的优化配置。综合考虑电能质量治理目标以及投资费用建立了优化配置数学模型,并提出一种将遗传算法与内点法有机结合的混合优化策略用于多种定制电力设备的优化配置。该混合策略利用遗传算法锁定各装置的最优安装位置并求得近似最优安装容量,将近似容量设为内点法初值寻找更加精确更优的安装容量。此外,分别基于约束越限和预判自适应对遗传算法和内点法做出改进,提高了寻优速度。理论分析和仿真结果表明,该混合算法比单独的遗传算法稳定性更高、寻优结果更加精确。

英文摘要:

In order to solve power quality problems more effectively such as harmonic pollution, low power factor as well as the sensitive loads not to work properly because of voltage sags, flickers and so on. The optimal configuration of custom power devices is studied. By considering power quality improving goals and total investment cost, a mathematical model is proposed for optimization. Besides, a mixed optimization algorithm that combines genetic algorithm and interior-point method is proposed for the optimal configuration of multi-type custom power devices. This mixed strategy uses genetic algorithm to find the optimal location and approximate optimal capacity of each device. Then the approximate capacity will be set as the initial value of the interior-point method, and more accurate capacity can be calculated through interior-point method. Besides, some improvements are made in the process of genetic algorithm and interior-point method. These improvements can speed up the convergence. Theoretical analysis and simulation results indicate that this mixed algorithm has better stability, and more accurate results can be obtained than through traditional genetic algorithm.

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期刊信息
  • 《电力系统保护与控制》
  • 北大核心期刊(2011版)
  • 主管单位:许昌开普电气研究院
  • 主办单位:许昌开普电气研究院
  • 主编:姚致清
  • 地址:河南省许昌市许继大道1706号
  • 邮编:461000
  • 邮箱:pspc@vip.126.com
  • 电话:0374-3212254 3212234
  • 国际标准刊号:ISSN:1674-3415
  • 国内统一刊号:ISSN:41-1401/TM
  • 邮发代号:36-135
  • 获奖情况:
  • 《CAT-CD规范》执行优秀期刊,河南省二十佳优秀科技期刊
  • 国内外数据库收录:
  • 荷兰文摘与引文数据库,美国剑桥科学文摘,中国中国科技核心期刊,中国北大核心期刊(2008版),中国北大核心期刊(2011版),中国北大核心期刊(2014版)
  • 被引量:28000