计算机集成制造系统 ›› 2021, Vol. 27 ›› Issue (3): 787-799.DOI: 10.13196/j.cims.2021.03.012

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基于分布式光伏运维的多类型资源调度技术

高鹏1,苏雍贺1,靳健2,谢祥颖3,张长志4,陶飞1   

  1. 1.北京航空航天大学自动化科学与电气工程学院
    2.北京师范大学政府管理学院
    3.国网电子商务有限公司光伏云事业部
    4.国网天津市电力公司电力科学研究院
  • 出版日期:2021-03-31 发布日期:2021-03-31
  • 基金资助:
    国家重点研发计划资助项目(2018YFB1500800);国家电网有限公司科技资助项目(SGTJDK00DYJS2000148);北京市科技重大专项资助项目(Z191100002719004)。

Multi-type resource scheduling technology based on distributed photovoltaic operation and maintenance

  • Online:2021-03-31 Published:2021-03-31
  • Supported by:
    Project supported by the National Key Research and Development Program,China (No.2018YFB1500800),the Science and Technology Foundation of State Grid Corporation,China (No.SGTJDK00DYJS2000148),and the Beijing Municipal Science and Technology Major Project,China(No.Z191100002719004).

摘要: 针对当前分布式光伏运维过程中存在的人工调度方式效率低,成本高的问题,提出了适用于分布式光伏运维的多类型资源调度方法。该方法通过分析分布式光伏运维资源匹配规则,建立了分布式光伏运维资源调度问题模型;为了验证不同算法求解不同场景下该模型的性能,开发了分布式光伏运维资源调度系统,并进行了验证分析,为每种场景选择了最优的调度算法。实验结果表明,所研究的分布式光伏运维资源调度技术,制定调度计划速度快,方案合理,可以减少运维成本,提高服务质量。

关键词: 分布式光伏, 维修服务, 静态调度, 遗传模拟退火算法, 粒子群算法

Abstract: To solve the problem of low efficiency and high cost in the process of distributed photovoltaic operation and maintenance,a multi-type resource scheduling method suitable for distributed photovoltaic operation and maintenance was proposed.By analyzing the matching rules of distributed photovoltaic operation and maintenance resources,the distributed photovoltaic operation and maintenance resource scheduling model was established.To verify the performance of different algorithms for solving the model under different scenarios,a distributed photovoltaic operation and maintenance resource scheduling system was developed analyzed,and the optimal scheduling algorithm was selected for each scenario.The distributed photovoltaic operation and maintenance resource scheduling technology studied was fast in scheduling and reasonable in scheme,which could reduce operation and maintenance cost and improve service quality.

Key words: distributed photovoltaic, maintenance service, static scheduling, genetic simulated annealing algorithm, particle swarm algorithm

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