基于多目标粒子群算法的风光水火多源AGC协调优化方法
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TM315

基金项目:

国网湖南省电力有限公司科技项目(5216A520000N);国家自然科学基金资助项目(51677012)。


Multi-source AGC coordination optimization method with Wind-PV-Hydro-Thermal based on multi-objective particle swarm optimization algorithm
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    摘要:

    针对高比例新能源渗透背景下的常规AGC机组和新能源AGC机组协调控制问题,提出了基于"两个细则"的风光水火多电源AGC多目标协调优化方法,该方法在确保电网调频经济性的同时兼顾了电网的调频质量和网架功率传输能力。基于某地区长期AGC历史统计数据,分析了不同类型机组的调频特性,计算其调频指标;基于华中电网"两个细则"的要求,以电网的调频成本和网损成本、调频速度和调频精度为目标,建立了含风光水火的多目标AGC有功协调优化模型;结合某内陆地区网架结构和AGC数据,采用多目标粒子群算法进行模型求解,得到了各个AGC场站的有功出力,进而验证了文中提出方法的有效性。

    Abstract:

    In order to realize the coordinated control of conventional AGC and renewable energy AGC under the high penetration of renewable energy to grid, this paper proposes an AGC multi-objective coordination optimization method with Wind-PV-Hydro-Thermal. This method not only ensures the economic operation of the power grid, but also considers the frequency quality and power transmission capacity of the grid. Firstly, based on the long-term AGC historical data in a certain region, the regulate frequency characteristics of different types of units are analyzed, and the regulate frequency indexes are calculated. Secondly, based on the requirements of the "Two Rules" of the Central China Power Grid, using the regulate frequency cost, power loss cost, regulate frequency speed and regulate frequency accuracy as objectives, a multi-objective AGC active power coordination optimization model including Wind-PV-Hydro-Thermal is proposed. Finally, considering the power grid structure and AGC data in an inland region, the model is solved using the multi-objective particle swarm algorithm, and the active power of each AGC station is obtained, verifying the effectiveness of the proposed method in this paper.

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宋兴荣,吴晋波,杨志学,李振文,胡迪军,洪权,任洲洋.基于多目标粒子群算法的风光水火多源AGC协调优化方法[J].重庆大学学报,2022,45(7):13-23.

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  • 收稿日期:2021-01-09
  • 最后修改日期:2021-04-14
  • 在线发布日期: 2022-07-27
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