大型风电场多Agent系统建模仿真及降损控制

肖运启, 李浩志, 卢泽众, 马静静, 付楠

太阳能学报 ›› 2022, Vol. 43 ›› Issue (9) : 314-320.

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太阳能学报 ›› 2022, Vol. 43 ›› Issue (9) : 314-320. DOI: 10.19912/j.0254-0096.tynxb.2020-1369

大型风电场多Agent系统建模仿真及降损控制

  • 肖运启, 李浩志, 卢泽众, 马静静, 付楠
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LARGE-SCALE WIND FARM MODELING AND LOSS REDUCTION CONTROL BASDE ON MULTI-AGENT SYSTEM

  • Xiao Yunqi, Li Haozhi, Lu Zezhong, Ma Jingjing, Fu Nan
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文章历史 +

摘要

设计一种基于多Agent的风电场控制架构,并针对集电线路损耗突出的问题,提出一种无功降损控制策略。同时,开发基于Java/JADE + MySQL + Matlab/Simulink的混合仿真平台,对某125 MW大型风电场进行多Agent系统建模,算例结果验证了所提策略的有效性。

Abstract

Due to the increasing installed capacity of wind farm, traditional centralized control and communication mode cannot meet the requirements of operation reliability and compatibility. Therefore, a wind farm control framework based on multi-agent is designed, with a novel reactive power control strategy for collector line loss reduction. Meanwhile, a hybrid multi-agent simulation platform based on Java/JADE+MySQL+Matlab/Simulink is developed, on which a 125 MW wind farm is modeled and simulated. The study results verify the effectiveness of the strategy proposed.

关键词

风电场 / 无功功率 / 粒子群算法 / 多Agent系统 / JADE平台

Key words

wind farm / reactive power / particle swarm optimization (PSO) / multi Agent systems / JADE platform

引用本文

导出引用
肖运启, 李浩志, 卢泽众, 马静静, 付楠. 大型风电场多Agent系统建模仿真及降损控制[J]. 太阳能学报. 2022, 43(9): 314-320 https://doi.org/10.19912/j.0254-0096.tynxb.2020-1369
Xiao Yunqi, Li Haozhi, Lu Zezhong, Ma Jingjing, Fu Nan. LARGE-SCALE WIND FARM MODELING AND LOSS REDUCTION CONTROL BASDE ON MULTI-AGENT SYSTEM[J]. Acta Energiae Solaris Sinica. 2022, 43(9): 314-320 https://doi.org/10.19912/j.0254-0096.tynxb.2020-1369
中图分类号: TM614   

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