引用本文:陈星莺,史豪杰,刘 健,余 昆,廖迎晨.基于招投标策略的地区电网无功优化控制[J].电力自动化设备,2015,35(7):
CHEN Xingying,SHI Haojie,LIU Jian,YU Kun,LIAO Yingchen.Optimal reactive power control based on bidding strategy in district power grid[J].Electric Power Automation Equipment,2015,35(7):
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基于招投标策略的地区电网无功优化控制
陈星莺1,2, 史豪杰1, 刘 健3, 余 昆1,2, 廖迎晨1,2
1.河海大学 能源与电气学院,江苏 南京 211100;2.江苏省配用电与能效工程技术研究中心,江苏 南京 211100;3.陕西电力科学研究院,陕西 西安 710054
摘要:
专家系统次优控制是实现地区电网在线无功优化控制的后备保障。针对传统产生式规则编制的无功优化专家系统软件逻辑复杂的问题,提出基于招投标策略的无功优化控制决策模型,依据综合评标法建立电压无功优化评价模型;利用多智能体系统(MAS)并行、协调求解问题的特点,建立地区电网无功优化控制系统架构,通过多智能体间协调控制实现招投标策略,确保地区电网在线无功优化控制系统的鲁棒性、可维护性和扩展性。实际应用验证了该系统的有效性。
关键词:  地区电网  多智能体  招投标策略  无功优化控制  专家系统  模型  控制
DOI:
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基金项目:国家高技术研究发展计划(863计划)项目(2012AA-050214);国家自然科学基金资助项目(51077043);国家电网公司重大科技项目(智能配电网自愈控制技术研究与开发)
Optimal reactive power control based on bidding strategy in district power grid
CHEN Xingying1,2, SHI Haojie1, LIU Jian3, YU Kun1,2, LIAO Yingchen1,2
1.College of Energy and Electrical Engineering,Hohai University,Nanjing 211100,China;2.Jiangsu Engineering Research Center for Distribution & Utilization and Energy Efficiency,Nanjing 211100,China;3.Shaanxi Electric Power Research Institute,Xi’an 710054,China
Abstract:
The suboptimal control by expert system is the backup protection of online optimal reactive power control in district power grid. Since the logic of expert system software designed according to the traditional production rules is complicated,a decision model of optimal reactive power control is established based on the bidding strategy and an evaluation model of voltage reactive power optimization is built based on the comprehensive bid evaluation method. A framework based on the multi-Agent system is established for the optimal reactive power control of district power grid,which realizes the bidding strategy by the parallel and coordinated control among multiple Agents to ensure its robustness,maintainability and expandability. The practical application verifies its effectiveness.
Key words:  district power grid  multi-Agent  bidding strategy  optimal reactive power control  expert system  models  control

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