基于智能多代理属地管理系统的有序用电模式
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摘要
有序用电是缓解供电系统高峰时段供需矛盾的重要手段,随着负荷管理系统的日益智能化,需要充分挖掘用户间的互动能力,提高有序用电决策方案的适用性,为此提出一种包含互济机制在内的智能多代理属地管理系统。在有序用电决策方案中,兼顾用户用电价值、错避峰潜力及其意愿,综合考虑用户与电网的利益,对于居民用户,调整电动汽车充电时段以促进其户用分布式电源就地消纳。并设立动态支援意愿序位表,通过用户间电能互济,对方案做出合理调整。算例分析结果表明了上述方法的有效性和经济性,增强了用户间的互动能力,可实现代理属地内部电力资源自治协调管理。
Orderly power utilization is an important measure to alleviate contradiction between supply and demand in power system peak load period. As load management system becomes more and more smart, it is necessary to fully explore interactive ability among users and make decision-making schemes for orderly power utilization more applicable. Therefore, an intelligent multi-agent apanage management system including mutual aid mechanism is proposed. In the decision-making scheme, users' electrical value, potential of peak shifting and their willingness are considered, and the interests of both power consumers and power grid are comprehensively considered. For residential users, their electric vehicles' charging time are managed to consume the distributed power generation locally. To conduct electrical mutual aid among users and adjust the schemes reasonably, a dynamic support willing ordinal table is established. Results of case study show that above method is effective and economic in improving interactive ability among users. Agents can coordinate their apanage power resources optimally.
Orderly power utilization is an important measure to alleviate contradiction between supply and demand in power system peak load period. As load management system becomes more and more smart, it is necessary to fully explore interactive ability among users and make decision-making schemes for orderly power utilization more applicable. Therefore, an intelligent multi-agent apanage management system including mutual aid mechanism is proposed. In the decision-making scheme, users' electrical value, potential of peak shifting and their willingness are considered, and the interests of both power consumers and power grid are comprehensively considered. For residential users, their electric vehicles' charging time are managed to consume the distributed power generation locally. To conduct electrical mutual aid among users and adjust the schemes reasonably, a dynamic support willing ordinal table is established. Results of case study show that above method is effective and economic in improving interactive ability among users. Agents can coordinate their apanage power resources optimally.
引文
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[14]王芃,文福拴,王斐,等.基于混合多属性评价的错峰用电预案编制方法[J].电力系统自动化,2016,40(5):54-61.Wang Peng,Wen Fushuan,Wang Fei,et al.A hybrid multiple-attribute evaluation based scheduling method for peak load shifting[J].Automation of Electric Power Systems,2016,40(5):54-61(in Chinese).
[15]汤奕,鲁针针,伏祥运.居民主动负荷促进分布式电源消纳的需求响应策略[J].电力系统自动化,2015,39(24):49-55.Tang Yi,Lu Zhenzhen,Fu Xiangyun.Demand response strategies for promoting consumption of distributed power generation with residential active loads[J].Automation of Electric Power Systems,2015,39(24):49-55(in Chinese).
[16]Chavali P,Yang P,Nehorai A.A distributed algorithm of appliance scheduling for home energy management system[J].IEEE Trans on Smart Grid,2014,5(1):282-290.
[17]张良,严正,冯冬涵,等.采用两阶段优化模型的电动汽车充电站内有序充电策略[J].电网技术,2014,38(4):968-974.Zhang Liang,Yan Zheng,Feng Donghan,et al.Two-stage optimization model based coordinated charging for EV charging station[J].Power System Technology,2014,38(4):968-974(in Chinese).
[18]陈俊全.精细化有序用电管理集中决策方法研究[D].杭州:浙江大学,2014.
[19]黄宇腾.负荷形态分析与负荷管理优化研究[D].杭州:浙江大学,2013.
[20]卜凡鹏,陈俊艺,张琪祁,等.一种基于双层迭代聚类分析的负荷模式可控精细化识别方法[J].电网技术,2018,42(3):903-913.Bu Fanpeng,Chen Junyi,Zhang Qiqi,et al.A controllable and refine recognition method of electrical load pattern based on bilayer iterative clustering analysis[J].Power System Technology,2018,42(3):903-913(in Chinese).
[2]陆婷婷,高赐威,苏卫华,等.有序用电避峰预案优化编制方法研究[J].电网技术,2014,38(9):2315-2321.Lu Tingting,Gao Ciwei,Su Weihua,et al.Research on drafting of optimal peak averting planning for ordered power utilization[J].Power System Technology,2014,38(9):2315-2321(in Chinese).
[3]钟海旺,夏清,黄媚,等.降低网损和消除阻塞的有序用电模式与方法[J].电网技术,2013,37(7):1915-1921.Zhong Haiwang,Xia Qing,Huang Mei,et al.A pattern and method of orderly power utilization considering transmission loss reduction and congestion elimination[J].Power System Technology,2013,37(7):1915-1921(in Chinese).
[4]张锋.有序用电指标体系及其评价方法的研究[D].北京:华北电力大学,2009.
[5]陈俊全,张明明,王科,等.精细化有序用电管理的框架设计[J].能源工程,2014(2):57-63.Chen Junquan,Zhang Mingming,Wang Ke,et al.Framework design of meticulous orderly power consumption management[J].Energy Engineering,2014(2):57-63(in Chinese).
[6]王岩,刘建喜,何德卫.考虑多目标优化的有序用电智能决策研究[J].电力需求侧管理,2015,17(3):16-20.Wang Yan,Liu Jianxi,He Dewei.Research of the intelligent decision system for orderly electricity use with multi-objective optimization[J].Power Demand Side Management,2015,17(3):16-20(in Chinese).
[7]颜庆国,童星,张宁,等.考虑用户节电损失的有序用电动态多级时空协调方法[J].电网技术,2016,40(2):425-432.Yan Qingguo,Tong Xing,Zhang Ning,et al.A dynamic multi-level temporal and spatial coordination method for orderly power utilization based on customer load curtailment cost characteristics[J].Power System Technology,2016,40(2):425-432(in Chinese).
[8]张明明,陈俊全,王科,等.多时间尺度协调的有序用电集中决策方法[J].电力系统自动化,2014,38(22):70-77.Zhang Mingming,Chen Junquan,Wang Ke,et al.A centralized decision method for multi-time scale coordinated orderly power consumption[J].Automation of Electric Power Systems,2014,38(22):70-77(in Chinese).
[9]汤奕,鲁针针,伏祥运.居民主动负荷促进分布式电源消纳的需求响应策略[J].电力系统自动化,2015,39(24):49-55.Tang Yi,Lu Zhenzhen,Fu Xiangyun.Demand response strategies for promoting consumption of distributed power generation with residential active loads[J].Automation of Electric Power Systems,2015,39(24):49-55(in Chinese).
[10]石坤,孔令基,李彬,等.基于熵值法改进的新型电力错峰资源调度策略[J].电力建设,2017,38(4):57-63.Shi Kun,Kong Lingji,Li Bin,et al.A novel power load shifting resource dispatching strategy based on improved entropy method[J].Electric Power Construction,2017,38(4):57-63(in Chinese).
[11]李强,宋宁希,王剑晓,等.基于用户互动能力的优化用电模式与方法[J].电网技术,2016,40(6):1818-1824.Li Qiang,Song Ningxi,Wang Jianxiao,et al.A pattern and method of optimized power utilization based on consumers’interaction capability[J].Power System Technology,2016,40(6):1818-1824(in Chinese).
[12]陈霄,童星,张宁,等.有序用电智能多代理系统架构与机制研究[J].电力系统保护与控制,2016,44(9):75-82.Chen Xiao,Tong Xing,Zhang Ning,et al.Intelligent multi-agent system for orderly power utilization:architecture and coordination mechanism design[J].Power System Protection and Control,2016,44(9):75-82(in Chinese).
[13]辛昊,严正,许少伦.基于多代理系统的电动汽车协调充电策略[J].电网技术,2015,39(1):48-54.Xin Hao,Yan Zheng,Xu Shaolun.Multi-agent system based coordinated charging strategy for electric vehicles[J].Power System Technology,2015,39(1):48-54(in Chinese).
[14]王芃,文福拴,王斐,等.基于混合多属性评价的错峰用电预案编制方法[J].电力系统自动化,2016,40(5):54-61.Wang Peng,Wen Fushuan,Wang Fei,et al.A hybrid multiple-attribute evaluation based scheduling method for peak load shifting[J].Automation of Electric Power Systems,2016,40(5):54-61(in Chinese).
[15]汤奕,鲁针针,伏祥运.居民主动负荷促进分布式电源消纳的需求响应策略[J].电力系统自动化,2015,39(24):49-55.Tang Yi,Lu Zhenzhen,Fu Xiangyun.Demand response strategies for promoting consumption of distributed power generation with residential active loads[J].Automation of Electric Power Systems,2015,39(24):49-55(in Chinese).
[16]Chavali P,Yang P,Nehorai A.A distributed algorithm of appliance scheduling for home energy management system[J].IEEE Trans on Smart Grid,2014,5(1):282-290.
[17]张良,严正,冯冬涵,等.采用两阶段优化模型的电动汽车充电站内有序充电策略[J].电网技术,2014,38(4):968-974.Zhang Liang,Yan Zheng,Feng Donghan,et al.Two-stage optimization model based coordinated charging for EV charging station[J].Power System Technology,2014,38(4):968-974(in Chinese).
[18]陈俊全.精细化有序用电管理集中决策方法研究[D].杭州:浙江大学,2014.
[19]黄宇腾.负荷形态分析与负荷管理优化研究[D].杭州:浙江大学,2013.
[20]卜凡鹏,陈俊艺,张琪祁,等.一种基于双层迭代聚类分析的负荷模式可控精细化识别方法[J].电网技术,2018,42(3):903-913.Bu Fanpeng,Chen Junyi,Zhang Qiqi,et al.A controllable and refine recognition method of electrical load pattern based on bilayer iterative clustering analysis[J].Power System Technology,2018,42(3):903-913(in Chinese).