基于多代理系统的微电网多尺度能量管理

摘要
图/表
参考文献
相关文章 (15)

全文: PDF (3479 KB)
输出: BibTeX | EndNote (RIS)

摘要对基于多代理系统的微电网能量管理策略进行了研究。首先,建立三层多代理系统;然后,基于博弈论研究大电网与多个微电网之间的上层电力市场竞价策略;进而,以单个微电网为研究对象,考虑需求侧响应,研究制定多时间尺度的分布式发电调度策略;最后,考虑到调度策略需要有负荷和风力发电机组短期预测作为前提保障,所以运用混沌相空间预测算法对负荷和风力发电机组进行短期预测。仿真结果验证了所提能量管理策略的有效性。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	贾星蓓
	窦春霞
	岳东
	徐式蕴

关键词 ：多代理系统, 微电网, 多时间尺度, 能量管理, 电力市场, 竞价策略

Abstract：The microgrid (MG) energy management strategy based on multi-agent-system (MAS) is researched in this paper.Firstly,a three-level multi-agent-system is constructed.Then,the optimal power market bidding strategies are researched between the upper-level and middle-level agents considering the MG profit maximization.Thirdly,taking a microgrid as the research object and considering demand response (DR),multi-time-scales energy management strategies are produced for distributed energy resources.Finally,taking into aocount the short-term load farecasting and renewable energy generations forecasting are guarantee for scheduling strategy,so, in the short-term load and renewable energy generation are forecasted by chaos phase space theory.The simulation results verify the effectiveness of the proposed energy management approach.

Key words： Multi-agent-system microgrid multi-time-scales energy management power market bidding strategy

收稿日期: 2015-06-04 出版日期: 2016-09-18

PACS:

TM73

基金资助:国家自然科学基金项目资助(51177142,61573300)。

作者简介: 贾星蓓女,1986年生,博士研究生,研究方向为微电网能量优化管理策略。E-mail:jiaxingbei1986@163.com;窦春霞女,1967年生,教授,博士生导师,研究方向为新能源控制技术、电力大系统分布式控制、微电网智能控制等。E-mail:cxdou@ysu.edu.cn(通信作者)

引用本文:

贾星蓓,窦春霞,岳东,徐式蕴. 基于多代理系统的微电网多尺度能量管理[J]. 电工技术学报, 2016, 31(17): 63-73. Jia Xingbei, Dou Chunxia, Yue Dong ,Xu Shiyun. Multiple-Time-Scales Optimal Energy Management in Microgrid System Based on Multi-Agent-System. Transactions of China Electrotechnical Society, 2016, 31(17): 63-73.

链接本文:

https://dgjsxb.ces-transaction.com/CN/Y2016/V31/I17/63

[1] 王成山,武震,李鹏.微电网关键技术研究[J].电工技术学报,2014,29(2):1-12.
Wang Chengshan,Wu Zhen,Li Peng.Research on key technologies of microgrid[J].Transactions of China Electrotechnical Society,2014,29(2):1-12.
[2] 张建华,于雷,刘念,等.含风/光/柴/蓄及海水淡化负荷的微电网容量优化配置[J].电工技术学报,2014,29(2):102-112.
Zhang Jianhua,Yu Lei,Liu Nian,et al.Capacity configuration optimization for island microgrid with wind/photovoltaic/diesel/storage and seawater desalination load[J].Transactions of China Electrotechnical Society,2014,29(2):102-112.
[3] 郭思琪,袁越,张新松,等.多时间尺度协调控制的独立微网能量管理策略[J].电工技术学报,2014,29(2):122-129.
Guo Siqi,Yuan Yue,Zhang Xinsong,et al.Energy management strategy of isolated microgrid based on multi-time scale coordinated control[J].Transactions of China Electrotechnical Society,2014,29(2):122-129.
[4] 李东东,崔龙龙,林顺富,等.家庭智能用电系统研究及智能控制器开发[J].电力系统保护与控制,2013,41(4):123-129.
Li Dongdong,Cui Longlong,Lin Shunfu,et al.Study of smart power utilization system and development of smart controller for homes[J].Power System Protection and Control,2013,41(4):123-129.
[5] Logenthiran T,Srinivasan D,Khambadkone A M.Multi-agent system for energy resource scheduling of integrated microgrids in a distributed system[J].Electric Power Systems Research,2011,81(1):138-148.
[6] 丁明,马凯,毕锐.基于多代理系统的多微网能量协调控制[J].电力系统保护与控制,2013,41(24):1-8.
Ding Ming,Ma Kai,Bi Rui.Energy coordination control of multi-microgrid based on multi-agent system[J].Power System Protection and Control,2013,41(24):1-8.
[7] 杨丽君,于琦,魏玲玲,等.基于移动多代理动态联盟的配电网故障恢复研究[J].电工技术学报,2016,31(8):147-155.
Yang Lijun,Yu Qi,Wei Lingling,et al.A distribution network fault recovery study on the dynamic alliance of mobile multi-agent[J].Transactions of China Electrotechnical Society,2016,31(8):147-155.
[8] 艾芊,章健.基于多代理系统的微电网竞价优化策略[J].电网技术,2010,34(2):46-51.
Ai Qian,Zhang Jian.Optimization bidding strategies of microgrids based on multi-agent system[J].Power System Technology,2010,34(2):46-51.
[9] Wang Jianhui,Zhou Zhi,Botterud A.An evolutionary game approach to analyzing bidding strategies in electricity markets with elastic demand[J].Energy,2011,36(5):3459-3467.
[10]Langary D,Sadati N,Ranjbar A M.Direct approach in computing robust Nash strategies for generating companies in electricity markets[J].Electrical Power and Energy Systems,2014,54(54):442-453.
[11]Kazemi M,Ivatloo B M,Ehsan M.Risk-based bidding of large electric utilities using information gap decision theory considering demand response[J].Electric Power Systems Research,2014,114(3):86-92.
[12]Nojavan S,Zare K,Ashpazi M A.A hybrid approach based on IGDT-MPSO method for optimal bidding strategy of price-taker generation station in day-ahead electricity market[J].Electrical Power and Energy Systems,2015,69:335-343.
[13]陈昌松,段善旭,蔡涛,等.基于改进遗传算法的微网能量管理模型[J].电工技术学报,2013,28(4):196-201.
Chen Changsong,Duan Shanxu,Cai Tao,et al..Microgrid energy management model based on improved genetic arithmetic[J].Transactions of China Electrotechnical Society,2013,28(4):196-201.
[14]麻秀范,崔换君.改进遗传算法在含分布式电源的配电网规划中的应用[J].电工技术学报,2011,26(3):175-181.
Ma Xiufan,Cui Huanjun.An improved genetic algorithm for distribution network planning with distributed generation[J].Transactions of China Electrotechnical Society,2011,26(3):175-181.
[15]Zakariazadeh A,Jadid S.Smart microgrid energy and reserve scheduling with demand response using stochastic optimization[J].Electrical Power and Energy Systems,2014,63(12):523-533.
[16]Mazidi M,Zakariazadeh A,Jadid S,et al.Integrated scheduling of renewable generation and demand response programs in a microgrid[J].Energy Conversion and Management,2014,86(10):1118-1127.
[17]Handschin E,Slomski H.Unit commitment in thermal power systems with long-term energy constraints[J].IEEE Transactions on Power Systems,1990,5(4):1470-1477.
[18]杨胜春,刘建涛,姚建国,等.多时间尺度协调的柔性负荷互动响应调度模型与策略[J].中国电机工程学报,2014,34(22):3664-3673.
Yang Shengchun,Liu Jiantao,Yao Jianguo,et al.Model and strategy for multi-time scale coordinated flexible load interactive scheduling[J].Proceedings of the CSEE,2014,34(22):3664-3673.
[19]曹永强,王本德,刘金禄.基于二元对比定权法的水质评价模型及其应用[J].水电能源科学,2002,20(3):19-21.
Cao Yongqiang,Wang Bende,Liu Jinlu.Water quality assessment model based on dualistic factor contrast for indexes weight calculation and its application[J].International Journal Hydroelectric Energy,2002,20(3):19-21.
[20]栗然,崔天宝,肖进永.基于云模型的短期电价预测[J].电网技术,2009,33(17):185-190.
Li Ran,Cui Tianbao,Xiao Jinyong.Short term electricity price forecasting based on cloud model[J].Power System Technology,2009,33(17):185-190.
[21]Green R C,Wang Lingfeng,Alam M.Training neural networks using central force optimization and particle swarm optimization:insights and comparisons[J].Expert Systems with Applications,2012,39(1):555-563.
[22]Kouhi S,Keynia F,Ravadanegh S N.A new short-term load forecast method based on neuro-evolutionary algorithm and chaotic feature selection[J].Electrical Power and Energy Systems,2014,62(11):862-867.
[23]韩敏.混沌时间序列预测理论与方法[M].北京:中国水利水电出版社,2007.
[24]陈鹏,周晖.微电网电力市场交易模型[J].电力需求侧管理,2011,13(4):23-29.
Chen Peng,Zhou Hui.Research on trading model of micro-grid under market conditions[J].Power DSM,2011,13(4):23-29.