基于马尔科夫链的电力负荷优化组合及应用
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摘要
具有波动性的电力用户负荷之间有的具有同时性,有的具有互补性,供电区内用户组成不同,则供电区综合负荷的波动性也不同。为提高配电网运行效率,改善配电网各供电区的综合负荷特性,文章提出负荷优化组合方法,并且为了能方便和有效地计及波动负荷序列的随机性,基于马尔科夫链理论对负荷进行建模和分析。首先对配电网内每个用户(负荷点)的历史日负荷曲线进行分类,并获得各用户的聚类负荷曲线;然后以日负荷曲线作为划分负荷状态的依据,基于马尔科夫链理论,对每个用户不同聚类状态及供电区综合负荷状态进行分析;最后基于负荷状态分析及用户的分配或再分配,建立以优化配电网各供电区综合负荷特性为目标的负荷优化组合模型,提出配电网各供电区的负荷最优组合方案。算例分析表明,提出的方法能有效优化供电区的综合负荷特性,达到削峰填谷、降低配电网损耗、提高配电网运行效率的目的,从而为配电网规划或改造提供参考。
This paper proposed a new planning idea and method for distribution networks considering load fluctuation based on power load optimal combination with Markov Chain, making analyses of random loads sequences efficient and resulting in better integrated load characteristics. Firstly, load curve states were classified for each consumer(load point) based on daily load data. Secondly, load state analyses of each single consumer and power supply area were conducted based on Markov Chain. Finally, in order to optimize integrated load characteristics, a model based on load state analysis was set up, capable of solving load optimal combination problem by adjusting network and load distribution. Case studies show that the developed method can be applied to optimize integrated load characteristics of power supply areas, reduce distribution network loss and provide guidance for distribution network planning and renovation.
This paper proposed a new planning idea and method for distribution networks considering load fluctuation based on power load optimal combination with Markov Chain, making analyses of random loads sequences efficient and resulting in better integrated load characteristics. Firstly, load curve states were classified for each consumer(load point) based on daily load data. Secondly, load state analyses of each single consumer and power supply area were conducted based on Markov Chain. Finally, in order to optimize integrated load characteristics, a model based on load state analysis was set up, capable of solving load optimal combination problem by adjusting network and load distribution. Case studies show that the developed method can be applied to optimize integrated load characteristics of power supply areas, reduce distribution network loss and provide guidance for distribution network planning and renovation.
引文
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[16]李欣然,姜学皎,钱军,等.基于用户日负荷曲线的用电行业分类与综合方法[J].电力系统自动化,2010,34(10):56-61.Li Xinran,Jiang Xuejiao,Qian Jun,et al.A classifying and synthesizing method of power consumer industry based on the daily load profile[J].Automation of Electric Power Systems,2010,34(10):56-61(in Chinese).
[17]Tan Pangning,Steinbach Michael,Kumar V.数据挖掘导论[M].范明,范宏建,等译.北京:人民邮电出版社,2011:39-50,327-330.
[18]黄宇腾,侯芳,周勤,等.一种面向需求侧管理的用户负荷形态组合分析方法[J].电力系统保护与控制,2013,41(13):20-25.Huang Yuteng,Hou Fang,Zhou Qin,et al.A new combinational electrical load analysis method for demand side management[J].Power System Protection and Control,2013,41(13):20-25(in Chinese).
[19]罗毅,李昱龙.基于熵权法和灰色关联分析法的输电网规划方案综合决策[J].电网技术,2013,37(1):77-81.Luo Yi,Li Yulong.Comprehensive decision-making of transmission network planning based on entropy weight and grey relational analysis[J].Power System Technology,2013,37(1):77-81(in Chinese).
[20]赵希正.中国电力负荷特性分析与预测[M].北京:中国电力出版社,2002:30-48.
[21]徐玖平,李军.多目标决策的理论与方法[M].北京:清华大学出版社,2005:80-128.
[22]周明,孙树栋.遗传算法原理与应用[M].北京:国防工业出版社,1999:18-31.
[2]欧帝宏,陈皓勇,何瑞辉.一种基于解空间划分的配电网最优重构算法[J].电网技术,2012,36(3):140-145.Ou Dihong,Chen Haoyong,He Ruihui.An optimal distribution network reconfiguration algorithm based on division of solution space[J].Power System Technology,2012,36(3):140-145(in Chinese).
[3]王淳.基于化学反应算法的配电网重构[J].电网技术,2012,36(5):209-214.Wang Chun.A distribution network reconfiguration based on chemical reaction optimization[J].Power System Technology,2012,36(5):209-214(in Chinese).
[4]肖峻,张婷,张跃,等.基于最大供电能力的配电网规划理念与方法[J].中国电机工程学报,2013,33(10):106-113.Xiao Jun,Zhang Ting,Zhang Yue,et al.TSC-based planning idea and method for distribution networks[J].Proceedings of the CSEE,2013,33(10):106-113(in Chinese).
[5]刘健,徐精求,董海鹏.配电网概率负荷分析及其应用[J].电网技术,2004,28(6):67-75.Liu Jian,Xu Jingqiu,Dong Haipeng.Probabilistic load flow analysis of distribution network and its application[J].Power System Technology,2004,28(6):67-75(in Chinese).
[6]陈光,戴攀,周浩,等.计及入网电动汽车和分布式电源的配电系统重构[J].电网技术,2013,37(1):82-88.Chen Guang,Dai Pan,Zhou Hao,et al.Distribution system reconfiguration considering distributed generators and plug-in electric vehicles[J].Power System Technology,2013,37(1):82-88(in Chinese).
[7]丛鹏伟,唐巍,张露,等.基于机会约束规划考虑DG与负荷多状态的配电网重构[J].电网技术,2013,37(9):2573-2579.Cong Pengwei,Tang Wei,Zhang Lu,et al.Chance-constrained programming based distribution network reconfiguration considering multi-state of distributed generation and load[J].Power System Technology,2013,37(9):2573-2579(in Chinese).
[8]伍言,刘俊勇,刘友波,等.基于负荷组合与光伏电源匹配算法的配电网配置[J].华东电力,2012,40(1):51-55.Wu Yan,Liu Junyong,Liu Youbo,et al.Microgrid configuration based on matching algorithm between load combination and photovoltaic DG[J].East China Electric Power,2012,40(1):51-55(in Chinese).
[9]Hongbo Lian,Xuejin Di,Zhengyi Shen,et al.Detailed power distribution network planning based on the description of load characteristics[C]//2014 China International Conference on Electricity Distribution(CICED).Shenzhen,China:China International Conference on Electricity Distribution(CICED),2014:23-26.
[10]蔡国伟,杜毅,李春山,等.基于支持向量机的中长期日负荷曲线预测[J].电网技术,2006,30(23):56-60.Cai Guowei,Du Yi,Li Chunshan,et al.Middle and long-term daily load curve forecasting based on support vector machine[J].Power System Technology,2006,30(23):56-60(in Chinese).
[11]郭永基.电力系统可靠性原理和应用[M].北京:清华大学出版社,1985:94-163.
[12]杨莳百.电力系统可靠性分析基础及应用[M].北京:水利电力出版社,1986:40-53,144-170,216-225.
[13]Dobakhshari A S,Fotuhi-Firuzabad M.A reliability model of large wind farms for power system adequacy studies[J].IEEE Transactions on Energy Conversion,2009,24(3):792-801.
[14]Muhammad Kumail Haider,Asad Khalid Ismail,Ihsan Ayyub Qazi.Neural information processing,part II[M].Berlin and Heidelberg:Springer Verlag,2012:632-639.
[15]丁明,徐宁舟.基于马尔可夫链的光伏发电系统输出功率短期预测方法[J].电网技术,2011,35(1):152-157.Ding Ming,Xu Ningzhou.A method to forecast short-term output power of photovoltaic generation system based on Markov chain[J].Power System Technology,2011,35(1):152-157(in Chinese).
[16]李欣然,姜学皎,钱军,等.基于用户日负荷曲线的用电行业分类与综合方法[J].电力系统自动化,2010,34(10):56-61.Li Xinran,Jiang Xuejiao,Qian Jun,et al.A classifying and synthesizing method of power consumer industry based on the daily load profile[J].Automation of Electric Power Systems,2010,34(10):56-61(in Chinese).
[17]Tan Pangning,Steinbach Michael,Kumar V.数据挖掘导论[M].范明,范宏建,等译.北京:人民邮电出版社,2011:39-50,327-330.
[18]黄宇腾,侯芳,周勤,等.一种面向需求侧管理的用户负荷形态组合分析方法[J].电力系统保护与控制,2013,41(13):20-25.Huang Yuteng,Hou Fang,Zhou Qin,et al.A new combinational electrical load analysis method for demand side management[J].Power System Protection and Control,2013,41(13):20-25(in Chinese).
[19]罗毅,李昱龙.基于熵权法和灰色关联分析法的输电网规划方案综合决策[J].电网技术,2013,37(1):77-81.Luo Yi,Li Yulong.Comprehensive decision-making of transmission network planning based on entropy weight and grey relational analysis[J].Power System Technology,2013,37(1):77-81(in Chinese).
[20]赵希正.中国电力负荷特性分析与预测[M].北京:中国电力出版社,2002:30-48.
[21]徐玖平,李军.多目标决策的理论与方法[M].北京:清华大学出版社,2005:80-128.
[22]周明,孙树栋.遗传算法原理与应用[M].北京:国防工业出版社,1999:18-31.