

FOLLOWUS
1.College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
2.Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 3GJ, UK
3.School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
4.Power Dispatch and Control Center, Henan Electric Power Company, Zhengzhou 450052, China
[ "Jun-peng ZHAN, E-mail: zhanjunpeng@zju.edu.cn" ]
Chuang-xin GUO, E-mail: guochuangxin@zju.edu.cn
[ "Qing-hua WU, qhwu@liv.ac.uk" ]
[ "Lu-liang ZHANG, ll.zhang02@mail.scut.edu.cn" ]
Received:31 January 2014,
Revised:2014-10-16,
Published:2014-11
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Jun-peng ZHAN, Chuang-xin GUO, Qing-hua WU, et al. Generation maintenance scheduling based on multiple objectives and their relationship analysis[J]. Frontiers of Information Technology & Electronic Engineering, 2014, 15(11): 1035-1047.
Jun-peng ZHAN, Chuang-xin GUO, Qing-hua WU, et al. Generation maintenance scheduling based on multiple objectives and their relationship analysis[J]. Frontiers of Information Technology & Electronic Engineering, 2014, 15(11): 1035-1047. DOI: 10.1631/jzus.C1400030.
研究目的
2
两个发电商的利益最大化之间存在冲突。其一,每个发电商倾向于将其拥有的机组在电价最低的时候进行检修,但每周可以检修的最大容量有限;其二,每个发电商倾向于发更多电,但每天的负荷固定不变。此外,系统可靠性目标与其他目标也构成冲突关系。为此,在电力市场环境下的发电检修计划中,考虑不同发电商的利益最大化,同时考虑电力系统的可靠性最大化。对多个目标同时进行优化,并分析不同目标之间的关系。
创新要点
2
提出一种更适于进化算法求解的发电检修计划模型,提高了求解效率。分析了电力市场环境下发电检修计划中不同目标之间的关系及其成因。
研究方法
2
为使发电检修计划模型更适于被进化算法求解,发电机组的检修变量采用整数编码,在线状态变量和启动状态变量均转化成为由机组出力变量表示的中间变量。对此多目标优化模型,采用带有多发现者的群搜索优化算法(GSOMP)求解。
重要结论
2
仿真分析表明拥有最便宜机组的发电商的利益最大化目标与系统总发电费用目标并不构成冲突。本文提出的系统可靠性目标函数,在高、低负荷时段均有利于保持一定的备用容量。
In a market environment of power systems
each producer pursues its maximal profit while theindependent system operator is in charge of the system reliability and the minimization of the total generationcost when generating the generation maintenance scheduling (GMS). Thus
the GMS is inherently a multi-objectiveoptimization problem as its objectives usually conflict with each other. This paper proposes a multi-objective GMSmodel in a market environment which includes three types of objectives
i.e.
each produceros profit
the systemreliability
and the total generation cost. The GMS model has been solved by the group search optimizer withmultiple producers (GSOMP) on two test systems. The simulation results show that the model is well solved by theGSOMP with a set of evenly distributed Pareto-optimal solutions obtained. The simulation results also illustratethat one produceros profit conflicts with another oneos
that the total generation cost does not conflict with the profitof the producer possessing the cheapest units while the total generation cost conflicts with the other producersoprofits
and that the reliability objective conflicts with the other objectives.
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