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浙江大学学报(工学版)
J4  2009, Vol. 43 Issue (11): 2067-2072    DOI: 10.3785/j.issn.1008-973X.2009.11.023
    
Optimization of transmission line maintenance scheduling based on expected value two-level programming
XU Xu-feng1, HUANG Min-xiang1, WANG Ting-ting2
(1. College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China;
2. Shanghai South Power Supply Corporation, Shanghai 200233, China)
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Abstract  

For solving the transmission-line maintenance scheduling optimization problem(TMSOP), the uncertainties of power system load, generator output, line failure rate and maintenance resource were analyzed. An optimization model based on stochastic expected value two-level programming (SEVTP) was established, taking the static safety risk of electrical system into consideration. This model synthetically evaluates the possibility and outcomes of uncertainty, plus the objective function quantifies the risk item in forms of static safety controlling cost. A hybrid intelligent optimization algorithm, combining Monte Carlo method, interior point method, particle swarm optimization (PSO) and tabu list, was presented to solve the Nash balance and Stackelberg-Nash balance of this model. The optimization outcome includes the line maintenance schedule and the arrangement for the maintenance resources, as well as the least-risk-operation style for the power system during the maintenance. Finally, the feasibility of this model and the solution was verified by an IEEE-RTS example．

Published: 01 November 2009
CLC:  TM 715  
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Cite this article:

HU Xu-Feng, HUANG Min-Xiang, WANG Ting-Ting. Optimization of transmission line maintenance scheduling based on expected value two-level programming. J4, 2009, 43(11): 2067-2072.

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http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2009.11.023     OR     http://www.zjujournals.com/eng/Y2009/V43/I11/2067


基于期望值二层规划的输电线路检修计划优化

针对输电线路检修计划优化问题（TMSOP）,考虑负荷、发电机出力、线路故障率及检修资源的不确定性,建立基于期望值二层规划的优化模型.模型计及系统静态安全风险,对不安全现象的概率和后果进行综合评估,并将风险指标用静态安全控制成本来量化计入目标函数中.利用蒙特卡罗方法、内点法、粒子群算法和禁忌表等混合智能优化算法来求解模型的Nash均衡和Stackelberg-Nash均衡.优化结果不仅确定了线路检修计划和检修资源安排,还明确了检修期间输电网风险最低的运行方式.最后通过IEEE-RTS的算例验证了模型和算法的可行性.

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