{"title":"Genetic programming hyper-heuristic for evolving a maintenance policy for wind farms","authors":"Yikai Ma, Wenjuan Zhang, Juergen Branke","doi":"10.1007/s10732-024-09533-2","DOIUrl":null,"url":null,"abstract":"<p>Reducing the cost of operating and maintaining wind farms is essential for the economic viability of this renewable energy source. This study applies hyper-heuristics to design a maintenance policy that prescribes the best maintenance action in every possible situation. Genetic programming is used to construct a priority function that determines what maintenance activities to conduct and the sequence of maintenance activities if there are not enough resources to do all of them simultaneously. The priority function may take into account the health condition of the target turbine and its components, the characteristics of the corresponding maintenance work, the workload of the maintenance crew, the working condition of the whole wind farm and the possibilities provided by opportunistic maintenance. Empirical results using a simulation model of the wind farm demonstrate that the proposed model can construct maintenance policies that perform well both in training and test scenarios, which shows the practicability of the approach.</p>","PeriodicalId":54810,"journal":{"name":"Journal of Heuristics","volume":"31 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Heuristics","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10732-024-09533-2","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Reducing the cost of operating and maintaining wind farms is essential for the economic viability of this renewable energy source. This study applies hyper-heuristics to design a maintenance policy that prescribes the best maintenance action in every possible situation. Genetic programming is used to construct a priority function that determines what maintenance activities to conduct and the sequence of maintenance activities if there are not enough resources to do all of them simultaneously. The priority function may take into account the health condition of the target turbine and its components, the characteristics of the corresponding maintenance work, the workload of the maintenance crew, the working condition of the whole wind farm and the possibilities provided by opportunistic maintenance. Empirical results using a simulation model of the wind farm demonstrate that the proposed model can construct maintenance policies that perform well both in training and test scenarios, which shows the practicability of the approach.
期刊介绍：
The Journal of Heuristics provides a forum for advancing the state-of-the-art in the theory and practical application of techniques for solving problems approximately that cannot be solved exactly. It fosters the development, understanding, and practical use of heuristic solution techniques for solving business, engineering, and societal problems. It considers the importance of theoretical, empirical, and experimental work related to the development of heuristics.
The journal presents practical applications, theoretical developments, decision analysis models that consider issues of rational decision making with limited information, artificial intelligence-based heuristics applied to a wide variety of problems, learning paradigms, and computational experimentation.
Officially cited as: J Heuristics
Provides a forum for advancing the state-of-the-art in the theory and practical application of techniques for solving problems approximately that cannot be solved exactly.
Fosters the development, understanding, and practical use of heuristic solution techniques for solving business, engineering, and societal problems.
Considers the importance of theoretical, empirical, and experimental work related to the development of heuristics.
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