{"title":"基于多目标优化的海上风电场预防性维修路线与调度*","authors":"Jia Cai, Yajie Liu, Tao Zhang","doi":"10.1109/ICCSIE55183.2023.10175291","DOIUrl":null,"url":null,"abstract":"Maintenance expenses and production interruption related to offshore wind farms may result in financial losses and decrease power system reliability. A mathematical model for preventive maintenance scheduling and routing of the maintenance fleets for offshore wind farms based on multiple-objective is proposed. It takes into account the multi-stakeholder interests in depth as well as the optimal planning requirements on multiple objectives such as economic costs and power system reliability. First, multiple decision variables involving task assignment, maintenance scheduling and routing for each vessel are presented and contrasted with the vehicle routing problems with time windows. Secondly, the reliability index based on maintenance losses is introduced, with the goal of enhancing the power system’s capacity to handle unexpected peak loads. Along with the multi-objective optimal planning model, function models describing economic costs and power system reliability are constructed. Thirdly, the non-dominated sorting genetic algorithm II is adopted to capture fair compromise solutions to balance different decision preferences. A computational study verifies the feasibility of the mathematical model, and the solutions to the multi-objective problem are thoroughly analyzed.","PeriodicalId":391372,"journal":{"name":"2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Preventive maintenance routing and scheduling for offshore wind farms based on multi-objective optimization*\",\"authors\":\"Jia Cai, Yajie Liu, Tao Zhang\",\"doi\":\"10.1109/ICCSIE55183.2023.10175291\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Maintenance expenses and production interruption related to offshore wind farms may result in financial losses and decrease power system reliability. A mathematical model for preventive maintenance scheduling and routing of the maintenance fleets for offshore wind farms based on multiple-objective is proposed. It takes into account the multi-stakeholder interests in depth as well as the optimal planning requirements on multiple objectives such as economic costs and power system reliability. First, multiple decision variables involving task assignment, maintenance scheduling and routing for each vessel are presented and contrasted with the vehicle routing problems with time windows. Secondly, the reliability index based on maintenance losses is introduced, with the goal of enhancing the power system’s capacity to handle unexpected peak loads. Along with the multi-objective optimal planning model, function models describing economic costs and power system reliability are constructed. Thirdly, the non-dominated sorting genetic algorithm II is adopted to capture fair compromise solutions to balance different decision preferences. A computational study verifies the feasibility of the mathematical model, and the solutions to the multi-objective problem are thoroughly analyzed.\",\"PeriodicalId\":391372,\"journal\":{\"name\":\"2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSIE55183.2023.10175291\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 First International Conference on Cyber-Energy Systems and Intelligent Energy (ICCSIE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSIE55183.2023.10175291","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Preventive maintenance routing and scheduling for offshore wind farms based on multi-objective optimization*
Maintenance expenses and production interruption related to offshore wind farms may result in financial losses and decrease power system reliability. A mathematical model for preventive maintenance scheduling and routing of the maintenance fleets for offshore wind farms based on multiple-objective is proposed. It takes into account the multi-stakeholder interests in depth as well as the optimal planning requirements on multiple objectives such as economic costs and power system reliability. First, multiple decision variables involving task assignment, maintenance scheduling and routing for each vessel are presented and contrasted with the vehicle routing problems with time windows. Secondly, the reliability index based on maintenance losses is introduced, with the goal of enhancing the power system’s capacity to handle unexpected peak loads. Along with the multi-objective optimal planning model, function models describing economic costs and power system reliability are constructed. Thirdly, the non-dominated sorting genetic algorithm II is adopted to capture fair compromise solutions to balance different decision preferences. A computational study verifies the feasibility of the mathematical model, and the solutions to the multi-objective problem are thoroughly analyzed.