{"title":"风力-光伏-水力发电系统调度的随机多标准决策","authors":"Weifeng Liu, Yu Zhang, Xigang Xing, Xuning Guo, Rui Ma, Jieyu Li, Yunling Li","doi":"10.2166/wcc.2024.531","DOIUrl":null,"url":null,"abstract":"\n The decision-making process of wind–photovoltaic–hydropower systems involves knowledge from many fields. Influenced by the knowledge level of the decision-maker and the attribute information of the scheme set, there exists a certain uncertainty in the indicator weights. In view of this, this paper proposes a stochastic multi-criteria decision-making framework for scheduling of wind–photovoltaic–hydropower systems, which overcomes the difficulty of uncertainty in indicator weights or even completely unknown information about indicator weights at the time of decision-making. The Stochastic Multi-criteria Acceptability Analysis (SMAA) theory and the VIKOR model are introduced, and the proposed SMAA–VIKOR model makes the indicator weight space explicit. The study shows that the proposed SMAA–VIKOR model can overcome the obstacle of decision-makers’ lack of information on indicator weights. The ranking acceptability indicators calculated by the model show a more obvious trend of advantages and disadvantages, which gives full confidence to the decision-making group to formulate a plan to be implemented. It breaks through the bottleneck of group decision-making, which is difficult to make effective decisions due to the condition of incomplete information, and enriches the library of stochastic multi-criteria decision-making methods for the scientific formulation of scheduling schemes of wind–photovoltaic–hydropower systems under uncertainty conditions.","PeriodicalId":506949,"journal":{"name":"Journal of Water and Climate Change","volume":"89 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stochastic multi-criteria decision-making for scheduling of wind–photovoltaic–hydropower systems\",\"authors\":\"Weifeng Liu, Yu Zhang, Xigang Xing, Xuning Guo, Rui Ma, Jieyu Li, Yunling Li\",\"doi\":\"10.2166/wcc.2024.531\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n The decision-making process of wind–photovoltaic–hydropower systems involves knowledge from many fields. Influenced by the knowledge level of the decision-maker and the attribute information of the scheme set, there exists a certain uncertainty in the indicator weights. In view of this, this paper proposes a stochastic multi-criteria decision-making framework for scheduling of wind–photovoltaic–hydropower systems, which overcomes the difficulty of uncertainty in indicator weights or even completely unknown information about indicator weights at the time of decision-making. The Stochastic Multi-criteria Acceptability Analysis (SMAA) theory and the VIKOR model are introduced, and the proposed SMAA–VIKOR model makes the indicator weight space explicit. The study shows that the proposed SMAA–VIKOR model can overcome the obstacle of decision-makers’ lack of information on indicator weights. The ranking acceptability indicators calculated by the model show a more obvious trend of advantages and disadvantages, which gives full confidence to the decision-making group to formulate a plan to be implemented. It breaks through the bottleneck of group decision-making, which is difficult to make effective decisions due to the condition of incomplete information, and enriches the library of stochastic multi-criteria decision-making methods for the scientific formulation of scheduling schemes of wind–photovoltaic–hydropower systems under uncertainty conditions.\",\"PeriodicalId\":506949,\"journal\":{\"name\":\"Journal of Water and Climate Change\",\"volume\":\"89 3\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Water and Climate Change\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2166/wcc.2024.531\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Water and Climate Change","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/wcc.2024.531","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Stochastic multi-criteria decision-making for scheduling of wind–photovoltaic–hydropower systems
The decision-making process of wind–photovoltaic–hydropower systems involves knowledge from many fields. Influenced by the knowledge level of the decision-maker and the attribute information of the scheme set, there exists a certain uncertainty in the indicator weights. In view of this, this paper proposes a stochastic multi-criteria decision-making framework for scheduling of wind–photovoltaic–hydropower systems, which overcomes the difficulty of uncertainty in indicator weights or even completely unknown information about indicator weights at the time of decision-making. The Stochastic Multi-criteria Acceptability Analysis (SMAA) theory and the VIKOR model are introduced, and the proposed SMAA–VIKOR model makes the indicator weight space explicit. The study shows that the proposed SMAA–VIKOR model can overcome the obstacle of decision-makers’ lack of information on indicator weights. The ranking acceptability indicators calculated by the model show a more obvious trend of advantages and disadvantages, which gives full confidence to the decision-making group to formulate a plan to be implemented. It breaks through the bottleneck of group decision-making, which is difficult to make effective decisions due to the condition of incomplete information, and enriches the library of stochastic multi-criteria decision-making methods for the scientific formulation of scheduling schemes of wind–photovoltaic–hydropower systems under uncertainty conditions.