{"title":"Optimal reservoir operation using the improved multi-step-ahead time-varying hedging rule under climate and land-use changes","authors":"S. Thiha, A. Shamseldin, B. Melville","doi":"10.1080/02626667.2023.2196427","DOIUrl":null,"url":null,"abstract":"ABSTRACT This study aims to optimize Yeywa Hydropower Reservoir (YHR) operation using the multi-step-ahead time-varying hedging (TVH) rule under climate change (CC) and land-use change (LUC) to improve summer power generation. The performance of three multi-objective algorithms – the Multi-objective Salp Swarm Algorithm (MOSSA), the Multi-objective Antlion Optimizer (MOALO) and the Non-dominated Sorting Whale Optimization Algorithm (NSOWA) – are compared. MOSSA provides the best solutions with a higher mean hypervolume in a shorter computation time, and it is utilized to optimize the TVH rules for four periods: monthly (TVH-1), quarterly (TVH-3), half-yearly (TVH-6) and yearly (TVH-12). The six-month-ahead TVH-6 rule and the five-month-ahead TVH-6 rule generate the highest summer power for the historical period (2011–2020) and the future period (2020–2059), respectively. The future decadal power generation is expected to be higher than the historical power generation. The future TVH-6 rule is more reliable and it has lower water deficits than the historical YHR operation rule.","PeriodicalId":55042,"journal":{"name":"Hydrological Sciences Journal-Journal Des Sciences Hydrologiques","volume":null,"pages":null},"PeriodicalIF":2.8000,"publicationDate":"2023-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hydrological Sciences Journal-Journal Des Sciences Hydrologiques","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1080/02626667.2023.2196427","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"WATER RESOURCES","Score":null,"Total":0}
引用次数: 1
Abstract
ABSTRACT This study aims to optimize Yeywa Hydropower Reservoir (YHR) operation using the multi-step-ahead time-varying hedging (TVH) rule under climate change (CC) and land-use change (LUC) to improve summer power generation. The performance of three multi-objective algorithms – the Multi-objective Salp Swarm Algorithm (MOSSA), the Multi-objective Antlion Optimizer (MOALO) and the Non-dominated Sorting Whale Optimization Algorithm (NSOWA) – are compared. MOSSA provides the best solutions with a higher mean hypervolume in a shorter computation time, and it is utilized to optimize the TVH rules for four periods: monthly (TVH-1), quarterly (TVH-3), half-yearly (TVH-6) and yearly (TVH-12). The six-month-ahead TVH-6 rule and the five-month-ahead TVH-6 rule generate the highest summer power for the historical period (2011–2020) and the future period (2020–2059), respectively. The future decadal power generation is expected to be higher than the historical power generation. The future TVH-6 rule is more reliable and it has lower water deficits than the historical YHR operation rule.
期刊介绍:
Hydrological Sciences Journal is an international journal focused on hydrology and the relationship of water to atmospheric processes and climate.
Hydrological Sciences Journal is the official journal of the International Association of Hydrological Sciences (IAHS).
Hydrological Sciences Journal aims to provide a forum for original papers and for the exchange of information and views on significant developments in hydrology worldwide on subjects including:
Hydrological cycle and processes
Surface water
Groundwater
Water resource systems and management
Geographical factors
Earth and atmospheric processes
Hydrological extremes and their impact
Hydrological Sciences Journal offers a variety of formats for paper submission, including original articles, scientific notes, discussions, and rapid communications.