{"title":"Assessment of Methods to Measure Power System Flexibility: A Review","authors":"D. Mouton, Ndamulelo Mararakanye, B. Bekker","doi":"10.1109/UPEC50034.2021.9548205","DOIUrl":null,"url":null,"abstract":"The addition of variable renewable energy (VRE) plants into the generation portfolio means that the power system has higher volatility, uncertainty, and variability. Therefore, there is an increased need for power system flexibility to account for this influx. Generation expansion planning entails strategizing an optimal long-term expansion plan for building new generation plants that satisfies economic and technical constraints. Concerns associated with VRE integration are evident in the case of the Namibian long-term expansion plan. The Namibian generation expansion plan makes use of two traditional adequacy planning techniques, namely loss of load probability (LOLP) and expected unsupplied energy (EUE), which are used for traditional generation plants where flexibility is already provided for. The problem with LOLP and EUE is that the only condition under which demand will not be met is when the demand exceeds the available capacity. The sole use of these metrics for generation expansion planning may be inadequate. Therefore, there is a need for flexibility assessment methods that can assess the flexibility of the Namibian power system to manage high variability. This paper reviews the different flexibility assessment methods available in literature studies and categorises the methods according to levels of computational complexity and data requirements. This paper finds that each level of flexibility assessment methods makes it possible to answer fundamental flexibility questions. Considering the findings, it is important to conduct all three levels of flexibility assessment methods to optimize flexibility.","PeriodicalId":325389,"journal":{"name":"2021 56th International Universities Power Engineering Conference (UPEC)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 56th International Universities Power Engineering Conference (UPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UPEC50034.2021.9548205","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The addition of variable renewable energy (VRE) plants into the generation portfolio means that the power system has higher volatility, uncertainty, and variability. Therefore, there is an increased need for power system flexibility to account for this influx. Generation expansion planning entails strategizing an optimal long-term expansion plan for building new generation plants that satisfies economic and technical constraints. Concerns associated with VRE integration are evident in the case of the Namibian long-term expansion plan. The Namibian generation expansion plan makes use of two traditional adequacy planning techniques, namely loss of load probability (LOLP) and expected unsupplied energy (EUE), which are used for traditional generation plants where flexibility is already provided for. The problem with LOLP and EUE is that the only condition under which demand will not be met is when the demand exceeds the available capacity. The sole use of these metrics for generation expansion planning may be inadequate. Therefore, there is a need for flexibility assessment methods that can assess the flexibility of the Namibian power system to manage high variability. This paper reviews the different flexibility assessment methods available in literature studies and categorises the methods according to levels of computational complexity and data requirements. This paper finds that each level of flexibility assessment methods makes it possible to answer fundamental flexibility questions. Considering the findings, it is important to conduct all three levels of flexibility assessment methods to optimize flexibility.