{"title":"A Holistic Approach to the Efficient Estimation of Operational Flexibility From Distributed Resources","authors":"Nikolaos Savvopoulos;Nikos Hatziargyriou;Hannu Laaksonen","doi":"10.1109/OAJPE.2024.3429390","DOIUrl":null,"url":null,"abstract":"The integration of Distributed Energy Resources (DER) like renewable generation into the power system has increased the need to develop effective strategies for procurement of flexibility services from these distribution network connected resources. In order to realize the flexibility potential of DERs to support flexibility needs of the system operators, the aggregated available flexibility at the interconnection point between transmission and distribution system needs to be estimated. This paper presents a novel optimization-based method to estimate the time-dependent flexibility at a primary distribution substation while accounting for the uncertainty of renewable generation. The proposed approach integrates the stochasticity of the flexibility resources using a scenario-based robust optimization and incorporates the intertemporal constraints of DER into the estimation process, ensuring a realistic representation of the flexibility capability over time. The scenarios are derived through sampling from a probability distribution of the renewable energy forecasts. This process utilizes a joint probability distribution and copulas to account for the temporal and spatial correlation among the renewable energy sources of the same region. Based on the joint hourly probability of the different scenarios a robust solution is finally obtained according to the assumed confidence level.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":null,"pages":null},"PeriodicalIF":3.3000,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10599483","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Open Access Journal of Power and Energy","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10599483/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
The integration of Distributed Energy Resources (DER) like renewable generation into the power system has increased the need to develop effective strategies for procurement of flexibility services from these distribution network connected resources. In order to realize the flexibility potential of DERs to support flexibility needs of the system operators, the aggregated available flexibility at the interconnection point between transmission and distribution system needs to be estimated. This paper presents a novel optimization-based method to estimate the time-dependent flexibility at a primary distribution substation while accounting for the uncertainty of renewable generation. The proposed approach integrates the stochasticity of the flexibility resources using a scenario-based robust optimization and incorporates the intertemporal constraints of DER into the estimation process, ensuring a realistic representation of the flexibility capability over time. The scenarios are derived through sampling from a probability distribution of the renewable energy forecasts. This process utilizes a joint probability distribution and copulas to account for the temporal and spatial correlation among the renewable energy sources of the same region. Based on the joint hourly probability of the different scenarios a robust solution is finally obtained according to the assumed confidence level.
可再生能源发电等分布式能源资源(DER)融入电力系统后,更需要制定有效策略,从这些配电网连接资源中获取灵活性服务。为了发挥 DER 的灵活性潜力,支持系统运营商的灵活性需求,需要估算输电和配电系统互联点的总可用灵活性。本文提出了一种基于优化的新方法,用于估算一次配电变电站随时间变化的灵活性,同时考虑到可再生能源发电的不确定性。所提出的方法利用基于情景的稳健优化整合了灵活性资源的随机性,并在估算过程中纳入了 DER 的跨时空约束,从而确保真实地反映出随时间变化的灵活性能力。情景是通过从可再生能源预测的概率分布中抽样得出的。这一过程利用联合概率分布和协和系数来考虑同一地区可再生能源之间的时空相关性。根据不同方案的每小时联合概率,最终按照假定的置信度得出稳健的解决方案。