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作 者:Junyi Yang Jiangmin Bao Yuhan Hou Han Wu Qiang Li Yue Yuan
机构地区:[1]Hohai University,Nanjing 211100,China [2]State Grid Jiangsu Electric Power Co.,Ltd.,Suzhou Power Supply Branch,Suzhou 215004,China [3]Nanjing Institute of Technology,Nanjing 211167,China [4]Electric Power Research Institute of State Grid Jiangsu Electric Power Co.Ltd.,Nanjing 211103,China [5]IEEE [6]CSEE
出 处:《CSEE Journal of Power and Energy Systems》2024年第3期1011-1025,共15页中国电机工程学会电力与能源系统学报(英文)
基 金:supported by the High-level Talents Introduction&Research Start-up Fund Program of Nanjing Institute of Technology(YKJ202134).
摘 要:Dependence of distributed generation(DG)outputs and load plays an essential role in renewable energy accommodation.This paper presents a novel DG hosting capacity(DGHC)evaluation method for distribution networks considering highdimensional dependence relations among solar radiation,wind speed,and various load types(i.e.,commercial,residential,and industrial).First,an advanced dependence modeling method called regular vine(R-vine)is applied to capture the complex dependence structure of solar radiation,wind speed,commercial loads,industrial loads,and residential loads.Then,a chanceconstrained DGHC evaluation model is employed to figure out maximum hosting capacity of each DG and its optimal allocation plan with different operational risks.Finally,a Benders decomposition algorithm is also employed to reduce computational burden.The proposed approaches are validated using a set of historical data from China.Results show dependence among different DGs and loads has significant impact on hosting capacity.Results also suggest using the R-vine model to capture dependence among distributed energy resources(DERs)and load.This finding provides useful advice for distribution networks in installing renewable energy generations.
关 键 词:Benders decomposition correlation DG hosting capacity regular vine
分 类 号:TM614[电气工程—电力系统及自动化]
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