摘要
This study proposes a method for analyzing the security distance of an Active Distribution Network(ADN)by incorporating the demand response of an Energy Hub(EH).Taking into account the impact of stochastic wind-solar power and flexible loads on the EH,an interactive power model was developed to represent the EH’s operation under these influences.Additionally,an ADN security distance model,integrating an EH with flexible loads,was constructed to evaluate the effect of flexible load variations on the ADN’s security distance.By considering scenarios such as air conditioning(AC)load reduction and base station(BS)load transfer,the security distances of phases A,B,and C increased by 17.1%,17.2%,and 17.7%,respectively.Furthermore,a multi-objective optimal power flow model was formulated and solved using the Forward-Backward Power Flow Algorithm,the NSGA-II multi-objective optimization algo-rithm,and the maximum satisfaction method.The simulation results of the IEEE33 node system example demonstrate that after opti-mization,the total energy cost for one day is reduced by 0.026%,and the total security distance limit of the ADN’s three phases is improved by 0.1 MVA.This method effectively enhances the security distance,facilitates BS load transfer and AC load reduction,and contributes to the energy-saving,economical,and safe operation of the power system.
基金
supported in part by the National Nat-ural Science Foundation of China(No.51977012,No.52307080).
作者简介
Corresponding author:Rui Ma received a bachelor’s degree from Changsha University of Electric Power,Changsha,in 1994,a master’s degree from Hunan University,Changsha,in 1999,and a Ph.D degree from North China Electric Power University,Beijing,in 2006.Currently he is working as Professor in Changsha University of Science&Technology,Changsha.His research interests includes the area of power system security analysis,renewable energy accessing,electricity market and low-carbon electricity.E-mail addresses:marui818@126.com;Corresponding author:Qi Zhou received a bachelor’s and master’s degrees from University of Science&Technol-ogy,Changsha,China,in 2019 and 2022.His research interest includes power system analysis and control,610566936@qq.com;Corresponding author:Shengyang Liu received a bachelor’s degree from Hunan University of Humanities,Science and Technology,Loudi,China,in 2022,and is currently pursuing the master’s degree at Changsha University of Science&Technology.His research interest includes power system analysis and control.,liushengyang2024@126.com;Corresponding author:Qin Yan received a bachelor’s degree from Wuhan University,Wuhan,in 2010,a master’s degree from Texas A&M University,College Station,in 2012,and a Ph.D.degree from Texas A&M University,College Station,USA,in 2018.She became an Assistant Professor at Changsha University of Science&Technology in 2021.Her research interests include plug-in electric vehicles,smart grid,distributed energy resources,and integrated energy system opti-mization,qin.yan@csust.edu.cn;Corresponding author:Mo Shi received a bachelor’s degree from North China Electric Power University,Beijing,in 2013,a master’s degree from North China Electric Power University,Beijing,in 2016.Currently he is working at the Electric Power Scientific Research Institute of Guangdong Power Grid Co.Her research interest is intelli-gent power distribution technology,6stonestone@sina.cn。
