{"title":"Reactive power management in distribution networks in the presence of distributed generation sources based on information gap decision theory","authors":"Maryam Ramezani, Mahboobeh Etemadizadeh, Hamid Falaghi","doi":"10.1016/j.segan.2024.101470","DOIUrl":null,"url":null,"abstract":"<div><p>The presence of uncertain parameters in power systems has led to many challenges for the designers and operators of these systems. One of these challenges is reactive power management in the presence of distributed renewable generation sources.</p><p>In this article, the management of reactive power in distribution networks in the electricity market and the presence of distributed renewable generation sources, including wind and solar power plants, is performed considering the uncertainties in the network load, power generation of distributed generation sources, and active and reactive power market prices. Furthermore, reactive power cost modeling of reactive power compensation equipment is carried out.</p><p>A hybrid stochastic/robust optimization method is employed to model the uncertainties in the problem. Finally, the efficiency of the method is confirmed by numerical examinations using the IEEE 33-bus distribution network and the GAMS optimization software. Simulation results indicate that in the risk-averse strategy, for a certain increase in cost, the radius of uncertainty in the active and reactive power market prices increases. Also, in this strategy, as β increases, the total cost of network operating increases by 81.72 %, while in a risk-seeking strategy, with the increase of β, the total operating cost of the network decreases by 77.78 %.</p></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":null,"pages":null},"PeriodicalIF":4.8000,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Energy Grids & Networks","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352467724001991","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
The presence of uncertain parameters in power systems has led to many challenges for the designers and operators of these systems. One of these challenges is reactive power management in the presence of distributed renewable generation sources.
In this article, the management of reactive power in distribution networks in the electricity market and the presence of distributed renewable generation sources, including wind and solar power plants, is performed considering the uncertainties in the network load, power generation of distributed generation sources, and active and reactive power market prices. Furthermore, reactive power cost modeling of reactive power compensation equipment is carried out.
A hybrid stochastic/robust optimization method is employed to model the uncertainties in the problem. Finally, the efficiency of the method is confirmed by numerical examinations using the IEEE 33-bus distribution network and the GAMS optimization software. Simulation results indicate that in the risk-averse strategy, for a certain increase in cost, the radius of uncertainty in the active and reactive power market prices increases. Also, in this strategy, as β increases, the total cost of network operating increases by 81.72 %, while in a risk-seeking strategy, with the increase of β, the total operating cost of the network decreases by 77.78 %.
期刊介绍:
Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.