{"title":"Renewables usage maximization in automated distribution networks by coordinated operation of dynamic line rating and dynamic network reconfiguration","authors":"Saeed Behzadi, Amir Bagheri","doi":"10.1016/j.seta.2024.104069","DOIUrl":null,"url":null,"abstract":"<div><div>Incorporation of smart-grid technologies (SGTs) in today’s electric distribution networks (DNs) has enabled distribution network operators (DNOs) to have an on-line supervision over the network equipment for optimal operation. This paper proposes a new approach for optimal scheduling of active DNs aiming at minimizing the curtailment power of wind and photovoltaic (PV) units as renewable energy sources (RESs). This purpose is fulfilled by minimizing the imported power from the transmission network resulting in maximization of renewables usage and minimization of power loss. The conducted approach is based on dynamic line rating (DLR) and dynamic network reconfiguration (DNR) as flexibility options. A convex formulation is employed to incorporate the objective function and constraints into a mixed-integer quadratically-constrained programming (MIQCP) model which is solved by global optimum solvers in GAMS. The proposed model is applied to the IEEE 33-bus system under different case studies, and the simulation results are analyzed. The obtained results indicate that the maximum scheduling of wind and PV units’ is fulfilled with the minimum energy losses. By the aid of DNR and DLR in a coordinated manner, the renewables scheduling is increased by about 64% while the energy loss is reduced by 29% compared to the base case.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"72 ","pages":"Article 104069"},"PeriodicalIF":7.1000,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Energy Technologies and Assessments","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S221313882400465X","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Incorporation of smart-grid technologies (SGTs) in today’s electric distribution networks (DNs) has enabled distribution network operators (DNOs) to have an on-line supervision over the network equipment for optimal operation. This paper proposes a new approach for optimal scheduling of active DNs aiming at minimizing the curtailment power of wind and photovoltaic (PV) units as renewable energy sources (RESs). This purpose is fulfilled by minimizing the imported power from the transmission network resulting in maximization of renewables usage and minimization of power loss. The conducted approach is based on dynamic line rating (DLR) and dynamic network reconfiguration (DNR) as flexibility options. A convex formulation is employed to incorporate the objective function and constraints into a mixed-integer quadratically-constrained programming (MIQCP) model which is solved by global optimum solvers in GAMS. The proposed model is applied to the IEEE 33-bus system under different case studies, and the simulation results are analyzed. The obtained results indicate that the maximum scheduling of wind and PV units’ is fulfilled with the minimum energy losses. By the aid of DNR and DLR in a coordinated manner, the renewables scheduling is increased by about 64% while the energy loss is reduced by 29% compared to the base case.
期刊介绍:
Encouraging a transition to a sustainable energy future is imperative for our world. Technologies that enable this shift in various sectors like transportation, heating, and power systems are of utmost importance. Sustainable Energy Technologies and Assessments welcomes papers focusing on a range of aspects and levels of technological advancements in energy generation and utilization. The aim is to reduce the negative environmental impact associated with energy production and consumption, spanning from laboratory experiments to real-world applications in the commercial sector.