{"title":"On the model flexibility of the geographical distributed real-time co-simulation: The example of ENET-RT lab","authors":"","doi":"10.1016/j.segan.2024.101501","DOIUrl":null,"url":null,"abstract":"<div><p>The decarbonization of the energy sector represents a challenge that requires new tools and approaches of analysis. This paper aims to demonstrate the fundamental role that geographical distributed real-time co-simulations (GD-RTDS) can play in this regard. To this end, three different case studies have been analyzed with GD-RTDS, covering a wide range of applications for the energy sector decarbonization: (a) implementation of Renewable Energy Communities for supporting the share increase of Renewable Energy Sources, (b) the integration and management of Onshore Power Supply, and (c) the integration of a forecasting tool for the management of the Electric Vehicle charging. The performed experiments included fully simulated components, together with (power) hardware-in-the-loop and software-in-the-loop elements. These components have been simulated in different laboratory facilities in Italy and Germany, all operating in a synchronized manner under the presented geographically-distributed setup. The results show that the proposed architecture is flexible enough to be used for modeling all the different case studies; moreover, they highlight the significant contribution that the GD-RTDS methodology can give in informing and driving energy transition policies and the fundamental role of power systems to spearhead the complete decarbonization of the energy sector.</p></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":null,"pages":null},"PeriodicalIF":4.8000,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352467724002303/pdfft?md5=9dd4b5a7b5da0a161115cb6052ec2469&pid=1-s2.0-S2352467724002303-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Energy Grids & Networks","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352467724002303","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 decarbonization of the energy sector represents a challenge that requires new tools and approaches of analysis. This paper aims to demonstrate the fundamental role that geographical distributed real-time co-simulations (GD-RTDS) can play in this regard. To this end, three different case studies have been analyzed with GD-RTDS, covering a wide range of applications for the energy sector decarbonization: (a) implementation of Renewable Energy Communities for supporting the share increase of Renewable Energy Sources, (b) the integration and management of Onshore Power Supply, and (c) the integration of a forecasting tool for the management of the Electric Vehicle charging. The performed experiments included fully simulated components, together with (power) hardware-in-the-loop and software-in-the-loop elements. These components have been simulated in different laboratory facilities in Italy and Germany, all operating in a synchronized manner under the presented geographically-distributed setup. The results show that the proposed architecture is flexible enough to be used for modeling all the different case studies; moreover, they highlight the significant contribution that the GD-RTDS methodology can give in informing and driving energy transition policies and the fundamental role of power systems to spearhead the complete decarbonization of the energy sector.
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.