{"data":{"id":"10.4121/3dde2317-817d-4c57-b844-39eca5411c0d","type":"dois","attributes":{"doi":"10.4121/3dde2317-817d-4c57-b844-39eca5411c0d","prefix":"10.4121","suffix":"3dde2317-817d-4c57-b844-39eca5411c0d","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"van Someren, Christian ","givenName":"Christian ","familyName":"van Someren","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Data and code underlying the publication: How battery energy storage impacts grid congestion – An evaluation of the trade-offs between different battery control strategies"}],"publisher":"4TU.ResearchData","container":{},"publicationYear":2025,"subjects":[{"subject":"Electrical and Electronic Engineering","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"0906"},{"subject":"FOS: Electrical engineering, electronic engineering, information engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"Renewable Energy","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"8505"},{"subject":"Engineering","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"09"},{"subject":"Energy","subjectScheme":"Australian and New Zealand Standard Research Classification (ANZSRC), 2008","classificationCode":"85"},{"subject":"battery energy storage"},{"subject":"battery control"},{"subject":"grid congestion"},{"subject":"grid modelling"}],"contributors":[{"name":"Hanze University Of Applies Sciences-Entrance Centre Of Expertise Energy","nameType":"Organizational","affiliation":[],"contributorType":"Other","nameIdentifiers":[]}],"dates":[{"date":"2025-05-14","dateType":"Issued"}],"language":"en","types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsVersionOf","relatedIdentifier":"10.4121/3dde2317-817d-4c57-b844-39eca5411c0d.v1","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":[],"formats":["*.py, *.csv, *.xlsm, *.xlsx, *.txt"],"version":"1","rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"The goal of this research was to evaluate the effects of different battery control strategies on battery performance and battery grid impacts. This dataset contains the code and data necessary to simulate power flows on a distribution grid in a rural village in the Netherlands, including interactions with household batteries. The model considers current grid topology, current consumer load and generation profiles, and the potential effects of introducing household batteries to the area. All data has 15-minute timesteps; units are in MW unless indicated otherwise.\u003cbr\u003eIncludes the following datasets:Electricity grid model parameters, derived from grid topology data (.xlsx file).Average annual load and generation profiles for consumer connections, derived from measurements (.csv files).EPEX electricity market prices (.csv file).Results and data analysis (.xlsm file).\u003cbr\u003eAlso included is the .py file with the code used to simulate power flows in the grid and battery energy storage systems.\u003cbr\u003eA readme file provides additional details and contact information.\u003cbr\u003eThis work is supported by Hanze University of Applied Sciences and the NO GIMZOS project funded by Topsector Energie - RVO.","descriptionType":"Abstract"}],"geoLocations":[],"fundingReferences":[{"awardTitle":"NetOptimalisatie voor Grootschalige Inpassing Zon- en windstroom Middels Opslag en Software","funderName":"Rijksdienst voor Ondernemend Nederland (RVO) - Topsector 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