Methodology to Build Demand Profiles for the Simulation of Renewable Energy Communities
| dc.centro | Escuela de Ingenierías Industriales | es_ES |
| dc.contributor.author | Comitre-Bueno, Alejandro | |
| dc.contributor.author | Puche-Pascual, Sebastián | |
| dc.contributor.author | Martín-Rivas, Sebastián | |
| dc.date.accessioned | 2025-12-17T10:30:34Z | |
| dc.date.available | 2025-12-17T10:30:34Z | |
| dc.date.issued | 2025-01-20 | |
| dc.departamento | Ingeniería Eléctrica | es_ES |
| dc.description | https://conferences.ieeeauthorcenter.ieee.org/author-ethics/guidelines-and-policies/post-publication-policies/#accepted (24 meses de embargo) | es_ES |
| dc.description.abstract | In order to answer the questions of sizing and operating renewable energy communities, it is necessary to have the appropriate data. Among the main data we have renewable generation, usually with abundant data available, and demand. We have two main difficulties with demand: on the one hand, low availability of public data and on the other hand, that the demand profiles adequately represent the conditions of greatest interest for sizing and operating the community. For this reason, a method is proposed here that allows the construction of the demand curves of interest to answer the questions of sizing and operation. The method allows the use of the available demand curves and from them the construction of new ones taking into account three main factors: i) overlap of the demand curve with the renewable generation curve (self-consumption), ii) correlation of the demand curve with a reference demand curve (average curve) and iii) a scale factor that relates the demand curve with the size of the community, and that allows the inclusion of information on the type of housing and the climatic zone. To illustrate the method, it is applied to a set of 55 demand curves (annual hourly profiles of 8760 values/curve), photovoltaic generation and three types of communities. | es_ES |
| dc.identifier.doi | 10.1109/IC2SPM62723.2024.10841344 | |
| dc.identifier.uri | https://hdl.handle.net/10630/41160 | |
| dc.language.iso | eng | es_ES |
| dc.publisher | IEEE | es_ES |
| dc.relation.eventdate | 2024 International Conference on Smart Systems and Power Management (IC2SPM) | es_ES |
| dc.relation.eventplace | Beirut, Lebanon | es_ES |
| dc.relation.eventtitle | 2024 International Conference on Smart Systems and Power Management (IC2SPM) | es_ES |
| dc.relation.projectID | /grantAgreement/Gobierno de España/Proyectos estratégicos orientados a la transición ecológica y a la transición digital, del Plan Estatal de Investigación Científica, Técnica y de Innovación para el período 2021-2023, en el marco del Plan de Recuperación, Transformación y Resiliencia/TED2021-132339B-C42/idrECO | es_ES |
| dc.rights | Atribución 4.0 Internacional | * |
| dc.rights.accessRights | embargoed access | es_ES |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
| dc.subject | Recursos energéticos renovables | es_ES |
| dc.subject | Energía fotovoltaica | es_ES |
| dc.subject.other | Photovoltaic generation | es_ES |
| dc.subject.other | Renewable energy sources | es_ES |
| dc.subject.other | Correlation in time domain | es_ES |
| dc.subject.other | Sizing and operation | es_ES |
| dc.subject.other | Renewable energy communities | es_ES |
| dc.title | Methodology to Build Demand Profiles for the Simulation of Renewable Energy Communities | es_ES |
| dc.type | conference output | es_ES |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 2d263ae0-a497-4fbf-ba6a-f82ba1dae2dc | |
| relation.isAuthorOfPublication.latestForDiscovery | 2d263ae0-a497-4fbf-ba6a-f82ba1dae2dc |
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