Optimizing household energy planning in Smart cities: a multiobjective approach
This article presents the advances in the design and implementation of a recommendation system for planning the use of household appliances, focused on improving energy efficiency from the point of view of both energy companies and end-users. The system proposes using historical information and data...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2021 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/137907 |
| Acceso en línea: | http://hdl.handle.net/11336/137907 |
| Access Level: | acceso abierto |
| Palabra clave: | SMART CITIES HOUSEHOLD ENERGY PLANNING EVOLUTIONARY COMPUTATION MULTIOBJECTIVE OPTIMIZATION MIXED INTEGER PROGRAMMING https://purl.org/becyt/ford/2.11 https://purl.org/becyt/ford/2 |
| Sumario: | This article presents the advances in the design and implementation of a recommendation system for planning the use of household appliances, focused on improving energy efficiency from the point of view of both energy companies and end-users. The system proposes using historical information and data from sensors to define instances of the planning problem considering user preferences, which in turn are proposed to be solved using a multiobjective evolutionary approach, in order to minimize energy consumption and maximize quality of service offered to users. Promising results are reported on realistic instances of the problem, compared with situations where no intelligent energy planning are used (i.e., ?Bussiness as Usual? model) and also with a greedy algorithm developed in the framework of the reference project. The proposed evolutionary approach was able to improve up to 29.0% in energy utilization and up to 65.3% in user preferences over the reference methods. |
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