Open AccessOptimizing household energy planning in smart cities: A multiobjective approach
Author(s) -
Sergio Nesmachnow,
Giovanni Colacurcio,
Diego Gabriel Rossit,
Jamal Toutouh,
Francisco Luna
Publication year - 2020
Publication title -
revista facultad de ingeniería universidad de antioquia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.16
H-Index - 12
eISSN - 2422-2844
pISSN - 0120-6230
DOI - 10.17533/udea.redin.20200587
Subject(s) - computer science , energy consumption , energy planning , energy (signal processing) , order (exchange) , multi objective optimization , evolutionary algorithm , point (geometry) , quality (philosophy) , greedy algorithm , service (business) , operations research , mathematical optimization , artificial intelligence , machine learning , engineering , algorithm , mathematics , renewable energy , business , philosophy , statistics , geometry , finance , epistemology , marketing , electrical engineering
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.