{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T09:26:14Z","timestamp":1776072374177,"version":"3.50.1"},"reference-count":64,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2018,3,9]],"date-time":"2018-03-09T00:00:00Z","timestamp":1520553600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>The growing demand for electricity is a challenge for the electricity sector as it not only involves the search for new sources of energy, but also the increase of generation capacity of the existing electrical infrastructure and the need to upgrade the existing grid. Therefore, new ways to reduce the consumption of energy are necessary to be implemented. When comparing an average house with an energy efficient house, it is possible to reduce annual energy bills up to 40%. Homeowners and tenants should consider developing an energy conservation plan in their homes. This is both an ecological and economically rational action. With this goal in mind, the need for the energy optimization arises. However, this has to be made by ensuring a fair level of comfort in the household, which in turn spawns a few control challenges. In this paper, the ON\/OFF, proportional-integral-derivative (PID) and Model Predictive Control (MPC) control methods of an air conditioning (AC) of a room are compared. The model of the house of this study has a PV domestic generation. The recorded climacteric data for this case study are for \u00c9vora, a pilot Portuguese city in an ongoing demand response (DR) project. Six Time-of-Use (ToU) electricity rates are studied and compared during a whole week of summer, typically with very high temperatures for this period of the year. The overall weekly expense of each studied tariff option is compared for every control method and in the end the optimal solution is reached.<\/jats:p>","DOI":"10.3390\/app8030408","type":"journal-article","created":{"date-parts":[[2018,3,9]],"date-time":"2018-03-09T12:17:41Z","timestamp":1520597861000},"page":"408","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":93,"title":["Model Predictive Control Home Energy Management and Optimization Strategy with Demand Response"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1244-5624","authenticated-orcid":false,"given":"Radu","family":"Godina","sequence":"first","affiliation":[{"name":"Centre for Mechanical and Aerospace Science and Technologies (C-MAST), University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"}]},{"given":"Eduardo","family":"Rodrigues","sequence":"additional","affiliation":[{"name":"Centre for Mechanical and Aerospace Science and Technologies (C-MAST), University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2217-5293","authenticated-orcid":false,"given":"Edris","family":"Pouresmaeil","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4329-6246","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Matias","sequence":"additional","affiliation":[{"name":"Centre for Mechanical and Aerospace Science and Technologies (C-MAST), University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"},{"name":"The Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), University of Aveiro, Campus Universit\u00e1rio de Santiago, 3810-193 Aveiro, Portugal"}]},{"given":"Jo\u00e3o","family":"Catal\u00e3o","sequence":"additional","affiliation":[{"name":"Centre for Mechanical and Aerospace Science and Technologies (C-MAST), University of Beira Interior, 6201-001 Covilh\u00e3, Portugal"},{"name":"Institute for Systems and Computer Engineering, Technology and Science (INESC TEC) and the Faculty of Engineering of the University of Porto, 4200-465 Porto, Portugal"},{"name":"Instituto de Engenharia de Sistemas e Computadores-Investiga\u00e7\u00e3o e Desenvolvimento (INESC-ID), Instituto Superior T\u00e9cnico, University of Lisbon, 1049-001 Lisbon, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2018,3,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1192","DOI":"10.1016\/j.rser.2017.04.095","article-title":"A review of data-driven building energy consumption prediction studies","volume":"81","author":"Amasyali","year":"2018","journal-title":"Renew. 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