{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,25]],"date-time":"2026-01-25T03:06:28Z","timestamp":1769310388105,"version":"3.49.0"},"reference-count":25,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,5,10]],"date-time":"2021-05-10T00:00:00Z","timestamp":1620604800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this work, an Appliance Scheduling-based Residential Energy Management System (AS-REMS) for reducing electricity cost and avoiding peak demand while keeping user comfort is presented. In AS-REMS, based on the effects of starting times of appliances on user comfort and the user attendance during their operations, appliances are divided into two classes in terms of controllability: MC-controllable (allowed to be scheduled by the Main Controller) and user-controllable (allowed to be scheduled only by a user). Use of all appliances are monitored in the considered home for a while for recording users\u2019 appliance usage preferences and habits on each day of the week. Then, for each MC-controllable appliance, preferred starting times are determined and prioritized according to the recorded user preferences on similar days. When scheduling, assigned priorities of starting times of these appliances are considered for maintaining user comfort, while the tariff rate is considered for reducing electricity cost. Moreover, expected power consumptions of user-controllable appliances corresponding to the recorded user habits and power consumptions of MC-controllable appliances corresponding to the assigned starting times are considered for avoiding peak demand. The corresponding scheduling problem is solved by Brute-Force Closest Pair method. AS-REMS reduces the peak demand levels by 45% and the electricity costs by 39.6%, while provides the highest level of user comfort by 88%. Thus, users\u2019 appliance usage preferences are sustained at a lower cost while their comfort is kept impressively.<\/jats:p>","DOI":"10.3390\/s21093287","type":"journal-article","created":{"date-parts":[[2021,5,10]],"date-time":"2021-05-10T10:49:51Z","timestamp":1620643791000},"page":"3287","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["An Appliance Scheduling System for Residential Energy Management"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2932-0166","authenticated-orcid":false,"given":"Hanife","family":"Apaydin-\u00d6zkan","sequence":"first","affiliation":[{"name":"Department of Electrical and Electronics Engineering, Eskisehir Technical University, Eskisehir 26555, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,10]]},"reference":[{"key":"ref_1","unstructured":"Energy, D. (2021, March 26). Chapter 5: Increasing Efficiency of Building Systems and Technologies September 2015, Available online: https:\/\/www.energy.gov\/sites\/prod\/files\/2017\/03\/f34\/qtr-2015-chapter5.pdf."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"115815","DOI":"10.1016\/j.energy.2019.07.145","article-title":"Integrated energy management system employing pre-emptive priority based load scheduling (PEPLS) approach at residential premises","volume":"186","author":"Murugaperumal","year":"2019","journal-title":"Energy"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Lee, S., and Choi., D.H. (2019). Reinforcement Learning-Based Energy Management of Smart Home with Rooftop Solar Photovoltaic System, Energy Storage System, and Home Appliances. Sensors, 19.","DOI":"10.3390\/s19183937"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.enbuild.2019.01.007","article-title":"Crowdsensing for a sustainable comfort and for energy saving","volume":"186","author":"Cottafava","year":"2019","journal-title":"Energy Build."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Silva, B.N., Khan, M., and Han, K. (2018). Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management. Sensors, 18.","DOI":"10.3390\/s18030685"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Veras, J.M., Silva, I.R.S., Pinheiro, P.R., Rab\u00ealo, R.A.L., Veloso, A.F.S., Borges, F.A.S., and Rodrigues, J.J.P.C. (2018). A Multi-Objective Demand Response Optimization Model for Scheduling Loads in a Home Energy Management System. Sensors, 18.","DOI":"10.3390\/s18103207"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Bui, K.H., Jung, J.J., and Camacho, D. (2018). Consensual Negotiation-Based Decision Making for Connected Appliances in Smart Home Management Systems. Sensors, 18.","DOI":"10.3390\/s18072206"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"105815","DOI":"10.1016\/j.ijepes.2019.105815","article-title":"Home energy management system based on task classification and the resident\u2019s requirements","volume":"118","author":"Samadi","year":"2020","journal-title":"Electr. Power Energy Syst."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2075","DOI":"10.1007\/s42452-020-03885-7","article-title":"A new optimal energy management strategy based on improved multiobjective antlion optimization algorithm: Applications in smart home","volume":"2","author":"Ramezani","year":"2020","journal-title":"SN Appl. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1016\/j.asoc.2019.03.002","article-title":"Binary particle swarm optimisation with quadratic transfer function:A new binary optimisation algortihm for optimal scheduling of appliances in smart homes","volume":"78","author":"Jordehi","year":"2019","journal-title":"Appl. Soft Comput. J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"102048","DOI":"10.1016\/j.scs.2020.102048","article-title":"Flexibility management model of home appliances to support DSO request in smart grids","volume":"55","author":"Lezama","year":"2020","journal-title":"Sustain. Cities Soc."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"106062","DOI":"10.1016\/j.ijepes.2020.106062","article-title":"A novel billing approach for fair and effective demand side management: Appliance level billing(AppLeBill)","volume":"121","author":"Cakmak","year":"2020","journal-title":"Electr. Power Energy Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/j.ijepes.2018.08.019","article-title":"Stochastic interval-based optimal offering model for residential energy management systems by household owners","volume":"105","author":"Gazafroudia","year":"2019","journal-title":"Electr. Power Energy Syst."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"105473","DOI":"10.1016\/j.ijepes.2019.105473","article-title":"Intensive quadratic programming approach for home energy management systems with power utility requirements","volume":"115","author":"Dao","year":"2020","journal-title":"Electr. Power Energy Syst."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"5787","DOI":"10.3390\/en7095787","article-title":"Optimization Models and Methods for Demand-Side Management of Residential Users: A Survey","volume":"7","author":"Barbato","year":"2014","journal-title":"Energies"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4520","DOI":"10.1109\/TSG.2018.2863049","article-title":"Microgrids Energy Management Using Robust Convex Programming","volume":"10","author":"Giraldo","year":"2019","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Ha, L.D., Ploix, S., Zamai, E., and Jacomino, M. (2006, January 16\u201318). Tabu search for the optimization of household energy consumption. Proceedings of the 2006 IEEE International Conference on Information Reuse & Integration, Waikoloa, HI, USA.","DOI":"10.1109\/IRI.2006.252393"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"6062","DOI":"10.1109\/TPWRS.2018.2825356","article-title":"Impacts of Residential Energy Management on Reliability of Distribution Systems Considering a Customer Satisfaction Models","volume":"33","author":"Rastegar","year":"2018","journal-title":"IEEE Trans. Power Syst."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1016\/j.jobe.2018.10.032","article-title":"Building automation system for grid-connected home to optimize energy consumption and electricity bill","volume":"21","author":"Chauhan","year":"2019","journal-title":"J. Build. Eng."},{"key":"ref_20","first-page":"625","article-title":"Smart home energy optimization with incentives compensation from inconvenience for shifting electric appliances","volume":"109","author":"Ni","year":"2019","journal-title":"Electr. Power Energy Syst."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"106477","DOI":"10.1016\/j.epsr.2020.106477","article-title":"Optimal GWCSO-based home appliances scheduling for demand response considering end-users comfort","volume":"187","author":"Waseem","year":"2020","journal-title":"Electr. Power Syst. Res."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1109\/TASE.2020.2986269","article-title":"Robust Optimal Energy Management of a Residential Microgrid Under Uncertainties on Demand and Renewable Power Generation","volume":"18","author":"Hosseini","year":"2021","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.enbuild.2015.03.038","article-title":"A new real time home power management system","volume":"97","author":"Ozkan","year":"2015","journal-title":"Energy Build."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"693","DOI":"10.1016\/j.energy.2016.08.016","article-title":"Appliance based control for Home Power Management Systems","volume":"114","author":"Ozkan","year":"2016","journal-title":"Energy"},{"key":"ref_25","unstructured":"TEDAS (2020). Elektrik Tarifeleri, TEDAS (Turkish Electricity Distribution Company)."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/9\/3287\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:58:43Z","timestamp":1760162323000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/9\/3287"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,10]]},"references-count":25,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["s21093287"],"URL":"https:\/\/doi.org\/10.3390\/s21093287","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,10]]}}}