{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,10]],"date-time":"2026-05-10T06:34:47Z","timestamp":1778394887364,"version":"3.51.4"},"reference-count":144,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,4,1]],"date-time":"2025-04-01T00:00:00Z","timestamp":1743465600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["UIDB\/00760\/2020"],"award-info":[{"award-number":["UIDB\/00760\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007157","name":"Instituto Polit\u00e9cnico do Porto","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100007157","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Process Integr Optim Sustain"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>This paper presents a systematic literature review of energy management models for smart homes, conducted between 2018 and 2024, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol. Smart homes leverage advanced technologies to optimize energy consumption and enhance sustainability through interconnected devices and sophisticated algorithms. The review covers energy optimization techniques, predictive management, renewable energy integration, demand-side management, user behavior, and data protection. It examines the effectiveness of various models, identifies key tends, and addresses challenges such as integrating diverse energy sources, managing consumption variability, and ensuring data privacy. The findings reveal significant advancements in energy optimization, home automation, and grid stability. However, areas like demand-side management and artificial intelligence (AI) and machine learning (ML) driven algorithms for energy management remain underexplored and require further research. Recommendations are provided to improve energy management systems and guide future research for increased efficiency and sustainability in smart homes. This review offers valuable insights into the current state of energy management models and lays the groundwork for future developments in smart home energy systems.<\/jats:p>","DOI":"10.1007\/s41660-025-00506-x","type":"journal-article","created":{"date-parts":[[2025,4,3]],"date-time":"2025-04-03T16:09:50Z","timestamp":1743696590000},"page":"1169-1198","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Future of Energy Management Models in Smart Homes: A Systematic Literature Review of Research Trends, Gaps, and Future Directions"],"prefix":"10.1007","volume":"9","author":[{"given":"Ubaid ur","family":"Rehman","sequence":"first","affiliation":[]},{"given":"Pedro","family":"Faria","sequence":"additional","affiliation":[]},{"given":"Luis","family":"Gomes","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4560-9544","authenticated-orcid":false,"given":"Zita","family":"Vale","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,4,1]]},"reference":[{"key":"506_CR1","doi-asserted-by":"publisher","unstructured":"Abishu HN, Seid AM, M\u00e1rquez-S\u00e1nchez S, Fernandez JH, Corchado JM, Erbad A (2024) Multi-Agent DRL-based multi-objective demand response optimization for real-time energy management in smart homes. In\u00a02024 International wireless communications and mobile computing (IWCMC)\u00a0(pp. 1210-1217). IEEE, Ayia Napa, Cyprus, 27-31 May 2024. https:\/\/doi.org\/10.1109\/IWCMC61514.2024.10592515","DOI":"10.1109\/IWCMC61514.2024.10592515"},{"key":"506_CR2","doi-asserted-by":"publisher","first-page":"1474","DOI":"10.1049\/iet-rpg.2018.6022","volume":"13","author":"C Abreu","year":"2019","unstructured":"Abreu C, Soares I, Oliveira L, Rua D, Machado P, Carvalho L, Pe\u00e7as Lopes JA (2019) Application of genetic algorithms and the cross-entropy method in practical home energy management systems. IET Renew Power Gener 13:1474\u20131483. https:\/\/doi.org\/10.1049\/iet-rpg.2018.6022","journal-title":"IET Renew Power Gener"},{"key":"506_CR3","doi-asserted-by":"publisher","first-page":"568","DOI":"10.1016\/j.egyr.2024.06.036","volume":"12","author":"F Ahmed","year":"2024","unstructured":"Ahmed F, Arshad A, Rehman AU, Alqahtani MH, Mahmoud K (2024) Effective incentive based demand response with voltage support capability via reinforcement learning based multi-agent framework. Energy Rep 12:568\u2013578. https:\/\/doi.org\/10.1016\/j.egyr.2024.06.036","journal-title":"Energy Rep"},{"key":"506_CR4","doi-asserted-by":"publisher","first-page":"118369","DOI":"10.1016\/j.enconman.2024.118369","volume":"307","author":"A Ajitha","year":"2024","unstructured":"Ajitha A, Akhilesh G (2024) Tarun Rajkumar, Sudha Radhika, Sanket Goel, Design and implementation of smart home energy management system for Indian residential sector. Energy Convers Manage 307:118369. https:\/\/doi.org\/10.1016\/j.enconman.2024.118369","journal-title":"Energy Convers Manage"},{"key":"506_CR5","doi-asserted-by":"publisher","first-page":"43155","DOI":"10.1109\/ACCESS.2024.3375771","volume":"12","author":"J Aldahmashi","year":"2024","unstructured":"Aldahmashi J, Ma X (2024) Real-time energy management in smart homes through deep reinforcement learning. IEEE Access 12:43155\u201343172. https:\/\/doi.org\/10.1109\/ACCESS.2024.3375771","journal-title":"IEEE Access"},{"key":"506_CR6","doi-asserted-by":"publisher","first-page":"104609","DOI":"10.1016\/j.est.2022.104609","volume":"50","author":"AO Ali","year":"2022","unstructured":"Ali AO, Elmarghany MR, Abdelsalam MM, Sabry MN, Hamed AM (2022) Closed-loop home energy management system with renewable energy sources in a smart grid: a comprehensive review. J Energy Storage 50:104609. https:\/\/doi.org\/10.1016\/j.est.2022.104609","journal-title":"J Energy Storage"},{"key":"506_CR7","doi-asserted-by":"publisher","first-page":"105410","DOI":"10.1016\/j.csite.2024.105410","volume":"64","author":"AO Ali","year":"2024","unstructured":"Ali AO, Elmarghany MR, Hamed AM, Sabry MN, Abdelsalam MM (2024) Optimized smart home energy management system: reducing grid consumption and costs through real-time pricing and hybrid architecture. Case Stud Therm Eng 64:105410. https:\/\/doi.org\/10.1016\/j.csite.2024.105410","journal-title":"Case Stud Therm Eng"},{"key":"506_CR8","doi-asserted-by":"publisher","first-page":"36417","DOI":"10.1109\/ACCESS.2021.3061995","volume":"9","author":"FE Aliabadi","year":"2021","unstructured":"Aliabadi FE, Agbossou K, Kelouwani S, Henao N, Hosseini SS (2021) Coordination of smart home energy management systems in neighborhood areas: a systematic review. IEEE Access 9:36417\u201336443. https:\/\/doi.org\/10.1109\/ACCESS.2021.3061995","journal-title":"IEEE Access"},{"key":"506_CR9","doi-asserted-by":"publisher","first-page":"e12404","DOI":"10.1002\/2050-7038.12404","volume":"30","author":"H Alsalloum","year":"2020","unstructured":"Alsalloum H, Merghem-Boulahia L, Rahim R (2020) A systematical analysis on the dynamic pricing strategies and optimization methods for energy trading in smart grids. Int Trans Electr Energ Syst 30:e12404. https:\/\/doi.org\/10.1002\/2050-7038.12404","journal-title":"Int Trans Electr Energ Syst"},{"key":"506_CR10","doi-asserted-by":"publisher","first-page":"93760","DOI":"10.1109\/ACCESS.2022.3202649","volume":"10","author":"A Al-Sorour","year":"2022","unstructured":"Al-Sorour A, Fazeli M, Monfared M, Fahmy A, Searle JR, Lewis RP (2022) Enhancing PV self-consumption within an energy community using MILP-based P2P trading. IEEE Access 10:93760\u201393772. https:\/\/doi.org\/10.1109\/ACCESS.2022.3202649","journal-title":"IEEE Access"},{"issue":"21","key":"506_CR11","doi-asserted-by":"publisher","first-page":"8235","DOI":"10.3390\/en15218235","volume":"15","author":"A Amer","year":"2022","unstructured":"Amer A, Shaban K, Massoud A (2022) Demand response in HEMSs using DRL and the impact of its various configurations and environmental changes. Energies 15(21):8235. https:\/\/doi.org\/10.3390\/en15218235","journal-title":"Energies"},{"issue":"1","key":"506_CR12","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1109\/TSG.2022.3198401","volume":"14","author":"AA Amer","year":"2023","unstructured":"Amer AA, Shaban K, Massoud AM (2023) DRL-HEMS: deep reinforcement learning agent for demand response in home energy management systems considering customers and operators perspectives. IEEE Trans Smart Grid 14(1):239\u2013250. https:\/\/doi.org\/10.1109\/TSG.2022.3198401","journal-title":"IEEE Trans Smart Grid"},{"issue":"4","key":"506_CR13","doi-asserted-by":"publisher","first-page":"989","DOI":"10.1007\/s41660-022-00255-1","volume":"6","author":"Archana","year":"2022","unstructured":"Archana (2022) Modelling barriers for smart grid technology acceptance in India. Process Integr Optim Sustain 6(4):989\u20131010. https:\/\/doi.org\/10.1007\/s41660-022-00255-1","journal-title":"Process Integr Optim Sustain"},{"issue":"4","key":"506_CR14","doi-asserted-by":"publisher","first-page":"959","DOI":"10.1016\/j.joi.2017.08.007","volume":"11","author":"M Aria","year":"2017","unstructured":"Aria M, Cuccurullo C (2017) bibliometrix: an R-tool for comprehensive science mapping analysis. J Informet 11(4):959\u2013975. https:\/\/doi.org\/10.1016\/j.joi.2017.08.007. (This citation refers to the R package)","journal-title":"J Informet"},{"key":"506_CR15","unstructured":"Association for Computing Machinery (n.d.) ACM digital library. Retrieved from https:\/\/dl.acm.org"},{"key":"506_CR16","doi-asserted-by":"publisher","first-page":"100700","DOI":"10.1016\/j.prime.2024.100700","volume":"9","author":"A Azimi","year":"2024","unstructured":"Azimi A, Akbari O (2024) A deep reinforcement learning-based method for dynamic quality of service aware energy and occupant comfort management in intelligent buildings. e-Prime-Adv Electric Eng Electronics Energy 9:100700. https:\/\/doi.org\/10.1016\/j.prime.2024.100700","journal-title":"e-Prime-Adv Electric Eng Electronics Energy"},{"key":"506_CR17","doi-asserted-by":"publisher","unstructured":"Babu GR, Chintalapati PV, Sree PK, Tayaru GRLM, Raju P, Kumar KS (2023) An advanced artificial intelligence-driven smart home towards ontology-based energy efficiency management system. In\u00a0international conference on innovations in data analytics (pp. 325-333). Singapore: Springer Nature Singapore.. https:\/\/doi.org\/10.1007\/978-981-97-3466-5_24","DOI":"10.1007\/978-981-97-3466-5_24"},{"key":"506_CR18","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1016\/j.matpr.2021.04.029","volume":"47","author":"R Balakrishnan","year":"2021","unstructured":"Balakrishnan R, Geetha V (2021) Review on home energy management system. Mater Today: Proceed 47:144\u2013150. https:\/\/doi.org\/10.1016\/j.matpr.2021.04.029","journal-title":"Mater Today: Proceed"},{"key":"506_CR19","doi-asserted-by":"publisher","first-page":"3695","DOI":"10.1016\/j.egyr.2024.03.031","volume":"11","author":"S Balavignesh","year":"2024","unstructured":"Balavignesh S, Kumar C, Sripriya R, Senjyu T (2024) An enhanced coati optimization algorithm for optimizing energy management in smart grids for home appliances. Energy Rep 11:3695\u20133720. https:\/\/doi.org\/10.1016\/j.egyr.2024.03.031","journal-title":"Energy Rep"},{"key":"506_CR20","unstructured":"Bibliometrix and Biblioshiny tool in R software (n.d.) Online Link: https:\/\/www.bibliometrix\/.org\/home\/"},{"key":"506_CR21","doi-asserted-by":"publisher","unstructured":"B\u00fcy\u00fck M, Av\u015far E, \u0130nci M (2022) Overview of smart home concepts through energy management systems, numerical research, and future perspective. Energy Sourc Part A: Recov Util Environ Effects 1\u201326. https:\/\/doi.org\/10.1080\/15567036.2021.2024924","DOI":"10.1080\/15567036.2021.2024924"},{"key":"506_CR22","doi-asserted-by":"publisher","first-page":"145264","DOI":"10.1109\/ACCESS.2023.3346324","volume":"11","author":"W Cai","year":"2023","unstructured":"Cai W, Sawant S, Reinhardt D, Rastegarpour S, Gros S (2023) A learning-based model predictive control strategy for home energy management systems. IEEE Access 11:145264\u2013145280. https:\/\/doi.org\/10.1109\/ACCESS.2023.3346324","journal-title":"IEEE Access"},{"key":"506_CR23","doi-asserted-by":"publisher","first-page":"129246","DOI":"10.1016\/j.jclepro.2021.129246","volume":"326","author":"Z Cao","year":"2021","unstructured":"Cao Z, Han X, Lyons W, O\u2019Rourke F (2021) Energy management optimisation using a combined long short-term memory recurrent neural network \u2013 particle swarm optimisation model. J Clean Prod 326:129246. https:\/\/doi.org\/10.1016\/j.jclepro.2021.129246","journal-title":"J Clean Prod"},{"key":"506_CR24","doi-asserted-by":"publisher","first-page":"1545","DOI":"10.1007\/s41660-024-00445-z","volume":"8","author":"J Chen","year":"2024","unstructured":"Chen J (2024) Optimal allocation of distributed generation using lightning search algorithm for profit maximization in a distribution system. Process Integr Optim Sustain 8:1545\u20131567. https:\/\/doi.org\/10.1007\/s41660-024-00445-z","journal-title":"Process Integr Optim Sustain"},{"key":"506_CR25","doi-asserted-by":"publisher","first-page":"111066","DOI":"10.1016\/j.rser.2021.111066","volume":"145","author":"C-F Chen","year":"2021","unstructured":"Chen C-F, Nelson H, Xiaojing Xu, Bonilla G, Jones N (2021) Beyond technology adoption: examining home energy management systems, energy burdens and climate change perceptions during COVID-19 pandemic. Renew Sustain Energy Rev 145:111066. https:\/\/doi.org\/10.1016\/j.rser.2021.111066","journal-title":"Renew Sustain Energy Rev"},{"key":"506_CR26","doi-asserted-by":"publisher","first-page":"114458","DOI":"10.1016\/j.enbuild.2024.114458","volume":"318","author":"WA Chen","year":"2024","unstructured":"Chen WA, Chen CF, Tomasik S (2024) Investigating intentions and barriers in adopting decentralized home energy management systems: a justice dimension of demand flexibility. Energy Build 318:114458. https:\/\/doi.org\/10.1016\/j.enbuild.2024.114458","journal-title":"Energy Build"},{"key":"506_CR27","doi-asserted-by":"publisher","first-page":"108617","DOI":"10.1016\/j.epsr.2022.108617","volume":"212","author":"Y Chu","year":"2022","unstructured":"Chu Y, Wei Z, Sun G, Zang H, Chen S, Zhou Y (2022) Optimal home energy management strategy: a reinforcement learning method with actor-critic using Kronecker-factored trust region. Electric Power Syst Res 212:108617. https:\/\/doi.org\/10.1016\/j.epsr.2022.108617","journal-title":"Electric Power Syst Res"},{"key":"506_CR28","unstructured":"Clarivate (n.d.) Web of Science. Retrieved from https:\/\/www.webofscience.com"},{"key":"506_CR29","unstructured":"Co-occurrence Network Analysis using Biblioshiny (n.d.) Online Link: https:\/\/bibliometrix.org\/biblioshiny\/biblioshiny3.html?utm_source=chatgpt.com. [Accessed: 18-Sep-2024]."},{"key":"506_CR30","doi-asserted-by":"publisher","first-page":"1205","DOI":"10.1016\/j.apenergy.2018.04.130","volume":"225","author":"CA Correa-Florez","year":"2018","unstructured":"Correa-Florez CA, Gerossier A, Michiorri A, Kariniotakis G (2018) Stochastic operation of home energy management systems including battery cycling. Appl Energy 225:1205\u20131218. https:\/\/doi.org\/10.1016\/j.apenergy.2018.04.130","journal-title":"Appl Energy"},{"issue":"1","key":"506_CR31","doi-asserted-by":"publisher","first-page":"579","DOI":"10.1109\/TSTE.2021.3121444","volume":"13","author":"B Couraud","year":"2021","unstructured":"Couraud B, Robu V, Flynn D, Andoni M, Norbu S, Quinard H (2021) Real-time control of distributed batteries with blockchain-enabled market export commitments. IEEE Trans Sustain Energy 13(1):579\u2013591. https:\/\/doi.org\/10.1109\/TSTE.2021.3121444","journal-title":"IEEE Trans Sustain Energy"},{"key":"506_CR32","doi-asserted-by":"publisher","first-page":"3179","DOI":"10.1007\/s13042-020-01241-0","volume":"12","author":"I Cviti\u0107","year":"2021","unstructured":"Cviti\u0107 I, Perakovi\u0107 D, Peri\u0161a M et al (2021) Ensemble machine learning approach for classification of IoT devices in smart home. Int J Mach Learn Cyber 12:3179\u20133202. https:\/\/doi.org\/10.1007\/s13042-020-01241-0","journal-title":"Int J Mach Learn Cyber"},{"key":"506_CR33","doi-asserted-by":"publisher","first-page":"108120","DOI":"10.1016\/j.epsr.2022.108120","volume":"210","author":"H Ding","year":"2022","unstructured":"Ding H, Yan Xu, Hao BCS, Li Q, Lentzakis A (2022) A safe reinforcement learning approach for multi-energy management of smart home. Electric Power Syst Res 210:108120. https:\/\/doi.org\/10.1016\/j.epsr.2022.108120","journal-title":"Electric Power Syst Res"},{"key":"506_CR34","doi-asserted-by":"publisher","first-page":"49436","DOI":"10.1109\/ACCESS.2020.2979189","volume":"8","author":"HT Dinh","year":"2020","unstructured":"Dinh HT, Yun J, Kim DM, Lee K-H, Kim D (2020) A home energy management system with renewable energy and energy storage utilizing main grid and electricity selling. IEEE Access 8:49436\u201349450. https:\/\/doi.org\/10.1109\/ACCESS.2020.2979189","journal-title":"IEEE Access"},{"key":"506_CR35","doi-asserted-by":"publisher","first-page":"119382","DOI":"10.1016\/j.apenergy.2022.119382","volume":"321","author":"HT Dinh","year":"2022","unstructured":"Dinh HT, Lee KH, Kim D (2022) Supervised-learning-based hour-ahead demand response for a behavior-based home energy management system approximating MILP optimization. Appl Energy 321:119382. https:\/\/doi.org\/10.1016\/j.apenergy.2022.119382","journal-title":"Appl Energy"},{"key":"506_CR36","unstructured":"Directory of Open Access Journals (n.d.) DOAJ. Retrieved from https:\/\/www.doaj.org"},{"key":"506_CR37","doi-asserted-by":"publisher","first-page":"e3919","DOI":"10.1002\/ett.3919","volume":"33","author":"M Diyan","year":"2022","unstructured":"Diyan M, Nathali Silva B, Han J, Cao ZB, Han K (2022) Intelligent internet of things gateway supporting heterogeneous energy data management and processing. Trans Emerging Tel Tech 33:e3919. https:\/\/doi.org\/10.1002\/ett.3919","journal-title":"Trans Emerging Tel Tech"},{"key":"506_CR38","doi-asserted-by":"publisher","unstructured":"Diyan M, Khan M, Zhenbo C, Silva BN, Han J, Han KJ (2021) Intelligent home energy management system based on Bi-directional long-short term memory and reinforcement learning. In\u00a02021 International Conference on Information Networking (ICOIN)\u00a0(pp. 782-787). IEEE, Jeju Island, Korea (South), 13-16 January 2021. https:\/\/doi.org\/10.1109\/ICOIN50884.2021.9333984","DOI":"10.1109\/ICOIN50884.2021.9333984"},{"issue":"2","key":"506_CR39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3565973","volume":"19","author":"G Dong","year":"2023","unstructured":"Dong G, Tang M, Wang Z, Gao J, Guo S, Cai L, Gutierrez R, Campbel B, Barnes LE, Boukhechba M (2023) Graph neural networks in IoT: a survey. ACM Trans Sensor Netw 19(2):1\u201350. https:\/\/doi.org\/10.1145\/3565973","journal-title":"ACM Trans Sensor Netw"},{"key":"506_CR40","doi-asserted-by":"publisher","first-page":"121169","DOI":"10.1109\/ACCESS.2024.3452476","volume":"12","author":"E Efatinasab","year":"2024","unstructured":"Efatinasab E, Sinigaglia A, Azadi N, Susto GA, Rampazzo M (2024) Adversarially robust fault zone prediction in smart grids with bayesian neural networks. IEEE Access 12:121169\u2013121184. https:\/\/doi.org\/10.1109\/ACCESS.2024.3452476","journal-title":"IEEE Access"},{"key":"506_CR41","doi-asserted-by":"publisher","first-page":"2698","DOI":"10.3390\/en16062698","volume":"16","author":"R El Makroum","year":"2023","unstructured":"El Makroum R, Khallaayoun A, Lghoul R, Mehta K, Z\u00f6rner W (2023) Home energy management system based on genetic algorithm for load scheduling: a case study based on real life consumption data. Energies 16:2698. https:\/\/doi.org\/10.3390\/en16062698","journal-title":"Energies"},{"key":"506_CR42","doi-asserted-by":"publisher","first-page":"118974","DOI":"10.1016\/j.eswa.2022.118974","volume":"213","author":"MZ Fakhar","year":"2023","unstructured":"Fakhar MZ, Yalcin E, Bilge A (2023) A survey of smart home energy conservation techniques. Expert Syst Appl 213:118974. https:\/\/doi.org\/10.1016\/j.eswa.2022.118974","journal-title":"Expert Syst Appl"},{"issue":"3","key":"506_CR43","doi-asserted-by":"publisher","first-page":"563","DOI":"10.17775\/CSEEJPES.2018.01130","volume":"6","author":"L Fan","year":"2020","unstructured":"Fan L, Li J, Zhang XP (2020) Load prediction methods using machine learning for home energy management systems based on human behavior patterns recognition. CSEE J Power Energy Syst 6(3):563\u2013571. https:\/\/doi.org\/10.17775\/CSEEJPES.2018.01130","journal-title":"CSEE J Power Energy Syst"},{"key":"506_CR44","doi-asserted-by":"publisher","unstructured":"Fan X, Li X, Ding Y, He J (2022) Demand response strategy for smart community considering user preferences. In 2022 34th Chinese Control and Decision Conference (CCDC)\u00a0(pp. 1039-1044). IEEE, Hefei, China, 15-17 August 2022.\u00a0https:\/\/doi.org\/10.1109\/CCDC55256.2022.10033526","DOI":"10.1109\/CCDC55256.2022.10033526"},{"issue":"6","key":"506_CR45","doi-asserted-by":"publisher","first-page":"1434","DOI":"10.1007\/s40565-019-0553-2","volume":"7","author":"MN Faqiry","year":"2019","unstructured":"Faqiry MN, Wang L, Wu H (2019) HEMS-enabled transactive flexibility in real-time operation of three-phase unbalanced distribution systems. J Modern Power Syst Clean Energy 7(6):1434\u20131449. https:\/\/doi.org\/10.1007\/s40565-019-0553-2","journal-title":"J Modern Power Syst Clean Energy"},{"key":"506_CR46","doi-asserted-by":"publisher","first-page":"109283","DOI":"10.1016\/j.compeleceng.2024.109283","volume":"117","author":"R Felicetti","year":"2024","unstructured":"Felicetti R, Ferracuti F, Iarlori S, Monteri\u00f9 A (2024) Peak shaving and self-consumption maximization in home energy management systems: a combined integer programming and reinforcement learning approach. Comput Electr Eng 117:109283. https:\/\/doi.org\/10.1016\/j.compeleceng.2024.109283","journal-title":"Comput Electr Eng"},{"key":"506_CR47","doi-asserted-by":"publisher","first-page":"124070","DOI":"10.1016\/j.apenergy.2024.124070","volume":"374","author":"R Fiorotti","year":"2024","unstructured":"Fiorotti R, Fardin JF, Rocha HR, Rua D, Lopes JAP (2024) Day-ahead optimal scheduling considering thermal and electrical energy management in smart homes with photovoltaic\u2013thermal systems. Appl Energy 374:124070. https:\/\/doi.org\/10.1016\/j.apenergy.2024.124070","journal-title":"Appl Energy"},{"key":"506_CR48","doi-asserted-by":"publisher","first-page":"47896","DOI":"10.1109\/ACCESS.2022.3172327","volume":"10","author":"A Forootani","year":"2022","unstructured":"Forootani A, Rastegar M, Jooshaki M (2022) An advanced satisfaction-based home energy management system using deep reinforcement learning. IEEE Access 10:47896\u201347905. https:\/\/doi.org\/10.1109\/ACCESS.2022.3172327","journal-title":"IEEE Access"},{"key":"506_CR49","doi-asserted-by":"publisher","first-page":"1077","DOI":"10.3390\/en16031077","volume":"16","author":"V Franki","year":"2023","unstructured":"Franki V, Majnari\u0107 D, Vi\u0161kovi\u0107 A (2023) A comprehensive review of artificial intelligence (AI) companies in the power sector. Energies 16:1077. https:\/\/doi.org\/10.3390\/en16031077","journal-title":"Energies"},{"key":"506_CR50","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3491100","author":"PA Gbadega","year":"2024","unstructured":"Gbadega PA, Sun Y, Balogun OA (2024) Advanced control technique for optimal power management of a prosumer-centric residential microgrid. IEEE Access. https:\/\/doi.org\/10.1109\/ACCESS.2024.3491100","journal-title":"IEEE Access"},{"key":"506_CR51","doi-asserted-by":"publisher","first-page":"105579","DOI":"10.1016\/j.scs.2024.105579","volume":"111","author":"F Ghanavati","year":"2024","unstructured":"Ghanavati F, Matias JC, Os\u00f3rio GJ (2024) Towards sustainable smart cities: integration of home energy management system for efficient energy utilization. Sustain Cities Soc 111:105579. https:\/\/doi.org\/10.1016\/j.scs.2024.105579","journal-title":"Sustain Cities Soc"},{"key":"506_CR52","doi-asserted-by":"publisher","first-page":"101028","DOI":"10.1016\/j.jobe.2019.101028","volume":"28","author":"HR Gholinejad","year":"2020","unstructured":"Gholinejad HR, Loni A, Adabi J, Marzband M (2020) A hierarchical energy management system for multiple home energy hubs in neighborhood grids. J Build Eng 28:101028. https:\/\/doi.org\/10.1016\/j.jobe.2019.101028","journal-title":"J Build Eng"},{"key":"506_CR53","doi-asserted-by":"publisher","first-page":"110000","DOI":"10.1016\/j.rser.2020.110000","volume":"132","author":"J Guerrero","year":"2020","unstructured":"Guerrero J, Gebbran D, Mhanna S, Chapman AC, Verbi\u010d G (2020) Towards a transactive energy system for integration of distributed energy resources: home energy management, distributed optimal power flow, and peer-to-peer energy trading. Renew Sustain Energy Rev 132:110000. https:\/\/doi.org\/10.1016\/j.rser.2020.110000","journal-title":"Renew Sustain Energy Rev"},{"key":"506_CR54","doi-asserted-by":"publisher","unstructured":"Hamedifar S, Liu S, Xiao G (2024) Non-Intrusive Load Monitoring-based Fuzzy Actor-Critic Reinforcement Learning Home Energy Management. In\u00a02024 IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS)\u00a0(pp. 1-6). IEEE, St. Louis, MO, USA, 12-15 May 2024. https:\/\/doi.org\/10.1109\/ICPS59941.2024.10639994","DOI":"10.1109\/ICPS59941.2024.10639994"},{"key":"506_CR55","doi-asserted-by":"publisher","first-page":"100822","DOI":"10.1016\/j.suscom.2022.100822","volume":"36","author":"P He","year":"2022","unstructured":"He P, Almasifar N, Mehbodniya A, Javaheri D, Webber JL (2022) Towards green smart cities using Internet of Things and optimization algorithms: a systematic and bibliometric review. Sustain Comp: Inform Syst 36:100822. https:\/\/doi.org\/10.1016\/j.suscom.2022.100822","journal-title":"Sustain Comp: Inform Syst"},{"issue":"3","key":"506_CR56","doi-asserted-by":"publisher","first-page":"743","DOI":"10.35833\/MPCE.2021.000394","volume":"10","author":"C Huang","year":"2022","unstructured":"Huang C, Zhang H, Wang L, Luo X, Song Y (2022) Mixed deep reinforcement learning considering discrete-continuous hybrid action space for smart home energy management. J Mod Power Syst. Clean Energy 10(3):743\u2013754. https:\/\/doi.org\/10.35833\/MPCE.2021.000394","journal-title":"J Mod Power Syst. Clean Energy"},{"issue":"2","key":"506_CR57","doi-asserted-by":"publisher","first-page":"180","DOI":"10.3390\/electronics8020180","volume":"8","author":"B Hussain","year":"2019","unstructured":"Hussain B, Khan A, Javaid N, Hasan QU, Malik AS, Ahmad O, Dar AH, Kazmi A (2019) A weighted-sum PSO algorithm for HEMS: a new approach for the design and diversified performance analysis. Electronics 8(2):180. https:\/\/doi.org\/10.3390\/electronics8020180","journal-title":"Electronics"},{"key":"506_CR58","doi-asserted-by":"publisher","first-page":"117340","DOI":"10.1016\/j.enconman.2023.117340","volume":"292","author":"THB Huy","year":"2023","unstructured":"Huy THB, Dinh HT, Vo DN, Kim D (2023) Real-time energy scheduling for home energy management systems with an energy storage system and electric vehicle based on a supervised-learning-based strategy. Energy Convers Manag 292:117340. https:\/\/doi.org\/10.1016\/j.enconman.2023.117340","journal-title":"Energy Convers Manag"},{"key":"506_CR59","doi-asserted-by":"publisher","first-page":"100647","DOI":"10.1016\/j.ref.2024.100647","volume":"51","author":"HH Issa","year":"2024","unstructured":"Issa HH, Abedini M, Hamzeh M, Anvari A (2024) Day-ahead multi-criteria energy management of a smart home under different electrical rationing scenarios. Renew Energy Focus 51:100647. https:\/\/doi.org\/10.1016\/j.ref.2024.100647","journal-title":"Renew Energy Focus"},{"key":"506_CR60","doi-asserted-by":"publisher","first-page":"101005","DOI":"10.1016\/j.suscom.2024.101005","volume":"43","author":"H \u0130zmitligil","year":"2024","unstructured":"\u0130zmitligil H, Karamanc\u0131o\u011flu A (2024) An online home energy management system using Q-learning and deep Q-learning. Sustain Comput: Inform. Syst 43:101005. https:\/\/doi.org\/10.1016\/j.suscom.2024.101005","journal-title":"Sustain Comput: Inform. Syst"},{"key":"506_CR61","doi-asserted-by":"publisher","unstructured":"Jamil A, Javaid N, Aslam S (2018) An efficient home energy optimization by using meta-heuristic techniques while incorporating game-theoretic approach for real-time coordination among home appliances. In\u00a02018 5th International Multi-Topic ICT Conference (IMTIC)\u00a0(pp. 1-6). IEEE, Jamshoro, Pakistan, 25-27 April 2018.\u00a0https:\/\/doi.org\/10.1109\/IMTIC.2018.8467218","DOI":"10.1109\/IMTIC.2018.8467218"},{"issue":"1","key":"506_CR62","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1007\/s41660-022-00304-9","volume":"7","author":"V Janamala","year":"2023","unstructured":"Janamala V, Radha Rani K, Sobha Rani P et al (2023) Optimal switching operations of soft open points in active distribution network for handling variable penetration of photovoltaic and electric vehicles using artificial rabbits optimization. Process Integr Optim Sustain 7(1):419\u2013437. https:\/\/doi.org\/10.1007\/s41660-022-00304-9","journal-title":"Process Integr Optim Sustain"},{"key":"506_CR63","doi-asserted-by":"publisher","unstructured":"Jha AV, Appasani B, Gupta DK, Ramavath S, Khan MS (2023) Machine learning and deep learning approaches for energy management in Smart Grid 3.0. In: Appasani B, Bizon N (eds) Smart Grid 3.0. Power Systems. Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-031-38506-3_6","DOI":"10.1007\/978-3-031-38506-3_6"},{"issue":"23","key":"506_CR64","doi-asserted-by":"publisher","first-page":"7440","DOI":"10.3390\/s24237440","volume":"24","author":"MI Joha","year":"2024","unstructured":"Joha MI, Rahman MM, Nazim MS, Jang YM (2024) A secure IIoT environment that integrates AI-driven real-time short-term active and reactive load forecasting with anomaly detection: a real-world application. Sensors 24(23):7440. https:\/\/doi.org\/10.3390\/s24237440","journal-title":"Sensors"},{"key":"506_CR65","doi-asserted-by":"publisher","first-page":"109548","DOI":"10.1016\/j.jobe.2024.109548.A","volume":"91","author":"VD Juyal","year":"2024","unstructured":"Juyal VD, Kakran S (2024) Smart home energy management and active power loss analysis of a residential community. J Build Eng 91:109548. https:\/\/doi.org\/10.1016\/j.jobe.2024.109548.A","journal-title":"J Build Eng"},{"key":"506_CR66","doi-asserted-by":"publisher","first-page":"123062","DOI":"10.1016\/j.apenergy.2024.123062","volume":"364","author":"D Kanakadhurga","year":"2024","unstructured":"Kanakadhurga D, Prabaharan N (2024) Smart home energy management using demand response with uncertainty analysis of electric vehicle in the presence of renewable energy sources. Appl Energy 364:123062. https:\/\/doi.org\/10.1016\/j.apenergy.2024.123062","journal-title":"Appl Energy"},{"issue":"1","key":"506_CR67","doi-asserted-by":"publisher","first-page":"4","DOI":"10.3390\/buildings9010004","volume":"9","author":"R KC","year":"2019","unstructured":"KC R, Rijal HB, Shukuya M, Yoshida K (2019) An investigation of the behavioral characteristics of higher-and lower-temperature group families in a condominium equipped with a HEMS system. Buildings 9(1):4. https:\/\/doi.org\/10.3390\/buildings9010004","journal-title":"Buildings"},{"key":"506_CR68","doi-asserted-by":"publisher","unstructured":"Keerthana K, Snekha S, Nandan G, Ramalingam SP, Shanmugam PK, Raglend IJ (2023) Minimising energy consumption cost using ant colony optimization with power quality considerations under HEMS environment. In 2023 innovations in power and advanced computing technologies (i-PACT) (pp. 1-8). IEEE, Kuala Lumpur, Malaysia, 08-10 December 2023. https:\/\/doi.org\/10.1109\/i-PACT58649.2023.10434471","DOI":"10.1109\/i-PACT58649.2023.10434471"},{"key":"506_CR69","doi-asserted-by":"publisher","first-page":"4837","DOI":"10.1007\/s12652-018-01169-y","volume":"10","author":"ZA Khan","year":"2019","unstructured":"Khan ZA, Zafar A, Javaid S et al (2019) Hybrid meta-heuristic optimization based home energy management system in smart grid. J Ambient Intell Human Comput 10:4837\u20134853. https:\/\/doi.org\/10.1007\/s12652-018-01169-y","journal-title":"J Ambient Intell Human Comput"},{"key":"506_CR70","doi-asserted-by":"publisher","first-page":"110755","DOI":"10.1016\/j.rser.2021.110755","volume":"140","author":"H Kim","year":"2021","unstructured":"Kim H, Choi H, Kang H, An J, Yeom S, Hong T (2021) A systematic review of the smart energy conservation system: from smart homes to sustainable smart cities. Renew Sustain Energy Rev 140:110755. https:\/\/doi.org\/10.1016\/j.rser.2021.110755","journal-title":"Renew Sustain Energy Rev"},{"key":"506_CR71","doi-asserted-by":"publisher","first-page":"112013","DOI":"10.1016\/j.rser.2021.112013","volume":"158","author":"D Kirli","year":"2022","unstructured":"Kirli D, Couraud B, Robu V, Salgado-Bravo M, Norbu S, Andoni M, Antonopoulos I, Negrete-Pincetic M, Flynn D, Kiprakis A (2022) Smart contracts in energy systems: a systematic review of fundamental approaches and implementations. Renew Sustain Energy Rev 158:112013. https:\/\/doi.org\/10.1016\/j.rser.2021.112013","journal-title":"Renew Sustain Energy Rev"},{"key":"506_CR72","doi-asserted-by":"publisher","DOI":"10.1007\/s41660-024-00436-0","author":"JPY Kiu","year":"2024","unstructured":"Kiu JPY, Kong KGH, Andiappan V et al (2024) Developing resilient peer-to-peer energy sharing scheme using \u201cN-1\u201d contingency. Process Integr Optim Sustain. https:\/\/doi.org\/10.1007\/s41660-024-00436-0","journal-title":"Process Integr Optim Sustain"},{"key":"506_CR73","unstructured":"K-means clustering using bibliometrix R tool for Data Analytics (n.d.) Online Link: https:\/\/rforanalytics.com\/06-method3.html. [Accessed: 15-Sep-2024]."},{"key":"506_CR74","doi-asserted-by":"publisher","unstructured":"Koltsaklis NE, Panapakidis IP, Christoforidis GC, Parisses CE (2019) An MILP model for the optimal energy management of a smart household. In\u00a02019 16th International Conference on the European Energy Market (EEM)\u00a0(pp. 1-6). IEEE, Ljubljana, Slovenia, 18-20 September 2019. https:\/\/doi.org\/10.1109\/EEM.2019.8916426","DOI":"10.1109\/EEM.2019.8916426"},{"key":"506_CR75","doi-asserted-by":"publisher","first-page":"1598","DOI":"10.3390\/en14061598","volume":"14","author":"G La Tona","year":"2021","unstructured":"La Tona G, Di Piazza MC, Luna M (2021) Effect of daily forecasting frequency on rolling-horizon-based EMS reducing electrical demand uncertainty in microgrids. Energies 14:1598. https:\/\/doi.org\/10.3390\/en14061598","journal-title":"Energies"},{"issue":"1","key":"506_CR76","doi-asserted-by":"publisher","first-page":"488","DOI":"10.1109\/TII.2020.3035451","volume":"18","author":"S Lee","year":"2020","unstructured":"Lee S, Choi DH (2020) Federated reinforcement learning for energy management of multiple smart homes with distributed energy resources. IEEE Trans Ind Inf 18(1):488\u2013497. https:\/\/doi.org\/10.1109\/TII.2020.3035451","journal-title":"IEEE Trans Ind Inf"},{"key":"506_CR77","doi-asserted-by":"publisher","first-page":"2157","DOI":"10.3390\/s20072157","volume":"20","author":"S Lee","year":"2020","unstructured":"Lee S, Choi D-H (2020) Energy management of smart home with home appliances, energy storage system and electric vehicle: a hierarchical deep reinforcement learning approach. Sensors 20:2157. https:\/\/doi.org\/10.3390\/s20072157","journal-title":"Sensors"},{"key":"506_CR78","doi-asserted-by":"publisher","unstructured":"Li H, Wan Z, He H (2020) A deep reinforcement learning based approach for home energy management system. In\u00a02020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT)\u00a0(pp. 1-5). IEEE, Washington, DC, USA, 17-20 February 2020. https:\/\/doi.org\/10.1109\/ISGT45199.2020.9087647","DOI":"10.1109\/ISGT45199.2020.9087647"},{"key":"506_CR79","doi-asserted-by":"publisher","first-page":"104850","DOI":"10.1016\/j.scs.2023.104850","volume":"98","author":"J Liao","year":"2023","unstructured":"Liao J, Yang D, Arshad NI, Venkatachalam K, Ahmadian A (2023) MEMS: an automated multi-energy management system for smart residences using the DD-LSTM approach. Sustain Cities Soc 98:104850. https:\/\/doi.org\/10.1016\/j.scs.2023.104850","journal-title":"Sustain Cities Soc"},{"key":"506_CR80","doi-asserted-by":"publisher","first-page":"101222","DOI":"10.1016\/j.iot.2024.101222","volume":"26","author":"Y-H Lin","year":"2024","unstructured":"Lin Y-H, Ciou J-C (2024) A privacy-preserving distributed energy management framework based on vertical federated learning-based smart data cleaning for smart home electricity data. Int Things 26:101222. https:\/\/doi.org\/10.1016\/j.iot.2024.101222","journal-title":"Int Things"},{"issue":"3","key":"506_CR81","doi-asserted-by":"publisher","first-page":"572","DOI":"10.17775\/CSEEJPES.2019.02890","volume":"6","author":"Y Liu","year":"2020","unstructured":"Liu Y, Zhang D, Gooi HB (2020) Optimization strategy based on deep reinforcement learning for home energy management. CSEE J Power Energy Syst 6(3):572\u2013582. https:\/\/doi.org\/10.17775\/CSEEJPES.2019.02890","journal-title":"CSEE J Power Energy Syst"},{"key":"506_CR82","doi-asserted-by":"publisher","first-page":"119911","DOI":"10.1016\/j.apenergy.2022.119911","volume":"326","author":"Y Liu","year":"2022","unstructured":"Liu Y, Ma J, Xing X, Liu X, Wang W (2022) A home energy management system incorporating data-driven uncertainty-aware user preference. Appl Energy 326:119911. https:\/\/doi.org\/10.1016\/j.apenergy.2022.119911","journal-title":"Appl Energy"},{"key":"506_CR83","doi-asserted-by":"publisher","unstructured":"Qing Lu, Zhixin Zhang, Shuaikang L\u00c3\u00bc (2020) Home energy management in smart households: Optimal appliance scheduling model with photovoltaic energy storage system, Energy Reports 6:2450\u201362. https:\/\/doi.org\/10.1016\/j.egyr.2020.09.001","DOI":"10.1016\/j.egyr.2020.09.001"},{"key":"506_CR84","doi-asserted-by":"publisher","unstructured":"Ludolfinger U, Peri\u0107 VS, Hamacher T, Hauke S, Martens M (2023) Transformer Model Based Soft Actor-Critic Learning for HEMS. In\u00a02023 International Conference on Power System Technology (PowerCon)\u00a0(pp. 1-6). IEEE, Jinan, China, 21-22 September 2023. https:\/\/doi.org\/10.1109\/PowerCon58120.2023.10331287","DOI":"10.1109\/PowerCon58120.2023.10331287"},{"issue":"1","key":"506_CR85","doi-asserted-by":"publisher","first-page":"9101453","DOI":"10.1155\/2021\/9101453","volume":"2021","author":"Y Ma","year":"2021","unstructured":"Ma Y, Chen X, Wang L, Yang J (2021) Study on smart home energy management system based on artificial intelligence. J Sensors 2021(1):9101453. https:\/\/doi.org\/10.1155\/2021\/9101453","journal-title":"J Sensors"},{"key":"506_CR86","doi-asserted-by":"publisher","first-page":"5809","DOI":"10.3390\/en16155809","volume":"16","author":"P Ma","year":"2023","unstructured":"Ma P, Cui S, Chen M, Zhou S, Wang K (2023) Review of family-level short-term load forecasting and its application in household energy management system. Energies 16:5809. https:\/\/doi.org\/10.3390\/en16155809","journal-title":"Energies"},{"key":"506_CR87","doi-asserted-by":"publisher","first-page":"1097","DOI":"10.3390\/en13051097","volume":"13","author":"I Machorro-Cano","year":"2020","unstructured":"Machorro-Cano I, Alor-Hern\u00e1ndez G, Paredes-Valverde MA, Rodr\u00edguez-Mazahua L, S\u00e1nchez-Cervantes JL, Olmedo-Aguirre JO (2020) HEMS-IoT: a big data and machine learning-based smart home system for energy saving. Energies 13:1097. https:\/\/doi.org\/10.3390\/en13051097","journal-title":"Energies"},{"key":"506_CR88","doi-asserted-by":"publisher","first-page":"100993","DOI":"10.1016\/j.suscom.2024.100993","volume":"43","author":"LP Maguluri","year":"2024","unstructured":"Maguluri LP, Umasankar A, Babu DV, Nisha ASA, Prabhu MR, Tilwani SA (2024) Coordinating electric vehicle charging with multiagent deep Q-networks for smart grid load balancing. Sustain Comput Informatics Syst 43:100993. https:\/\/doi.org\/10.1016\/j.suscom.2024.100993","journal-title":"Sustain Comput Informatics Syst"},{"key":"506_CR89","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1007\/s12667-019-00364-w","volume":"13","author":"B Mahapatra","year":"2022","unstructured":"Mahapatra B, Nayyar A (2022) Home energy management system (HEMS): concept, architecture, infrastructure, challenges and energy management schemes. Energy Syst 13:643\u2013669. https:\/\/doi.org\/10.1007\/s12667-019-00364-w","journal-title":"Energy Syst"},{"issue":"8","key":"506_CR90","doi-asserted-by":"publisher","first-page":"817","DOI":"10.1080\/15325008.2020.1821831","volume":"48","author":"M Mahmoudi","year":"2020","unstructured":"Mahmoudi M, Afsharchi M, Khodayifar S (2020) Demand response management in smart homes using robust optimization. Electr Power Components Syst 48(8):817\u2013832. https:\/\/doi.org\/10.1080\/15325008.2020.1821831","journal-title":"Electr Power Components Syst"},{"key":"506_CR91","doi-asserted-by":"publisher","first-page":"101692","DOI":"10.1016\/j.jobe.2020.101692","volume":"33","author":"D Mariano-Hern\u00e1ndez","year":"2021","unstructured":"Mariano-Hern\u00e1ndez D, Hern\u00e1ndez-Callejo L, Zorita-Lamadrid A, Duque-P\u00e9rez O, Garc\u00eda FS (2021) A review of strategies for building energy management system: model predictive control, demand side management, optimization, and fault detect & diagnosis. J Build Eng 33:101692. https:\/\/doi.org\/10.1016\/j.jobe.2020.101692","journal-title":"J Build Eng"},{"key":"506_CR92","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1016\/j.rser.2018.02.021","volume":"88","author":"G Mavromatidis","year":"2018","unstructured":"Mavromatidis G, Orehounig K, Carmeliet J (2018) A review of uncertainty characterisation approaches for the optimal design of distributed energy systems. Renew Sustain Energy Rev 88:258\u2013277. https:\/\/doi.org\/10.1016\/j.rser.2018.02.021","journal-title":"Renew Sustain Energy Rev"},{"key":"506_CR93","doi-asserted-by":"publisher","first-page":"101555","DOI":"10.1016\/j.erss.2020.101555","volume":"68","author":"C McIlvennie","year":"2020","unstructured":"McIlvennie C, Sanguinetti A, Pritoni M (2020) Of impacts, agents, and functions: an interdisciplinary meta-review of smart home energy management systems research. Energy Res Soc Sci 68:101555. https:\/\/doi.org\/10.1016\/j.erss.2020.101555","journal-title":"Energy Res Soc Sci"},{"key":"506_CR94","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1016\/j.ins.2018.03.039","volume":"448","author":"F Meng","year":"2018","unstructured":"Meng F, Zeng XJ, Zhang Y, Dent CJ, Gong D (2018) An integrated optimization+ learning approach to optimal dynamic pricing for the retailer with multi-type customers in smart grids. Inform Sci 448:215\u2013232. https:\/\/doi.org\/10.1016\/j.ins.2018.03.039","journal-title":"Inform Sci"},{"key":"506_CR95","doi-asserted-by":"publisher","first-page":"106229","DOI":"10.1016\/j.epsr.2020.106229","volume":"182","author":"H Merdano\u011flu","year":"2020","unstructured":"Merdano\u011flu H, Yak\u0131c\u0131 E, Do\u011fan OT, Duran S, Karatas M (2020) Finding optimal schedules in a home energy management system. Electric Power Syst Res 182:106229. https:\/\/doi.org\/10.1016\/j.epsr.2020.106229","journal-title":"Electric Power Syst Res"},{"issue":"97","key":"506_CR96","doi-asserted-by":"publisher","first-page":"38354","DOI":"10.1016\/j.ijhydene.2023.06.126","volume":"48","author":"B Modu","year":"2023","unstructured":"Modu B, Abdullah MP, Bukar AL, Hamza MF (2023) A systematic review of hybrid renewable energy systems with hydrogen storage: sizing, optimization, and energy management strategy. Int J Hydrogen Energy 48(97):38354\u201338373. https:\/\/doi.org\/10.1016\/j.ijhydene.2023.06.126","journal-title":"Int J Hydrogen Energy"},{"key":"506_CR97","doi-asserted-by":"publisher","unstructured":"Moher D, Liberati A, Tetzlaff J, Altman DG, Prisma Group (2010) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Int Surg J 8(5): 336-341.\u00a0https:\/\/doi.org\/10.1371\/journal.pmed.1000097","DOI":"10.1371\/journal.pmed.1000097"},{"key":"506_CR98","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1007\/s11336-006-1579-x","volume":"72","author":"F Murtagh","year":"2007","unstructured":"Murtagh F (2007) Multiple correspondence analysis and related methods. Psychometrika 72:275. https:\/\/doi.org\/10.1007\/s11336-006-1579-x","journal-title":"Psychometrika"},{"key":"506_CR99","doi-asserted-by":"publisher","first-page":"29716","DOI":"10.1109\/ACCESS.2022.3158346","volume":"10","author":"AE Nezhad","year":"2022","unstructured":"Nezhad AE, Rahimnejad A, Nardelli PH, Gadsden SA, Sahoo S, Ghanavati F (2022) A shrinking horizon model predictive controller for daily scheduling of home energy management systems. IEEE Access 10:29716\u201329730. https:\/\/doi.org\/10.1109\/ACCESS.2022.3158346","journal-title":"IEEE Access"},{"issue":"2","key":"506_CR100","doi-asserted-by":"publisher","first-page":"1470","DOI":"10.1109\/TPWRS.2020.3021474","volume":"36","author":"DH Nguyen","year":"2021","unstructured":"Nguyen DH (2021) optimal solution analysis and decentralized mechanisms for peer-to-peer energy markets. IEEE Trans Power Syst 36(2):1470\u20131481. https:\/\/doi.org\/10.1109\/TPWRS.2020.3021474","journal-title":"IEEE Trans Power Syst"},{"key":"506_CR101","doi-asserted-by":"publisher","first-page":"105721","DOI":"10.1016\/j.engappai.2022.105721","volume":"119","author":"M Nutakki","year":"2023","unstructured":"Nutakki M, Mandava S (2023) Review on optimization techniques and role of Artificial Intelligence in home energy management systems. Eng Appl Artif Intell 119:105721. https:\/\/doi.org\/10.1016\/j.engappai.2022.105721","journal-title":"Eng Appl Artif Intell"},{"key":"506_CR102","doi-asserted-by":"publisher","first-page":"1391602","DOI":"10.3389\/fther.2024.1391602","volume":"4","author":"T Pan","year":"2024","unstructured":"Pan T, Zhu Z, Luo H, Li C, Jin X, Meng Z, Cai X (2024) Home energy management strategy to schedule multiple types of loads and energy storage device with consideration of user comfort: a deep reinforcement learning based approach. Front Therm Eng 4:1391602. https:\/\/doi.org\/10.3389\/fther.2024.1391602","journal-title":"Front Therm Eng"},{"key":"506_CR103","doi-asserted-by":"publisher","first-page":"3727","DOI":"10.1016\/j.egyr.2022.02.300","volume":"8","author":"S Panda","year":"2022","unstructured":"Panda S, Mohanty S, Rout PK, Sahu BK, Bajaj M, Zawbaa HM, Kamel S (2022) Residential demand side management model, optimization and future perspective: a review. Energy Rep 8:3727\u20133766. https:\/\/doi.org\/10.1016\/j.egyr.2022.02.300","journal-title":"Energy Rep"},{"key":"506_CR104","doi-asserted-by":"publisher","first-page":"2404","DOI":"10.3390\/en17102404","volume":"17","author":"B Park","year":"2024","unstructured":"Park B, Kwon S-H, Oh B (2024) Standby power reduction of home appliance by the i-HEMS system using supervised learning techniques. Energies 17:2404. https:\/\/doi.org\/10.3390\/en17102404","journal-title":"Energies"},{"key":"506_CR105","doi-asserted-by":"publisher","first-page":"132","DOI":"10.3390\/su13010132","volume":"13","author":"C Pfeiffer","year":"2021","unstructured":"Pfeiffer C, Puchegger M, Maier C, Tomaschitz IV, Kremsner TP, Gnam L (2021) A case study of socially-accepted potentials for the use of end user flexibility by home energy management systems. Sustainability 13:132. https:\/\/doi.org\/10.3390\/su13010132","journal-title":"Sustainability"},{"key":"506_CR106","doi-asserted-by":"publisher","first-page":"114648","DOI":"10.1016\/j.rser.2024.114648","volume":"202","author":"W Pinthurat","year":"2024","unstructured":"Pinthurat W, Surinkaew T, Hredzak B (2024) An overview of reinforcement learning-based approaches for smart home energy management systems with energy storages. Renew Sustain Energy Rev 202:114648. https:\/\/doi.org\/10.1016\/j.rser.2024.114648","journal-title":"Renew Sustain Energy Rev"},{"key":"506_CR107","doi-asserted-by":"publisher","unstructured":"Radhamani R, Karthick S, Kumar SK, Gokulraj M (2024) Deployment of an IoT-integrated home energy management system employing deep reinforcement learning. In\u00a02024 2nd International Conference on Artificial Intelligence and Machine Learning Applications Theme: Healthcare and Internet of Things (AIMLA)\u00a0(pp. 1-4). IEEE, Namakkal, India, 15-16 March 2024. https:\/\/doi.org\/10.1109\/AIMLA59606.2024.10531519.","DOI":"10.1109\/AIMLA59606.2024.10531519"},{"issue":"16","key":"506_CR108","doi-asserted-by":"publisher","first-page":"e35887","DOI":"10.1016\/j.heliyon.2024.e35887","volume":"10","author":"N Ramachandra","year":"2024","unstructured":"Ramachandra N, Natarajan R (2024) State-of-the-art and real-time implementation of an IoT-based home energy management system for a cluster of dwellings. Heliyon 10(16):e35887. https:\/\/doi.org\/10.1016\/j.heliyon.2024.e35887","journal-title":"Heliyon"},{"key":"506_CR109","doi-asserted-by":"publisher","first-page":"110166","DOI":"10.1016\/j.dib.2024.110166","volume":"53","author":"RA Ramadan","year":"2024","unstructured":"Ramadan RA (2024) Internet of Things dataset for home renewable energy management. Data in Brief 53:110166. https:\/\/doi.org\/10.1016\/j.dib.2024.110166","journal-title":"Data in Brief"},{"key":"506_CR110","doi-asserted-by":"publisher","first-page":"102766","DOI":"10.1016\/j.rineng.2024.102766","volume":"23","author":"A Raza","year":"2024","unstructured":"Raza A, Jingzhao L, Adnan M, Iqbal MS (2024) Transforming smart homes via P2P energy trading using robust forecasting and scheduling framework. Results Eng 23:102766. https:\/\/doi.org\/10.1016\/j.rineng.2024.102766","journal-title":"Results Eng"},{"key":"506_CR111","doi-asserted-by":"publisher","first-page":"103207","DOI":"10.1016\/j.scs.2021.103207","volume":"76","author":"M Ren","year":"2022","unstructured":"Ren M, Liu X, Yang Z, Zhang J, Guo Y, Jia Y (2022) A novel forecasting based scheduling method for household energy management system based on deep reinforcement learning. Sustain Cities Soc 76:103207. https:\/\/doi.org\/10.1016\/j.scs.2021.103207","journal-title":"Sustain Cities Soc"},{"key":"506_CR112","doi-asserted-by":"publisher","first-page":"122258","DOI":"10.1016\/j.apenergy.2023.122258","volume":"355","author":"K Ren","year":"2024","unstructured":"Ren K, Liu J, Zeyang Wu, Liu X, Nie Y, Haitao Xu (2024) A data-driven DRL-based home energy management system optimization framework considering uncertain household parameters. Appl Energy 355:122258. https:\/\/doi.org\/10.1016\/j.apenergy.2023.122258","journal-title":"Appl Energy"},{"key":"506_CR113","doi-asserted-by":"publisher","first-page":"100448","DOI":"10.1016\/j.egyai.2024.100448","volume":"18","author":"J Ruddick","year":"2024","unstructured":"Ruddick J, Ceusters G, Van Kriekinge G, Genov E, De Cauwer C, Coosemans T, Messagie M (2024) Real-world validation of safe reinforcement learning, model predictive control and decision tree-based home energy management systems. Energy and AI 18:100448. https:\/\/doi.org\/10.1016\/j.egyai.2024.100448","journal-title":"Energy and AI"},{"key":"506_CR114","doi-asserted-by":"publisher","first-page":"112253","DOI":"10.1016\/j.enbuild.2022.112253","volume":"269","author":"M Saffari","year":"2022","unstructured":"Saffari M, Beagon P (2022) Home energy retrofit: reviewing its depth, scale of delivery, and sustainability. Energy Build 269:112253. https:\/\/doi.org\/10.1016\/j.enbuild.2022.112253","journal-title":"Energy Build"},{"key":"506_CR115","doi-asserted-by":"publisher","first-page":"104528","DOI":"10.1016\/j.scs.2023.104528","volume":"95","author":"A Salari","year":"2023","unstructured":"Salari A, Ahmadi SE, Marzband M, Zeinali M (2023) Fuzzy Q-learning-based approach for real-time energy management of home microgrids using cooperative multi-agent system. Sustain Cities Soc 95:104528. https:\/\/doi.org\/10.1016\/j.scs.2023.104528","journal-title":"Sustain Cities Soc"},{"key":"506_CR116","doi-asserted-by":"publisher","unstructured":"Saleptsis M, Mussetta M, Leva S (2024) An overview of optimization methods for home energy management systems. In\u00a02024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC\/I&CPS Europe)\u00a0(pp. 1-6). IEEE, Rome, Italy, 17-20 June 2024. https:\/\/doi.org\/10.1109\/EEEIC\/ICPSEurope61470.2024.10751185.","DOI":"10.1109\/EEEIC\/ICPSEurope61470.2024.10751185"},{"key":"506_CR117","doi-asserted-by":"publisher","first-page":"106211","DOI":"10.1016\/j.ijepes.2020.106211","volume":"122","author":"E Samadi","year":"2020","unstructured":"Samadi E, Badri A, Ebrahimpour R (2020) Decentralized multi-agent based energy management of microgrid using reinforcement learning. Int J Electr Power Energy Syst 122:106211. https:\/\/doi.org\/10.1016\/j.ijepes.2020.106211","journal-title":"Int J Electr Power Energy Syst"},{"key":"506_CR118","doi-asserted-by":"publisher","first-page":"5517","DOI":"10.1109\/ACCESS.2020.3047885","volume":"9","author":"S Saxena","year":"2021","unstructured":"Saxena S, Farag HEZ, Brookson A, Turesson H, Kim H (2021) A permissioned blockchain system to reduce peak demand in residential communities via energy trading: a real-world case study. IEEE Access 9:5517\u20135530. https:\/\/doi.org\/10.1109\/ACCESS.2020.3047885","journal-title":"IEEE Access"},{"key":"506_CR119","doi-asserted-by":"publisher","first-page":"102517","DOI":"10.1016\/j.scs.2020.102517","volume":"65","author":"S Sharda","year":"2021","unstructured":"Sharda S, Singh M, Sharma K (2021) Demand side management through load shifting in IoT based HEMS: overview, challenges and opportunities. Sustain Cities Soc 65:102517. https:\/\/doi.org\/10.1016\/j.scs.2020.102517","journal-title":"Sustain Cities Soc"},{"key":"506_CR120","doi-asserted-by":"publisher","first-page":"24498","DOI":"10.1109\/ACCESS.2018.2831917","volume":"6","author":"H Shareef","year":"2018","unstructured":"Shareef H, Ahmed MS, Mohamed A, Al Hassan E (2018) Review on home energy management system considering demand responses, smart technologies, and intelligent controllers. IEEE Access 6:24498\u201324509. https:\/\/doi.org\/10.1109\/ACCESS.2018.2831917","journal-title":"IEEE Access"},{"key":"506_CR121","doi-asserted-by":"publisher","first-page":"5196","DOI":"10.3390\/en14165196","volume":"14","author":"U Singh","year":"2021","unstructured":"Singh U, Rizwan M, Alaraj M, Alsaidan I (2021) A Machine learning-based gradient boosting regression approach for wind power production forecasting: a step towards smart grid environments. Energies 14:5196. https:\/\/doi.org\/10.3390\/en14165196","journal-title":"Energies"},{"key":"506_CR122","doi-asserted-by":"publisher","unstructured":"Szczygielski JJ, Charteris A, Obojska L, Brzeszczy\u0144ski J (2024) What does energy price uncertainty reveal about the global energy crisis? Int Rev Financ Anal 103838. https:\/\/doi.org\/10.1016\/j.irfa.2024.103838","DOI":"10.1016\/j.irfa.2024.103838"},{"key":"506_CR123","doi-asserted-by":"publisher","first-page":"111132","DOI":"10.1016\/j.jobe.2024.111132","volume":"98","author":"JC Teo","year":"2024","unstructured":"Teo JC, Yao L (2024) Home energy management system for residential fuel cell-based combined heat and power system. J Building Eng 98:111132. https:\/\/doi.org\/10.1016\/j.jobe.2024.111132","journal-title":"J Building Eng"},{"key":"506_CR124","doi-asserted-by":"publisher","first-page":"107666","DOI":"10.1016\/j.ijepes.2021.107666","volume":"136","author":"M Tostado-V\u00e9liz","year":"2022","unstructured":"Tostado-V\u00e9liz M, Gurung S, Jurado F (2022) Efficient solution of many-objective home energy management systems. Int J Electr Power Energy Syst 136:107666. https:\/\/doi.org\/10.1016\/j.ijepes.2021.107666","journal-title":"Int J Electr Power Energy Syst"},{"key":"506_CR125","doi-asserted-by":"publisher","first-page":"117310","DOI":"10.1016\/j.apenergy.2021.117310","volume":"299","author":"S Tuomela","year":"2021","unstructured":"Tuomela S, de Castro Tom\u00e9 M, Iivari N, Svento R (2021) Impacts of home energy management systems on electricity consumption. Appl Energy 299:117310. https:\/\/doi.org\/10.1016\/j.apenergy.2021.117310","journal-title":"Appl Energy"},{"key":"506_CR126","doi-asserted-by":"publisher","first-page":"104720","DOI":"10.1016\/j.scs.2023.104720","volume":"96","author":"U ur Rehman","year":"2023","unstructured":"ur Rehman U, Faria P, Gomes L, Vale Z (2023) Future of energy management systems in smart cities: a systematic literature review. Sustain Cities Soc 96:104720. https:\/\/doi.org\/10.1016\/j.scs.2023.104720","journal-title":"Sustain Cities Soc"},{"key":"506_CR127","doi-asserted-by":"publisher","first-page":"100982","DOI":"10.1016\/j.suscom.2024.100982","volume":"42","author":"K Valarmathi","year":"2024","unstructured":"Valarmathi K, Seetha J, Krishnamoorthy NV, Hema M, Ramkumar G (2024) An integrated energy storage framework with significant energy management and absorption mechanism for machine learning assisted electric vehicle application. Sustain Comp: Inform Syst 42:100982. https:\/\/doi.org\/10.1016\/j.suscom.2024.100982","journal-title":"Sustain Comp: Inform Syst"},{"key":"506_CR128","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1007\/s11708-020-0665-4","volume":"14","author":"J Wang","year":"2020","unstructured":"Wang J, Chen B, Li P et al (2020) Distributionally robust optimization of home energy management system based on receding horizon optimization. Front Energy 14:254\u2013266. https:\/\/doi.org\/10.1007\/s11708-020-0665-4","journal-title":"Front Energy"},{"key":"506_CR129","doi-asserted-by":"publisher","first-page":"101603","DOI":"10.1016\/j.jobe.2020.101603","volume":"33","author":"X Wang","year":"2021","unstructured":"Wang X, Mao X, Khodaei H (2021) A multi-objective home energy management system based on internet of things and optimization algorithms. J Build Eng 33:101603. https:\/\/doi.org\/10.1016\/j.jobe.2020.101603","journal-title":"J Build Eng"},{"key":"506_CR130","doi-asserted-by":"publisher","first-page":"114951","DOI":"10.1016\/j.enbuild.2024.114951","volume":"325","author":"Z Wu","year":"2024","unstructured":"Wu Z, Chen X, Lin Y, Wen J, Chen Y (2024) A smart home energy management system based on human activity recognition and deep reinforcement learning. Energy Build 325:114951. https:\/\/doi.org\/10.1016\/j.enbuild.2024.114951","journal-title":"Energy Build"},{"key":"506_CR131","doi-asserted-by":"publisher","first-page":"3501","DOI":"10.1016\/j.egyr.2024.03.003","volume":"11","author":"S Xiong","year":"2024","unstructured":"Xiong S, Liu D, Chen Y, Zhang Yi, Cai X (2024) A deep reinforcement learning approach based energy management strategy for home energy system considering the time-of-use price and real-time control of energy storage system. Energy Rep 11:3501\u20133508. https:\/\/doi.org\/10.1016\/j.egyr.2024.03.003","journal-title":"Energy Rep"},{"issue":"4","key":"506_CR132","doi-asserted-by":"publisher","first-page":"3201","DOI":"10.1109\/TSG.2020.2971427","volume":"11","author":"X Xu","year":"2020","unstructured":"Xu X, Jia Y, Xu Y, Xu Z, Chai S, Lai CS (2020) A multi-agent reinforcement learning-based data-driven method for home energy management. IEEE Trans Smart Grid 11(4):3201\u20133211. https:\/\/doi.org\/10.1109\/TSG.2020.2971427","journal-title":"IEEE Trans Smart Grid"},{"key":"506_CR133","doi-asserted-by":"publisher","first-page":"111689","DOI":"10.1016\/j.asoc.2024.111689","volume":"161","author":"R Xu","year":"2024","unstructured":"Xu R, Khan S, Jin W, Khan AN, Khan QW, Lim S, Kim DH (2024) A decentralized federated learning based interoperable and heterogeneity aware predictive optimization method for energy and comfort in smart homes environment. Appl Soft Comp 161:111689. https:\/\/doi.org\/10.1016\/j.asoc.2024.111689","journal-title":"Appl Soft Comp"},{"key":"506_CR134","doi-asserted-by":"publisher","first-page":"3385","DOI":"10.3390\/su12083385","volume":"12","author":"AS Yahaya","year":"2020","unstructured":"Yahaya AS, Javaid N, Alzahrani FA, Rehman A, Ullah I, Shahid A, Shafiq M (2020) Blockchain based sustainable local energy trading considering home energy management and demurrage mechanism. Sustainability 12:3385. https:\/\/doi.org\/10.3390\/su12083385","journal-title":"Sustainability"},{"key":"506_CR135","doi-asserted-by":"publisher","first-page":"1632","DOI":"10.1016\/j.enbuild.2017.11.064","volume":"158","author":"A Yoshida","year":"2018","unstructured":"Yoshida A, Jun Yoshikawa Yu, Fujimoto YA, Hayashi Y (2018) Stochastic receding horizon control minimizing mean-variance with demand forecasting for home EMSs. Energy Build 158:1632\u20131639. https:\/\/doi.org\/10.1016\/j.enbuild.2017.11.064","journal-title":"Energy Build"},{"key":"506_CR136","doi-asserted-by":"publisher","first-page":"1367","DOI":"10.1007\/s00500-023-08328-0","volume":"28","author":"H Youssef","year":"2024","unstructured":"Youssef H, Kamel S, Hassan MH et al (2024) An improved bald eagle search optimization algorithm for optimal home energy management systems. Soft Comput 28:1367\u20131390. https:\/\/doi.org\/10.1007\/s00500-023-08328-0","journal-title":"Soft Comput"},{"key":"506_CR137","doi-asserted-by":"publisher","first-page":"111055","DOI":"10.1016\/j.epsr.2024.111055","volume":"238","author":"J Yuan","year":"2025","unstructured":"Yuan J, Zeng X, Zhou J, Li J, Lv J, Chen R, Chen K, Yang W, Zhang Y (2025) Data-driven real-time home energy management system based on adaptive dynamic programming. Electric Power Syst Res 238:111055. https:\/\/doi.org\/10.1016\/j.epsr.2024.111055","journal-title":"Electric Power Syst Res"},{"key":"506_CR138","doi-asserted-by":"publisher","first-page":"119271","DOI":"10.1109\/ACCESS.2020.3005244","volume":"8","author":"U Zafar","year":"2020","unstructured":"Zafar U, Bayhan S, Sanfilippo A (2020) Home energy management system concepts, configurations, and technologies for the smart grid. IEEE Access 8:119271\u2013119286. https:\/\/doi.org\/10.1109\/ACCESS.2020.3005244","journal-title":"IEEE Access"},{"key":"506_CR139","doi-asserted-by":"publisher","first-page":"101054","DOI":"10.1016\/j.jobe.2019.101054","volume":"28","author":"A Zeng","year":"2020","unstructured":"Zeng A, Ho H, Yao Yu (2020) Prediction of building electricity usage using Gaussian process regression. J Build Eng 28:101054. https:\/\/doi.org\/10.1016\/j.jobe.2019.101054","journal-title":"J Build Eng"},{"key":"506_CR140","doi-asserted-by":"publisher","first-page":"106140","DOI":"10.1016\/j.ijepes.2020.106140","volume":"121","author":"S Zhang","year":"2020","unstructured":"Zhang S, Rong J, Wang B (2020) A privacy protection scheme of smart meter for decentralized smart home environment based on consortium blockchain. Int J Electr Power Energy Syst 121:106140. https:\/\/doi.org\/10.1016\/j.ijepes.2020.106140","journal-title":"Int J Electr Power Energy Syst"},{"key":"506_CR141","doi-asserted-by":"publisher","first-page":"122592","DOI":"10.1016\/j.apenergy.2023.122592","volume":"358","author":"C Zhang","year":"2024","unstructured":"Zhang C, Yang Yi, Wang Y, Qiu J, Zhao J (2024) Auction-based peer-to-peer energy trading considering echelon utilization of retired electric vehicle second-life batteries. Appl Energy 358:122592. https:\/\/doi.org\/10.1016\/j.apenergy.2023.122592","journal-title":"Appl Energy"},{"key":"506_CR142","doi-asserted-by":"publisher","unstructured":"Zhang F, Li D, Zhang Y, Chen B (2023) A secure distributed energy trading mechanism for residential communities based on smart contract. In\u00a02023 8th asia conference on power and electrical engineering (ACPEE)\u00a0(pp. 970-975). IEEE, Tianjin, China, 14-16 April 2023. https:\/\/doi.org\/10.1109\/ACPEE56931.2023.10135882","DOI":"10.1109\/ACPEE56931.2023.10135882"},{"key":"506_CR143","doi-asserted-by":"publisher","first-page":"76753","DOI":"10.1109\/ACCESS.2024.3407121","volume":"12","author":"R Zheng","year":"2024","unstructured":"Zheng R, Sumper A, Arag\u00fc\u00e9s-Pe\u00f1alba M, Galceran-Arellano S (2024) Advancing power system services with privacy-preserving federated learning techniques: a review. IEEE Access 12:76753\u201376780. https:\/\/doi.org\/10.1109\/ACCESS.2024.3407121","journal-title":"IEEE Access"},{"key":"506_CR144","doi-asserted-by":"publisher","first-page":"109604","DOI":"10.1016\/j.ijepes.2023.109604","volume":"155","author":"F Zobiri","year":"2024","unstructured":"Zobiri F, Gama M, Nikova S, Deconinck G (2024) Residential flexibility characterization and trading using secure multiparty computation. Int J Electr. Power Energy Syst 155:109604. https:\/\/doi.org\/10.1016\/j.ijepes.2023.109604","journal-title":"Int J Electr. Power Energy Syst"}],"container-title":["Process Integration and Optimization for Sustainability"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s41660-025-00506-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s41660-025-00506-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s41660-025-00506-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,20]],"date-time":"2025-08-20T07:23:10Z","timestamp":1755674590000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s41660-025-00506-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,1]]},"references-count":144,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["506"],"URL":"https:\/\/doi.org\/10.1007\/s41660-025-00506-x","relation":{},"ISSN":["2509-4238","2509-4246"],"issn-type":[{"value":"2509-4238","type":"print"},{"value":"2509-4246","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,1]]},"assertion":[{"value":"16 January 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 March 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 March 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 April 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}}]}}