{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T22:49:59Z","timestamp":1762642199820,"version":"build-2065373602"},"reference-count":27,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2019,4,2]],"date-time":"2019-04-02T00:00:00Z","timestamp":1554163200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51877134"],"award-info":[{"award-number":["51877134"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005311","name":"China Southern Power Grid","doi-asserted-by":"publisher","award":["GDKJXM20161607"],"award-info":[{"award-number":["GDKJXM20161607"]}],"id":[{"id":"10.13039\/501100005311","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>With the development of techniques, such as the Internet of Things (IoT) and edge computing, home energy management systems (HEMS) have been widely implemented to improve the electric energy efficiency of customers. In order to automatically optimize electric appliances\u2019 operation schedules, this paper considers how to quantitatively evaluate a customer\u2019s comfort satisfaction in energy-saving programs, and how to formulate the optimal energy-saving model based on this satisfaction evaluation. First, the paper categorizes the utility functions of current electric appliances into two types; time-sensitive utilities and temperature-sensitive utilities, which cover nearly all kinds of electric appliances in HEMS. Furthermore, considering the bounded rationality of customers, a novel concept called the energy-saving cost is defined by incorporating prospect theory in behavioral economics into general utility functions. The proposed energy-saving cost depicts the comfort loss risk for customers when their HEMS schedules the operation status of appliances, which is able to be set by residents as a coefficient in the automatic energy-saving program. An optimization model is formulated based on minimizing energy consumption. Because the energy-saving cost has already been evaluated in the context of the satisfaction of customers, the formulation of the optimization program is very simple and has high computational efficiency. The case study included in this paper is first performed on a general simulation system. Then, a case study is set up based on real field tests from a pilot project in Guangdong province, China, in which air-conditioners, lighting, and some other popular electric appliances were included. The total energy-saving rate reached 65.5% after the proposed energy-saving program was deployed in our project. The benchmark test shows our optimal strategy is able to considerably save electrical energy for residents while ensuring customers\u2019 comfort satisfaction is maintained.<\/jats:p>","DOI":"10.3390\/fi11040088","type":"journal-article","created":{"date-parts":[[2019,4,3]],"date-time":"2019-04-03T03:39:28Z","timestamp":1554262768000},"page":"88","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["An Optimal Energy-Saving Strategy for Home Energy Management Systems with Bounded Customer Rationality"],"prefix":"10.3390","volume":"11","author":[{"given":"Guoying","family":"Lin","sequence":"first","affiliation":[{"name":"Metrology Center of Guangdong Power Grid Co., Ltd., Guangzhou 510080, China"}]},{"given":"Yuyao","family":"Yang","sequence":"additional","affiliation":[{"name":"Metrology Center of Guangdong Power Grid Co., Ltd., Guangzhou 510080, China"}]},{"given":"Feng","family":"Pan","sequence":"additional","affiliation":[{"name":"Metrology Center of Guangdong Power Grid Co., Ltd., Guangzhou 510080, China"}]},{"given":"Sijian","family":"Zhang","sequence":"additional","affiliation":[{"name":"Metrology Center of Guangdong Power Grid Co., Ltd., Guangzhou 510080, China"}]},{"given":"Fen","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Department of Electrical Engineering, Shanghai Jiao-Tong University, Shanghai 200240, China"}]},{"given":"Shuai","family":"Fan","sequence":"additional","affiliation":[{"name":"Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Department of Electrical Engineering, Shanghai Jiao-Tong University, Shanghai 200240, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2565","DOI":"10.1109\/TSG.2016.2529424","article-title":"Modeling and valuation of residential demand flexibility for renewable energy integration","volume":"8","author":"Gottwalt","year":"2017","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Jia, K., Wang, Z., Fan, S., Zhai, S., and He, G. (2019). Data-Centric Approach: A Novel Systematic Approach for Cyber Physical System Heterogeneity in Smart Grid. IEEJ Trans. Electr. Electron. Eng.","DOI":"10.1002\/tee.22861"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Pecorella, T., Pierucci, L., and Nizzi, F. (2018). \u201cNetwork Sentiment\u201d Framework to Improve Security and Privacy for Smart Home. Future Internet, 10.","DOI":"10.3390\/fi10120125"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"He, J., Xiao, Q., He, P., and Pathan, M.S. (2017). An Adaptive Privacy Protection Method for Smart Home Environments Using Supervised Learning. Future Internet, 9.","DOI":"10.3390\/fi9010007"},{"key":"ref_5","first-page":"20","article-title":"Collaborative Optimal Operation Strategy for Decentralized Electric Heating Loads","volume":"41","author":"Fan","year":"2017","journal-title":"Autom. Electr. Power Syst."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Alonso, S., Mor\u00e1n, A., Prada, M.\u00c1., Reguera, P., Fuertes, J.J., and Dom\u00ednguez, M. (2019). A Data-Driven Approach for Enhancing the Efficiency in Chiller Plants: A Hospital Case Study. Energies, 12.","DOI":"10.3390\/en12050827"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Gomes, L., Ramos, C., Jozi, A., Serra, B., Paiva, L., and Vale, Z. (2019). IoH: A Platform for the Intelligence of Home with a Context Awareness and Ambient Intelligence Approach. Future Internet, 11.","DOI":"10.3390\/fi11030058"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Pan, F., Lin, G., Lin, J., Fan, S., He, G., and Jia, K. (2018, January 22\u201325). Design and Simulation of the Autonomous Decentralized Dispatching System of Generalized Demand Side Resources. Proceedings of the 2018 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), Singapore.","DOI":"10.1109\/ISGT-Asia.2018.8467786"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Jia, K., Xiao, J., Fan, S., and He, G. (2018). A MQTT\/MQTT-SN-Based User Energy Management System for Automated Residential Demand Response: Formal Verification and Cyber-Physical Performance Evaluation. Appl. Sci., 8.","DOI":"10.3390\/app8071035"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/j.buildenv.2018.01.013","article-title":"Indoor environmental quality in social housing: A literature review","volume":"131","author":"Siegel","year":"2018","journal-title":"Build. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1177\/1351010X17740477","article-title":"Thermal and acoustic performance expectations on timber buildings","volume":"24","author":"Caniato","year":"2017","journal-title":"Build. Acoust."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1080\/09613218.2010.495216","article-title":"Understanding occupants: Feedback techniques for large-scale low-carbon domestic refurbishments","volume":"38","author":"Gupta","year":"2010","journal-title":"Build. Res. Inf."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Fan, S., He, G., Jia, K., and Wang, Z. (2018). A Novel Distributed Large-Scale Demand Response Scheme in High Proportion Renewable Energy Sources Integration Power Systems. Appl. Sci., 8.","DOI":"10.3390\/app8030452"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Fan, S., He, G., Guo, B., and Wang, Z. (2018, January 8\u201310). A user energy management system (UEMS)-based microgrid economic dispatch model. Proceedings of the IEEE Asia-Pacific Power & Energy Engineering Conference, Bangalore, India.","DOI":"10.1109\/APPEEC.2017.8308915"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.epsr.2016.03.026","article-title":"A novel economic model for price-based demand response","volume":"135","author":"Mohajeryami","year":"2016","journal-title":"Electr. Power Syst. Res."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Lin, C.-M., Wu, C.-Y., Tseng, K.-Y., Ku, C.-C., and Lin, S.-F. (2019). Applying Two-Stage Differential Evolution for Energy Saving in Optimal Chiller Loading. Energies, 12.","DOI":"10.3390\/en12040622"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Odkhuu, N., Lee, K.-B., A. Ahmed, M., and Kim, Y.-C. (2018). Optimal Energy Management of V2B with RES and ESS for Peak Load Minimization. Appl. Sci., 8.","DOI":"10.3390\/app8112125"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1007\/BF00122574","article-title":"Advances in prospect theory: Cumulative representation of uncertainty","volume":"5","author":"Tversky","year":"1992","journal-title":"J. Risk Uncertain."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Jia, K., He, G., Yang, L., and Zhou, N. (2018, January 21\u201325). Preference Analyses of Residential Appliances in Demand Response: A Novel Perspective Based on Behavioral Economics. Proceedings of the 2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), Sarajevo, Bosnia and Herzegovina.","DOI":"10.1109\/ISGTEurope.2018.8571721"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Jia, K., He, G., Zhai, S., Lin, G., Lu, S., and Pan, F. (2018, January 22\u201325). Utility-Based Real-Time Estimation of Appliance Dispatching Cost for Residential Energy Management. Proceedings of the 2018 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), Singapore.","DOI":"10.1109\/ISGT-Asia.2018.8467946"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Wang, J., Fang, K., Dai, J., Yang, Y., and Zhou, Y. (2017). Optimal Scheduling of Industrial Task-Continuous Load Management for Smart Power Utilization. Appl. Sci., 7.","DOI":"10.3390\/app7030281"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"217","DOI":"10.3390\/en8010217","article-title":"Optimal Scheduling of Domestic Appliances via MILP","volume":"8","author":"Bradac","year":"2015","journal-title":"Energies"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Singh, M., and Jha, R.C. (2019). Object-Oriented Usability Indices for Multi-Objective Demand Side Management Using Teaching-Learning Based Optimization. Energies, 12.","DOI":"10.3390\/en12030370"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Dunkelberg, H., Sondermann, M., Meschede, H., and Hesselbach, J. (2019). Assessment of Flexibilisation Potential by Changing Energy Sources Using Monte Carlo Simulation. Energies, 12.","DOI":"10.3390\/en12040711"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Lin, G., Pan, F., Yang, Y., Yang, L., He, G., and Fan, S. (2018, January 22\u201325). The Pattern Recognition of Residential Power Consumption Based on HMM. Proceedings of the 2018 IEEE Innovative Smart Grid Technologies\u2014Asia (ISGT Asia), Singapore.","DOI":"10.1109\/ISGT-Asia.2018.8467905"},{"key":"ref_26","unstructured":"Liu, M., Wu, Y., Wu, R., Fan, S., He, G., and Jia, K. (2017). User-Side Self-Approximate Optimization Method and Its Application Based on Power Utility and Electrical Appliance Parameter Characterization. Electr. Power Constr."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"420","DOI":"10.1109\/TSG.2013.2278477","article-title":"Household Energy Consumption Segmentation Using Hourly Data","volume":"5","author":"Kwac","year":"2014","journal-title":"IEEE Trans. Smart Grid"}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/11\/4\/88\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:42:21Z","timestamp":1760186541000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/11\/4\/88"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,2]]},"references-count":27,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2019,4]]}},"alternative-id":["fi11040088"],"URL":"https:\/\/doi.org\/10.3390\/fi11040088","relation":{},"ISSN":["1999-5903"],"issn-type":[{"type":"electronic","value":"1999-5903"}],"subject":[],"published":{"date-parts":[[2019,4,2]]}}}