Household power usage pattern filtering-based residential electricity plan recommender system
Author
Abstract
Suggested Citation
DOI: 10.1016/j.apenergy.2021.117191
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Gupta, Ankit & Mehrotra, Kishan G. & Mohan, Chilukuri, 2010. "A clustering-based discretization for supervised learning," Statistics & Probability Letters, Elsevier, vol. 80(9-10), pages 816-824, May.
- Afzalan, Milad & Jazizadeh, Farrokh, 2019. "Residential loads flexibility potential for demand response using energy consumption patterns and user segments," Applied Energy, Elsevier, vol. 254(C).
- Tsai, Men-Shen & Lin, Yu-Hsiu, 2012. "Modern development of an Adaptive Non-Intrusive Appliance Load Monitoring system in electricity energy conservation," Applied Energy, Elsevier, vol. 96(C), pages 55-73.
- Ogunjuyigbe, A.S.O. & Ayodele, T.R. & Akinola, O.A., 2017. "User satisfaction-induced demand side load management in residential buildings with user budget constraint," Applied Energy, Elsevier, vol. 187(C), pages 352-366.
- Pamulapati, Trinadh & Mallipeddi, Rammohan & Lee, Minho, 2020. "Multi-objective home appliance scheduling with implicit and interactive user satisfaction modelling," Applied Energy, Elsevier, vol. 267(C).
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Qiu, Dawei & Wang, Yi & Wang, Junkai & Jiang, Chuanwen & Strbac, Goran, 2023. "Personalized retail pricing design for smart metering consumers in electricity market," Applied Energy, Elsevier, vol. 348(C).
- vom Scheidt, Frederik & Staudt, Philipp, 2024. "A data-driven Recommendation Tool for Sustainable Utility Service Bundles," Applied Energy, Elsevier, vol. 353(PB).
- Agyeman, Stephen Duah & Lin, Boqiang, 2023. "Electricity industry (de)regulation and innovation in negative-emission technologies: How do market liberalization influences climate change mitigation?," Energy, Elsevier, vol. 270(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Sara Ayub & Shahrin Md Ayob & Chee Wei Tan & Saad M. Arif & Muhammad Taimoor & Lubna Aziz & Abba Lawan Bukar & Qasem Al-Tashi & Razman Ayop, 2023. "Multi-Criteria Energy Management with Preference Induced Load Scheduling Using Grey Wolf Optimizer," Sustainability, MDPI, vol. 15(2), pages 1-38, January.
- Oladayo S. Ajani & Abhishek Kumar & Rammohan Mallipeddi & Swagatam Das & Ponnuthurai Nagaratnam Suganthan, 2022. "Benchmarking Optimization-Based Energy Disaggregation Algorithms," Energies, MDPI, vol. 15(5), pages 1-19, February.
- Wu, Junqi & Niu, Zhibin & Li, Xiang & Huang, Lizhen & Nielsen, Per Sieverts & Liu, Xiufeng, 2023. "Understanding multi-scale spatiotemporal energy consumption data: A visual analysis approach," Energy, Elsevier, vol. 263(PD).
- Diaz, Cesar & Ruiz, Fredy & Patino, Diego, 2017. "Modeling and control of water booster pressure systems as flexible loads for demand response," Applied Energy, Elsevier, vol. 204(C), pages 106-116.
- Jia, Kunqi & Guo, Ge & Xiao, Jucheng & Zhou, Huan & Wang, Zhihua & He, Guangyu, 2019. "Data compression approach for the home energy management system," Applied Energy, Elsevier, vol. 247(C), pages 643-656.
- Liu, Hong & Zhao, Yue & Gu, Chenghong & Ge, Shaoyun & Yang, Zan, 2021. "Adjustable capability of the distributed energy system: Definition, framework, and evaluation model," Energy, Elsevier, vol. 222(C).
- Zheng, Ling & Zhou, Bin & Cao, Yijia & Wing Or, Siu & Li, Yong & Wing Chan, Ka, 2022. "Hierarchical distributed multi-energy demand response for coordinated operation of building clusters," Applied Energy, Elsevier, vol. 308(C).
- Zeng, Huibin & Shao, Bilin & Dai, Hongbin & Yan, Yichuan & Tian, Ning, 2023. "Natural gas demand response strategy considering user satisfaction and load volatility under dynamic pricing," Energy, Elsevier, vol. 277(C).
- Wu, Xiao & Yang, Lihua & Zheng, Bingle, 2024. "Joint capacity configuration and demand response optimization of integrated energy system considering economic and dynamic control performance," Energy, Elsevier, vol. 301(C).
- Jeewon Park & Oladayo S. Ajani & Rammohan Mallipeddi, 2023. "Optimization-Based Energy Disaggregation: A Constrained Multi-Objective Approach," Mathematics, MDPI, vol. 11(3), pages 1-13, January.
- Davarzani, Sima & Pisica, Ioana & Taylor, Gareth A. & Munisami, Kevin J., 2021. "Residential Demand Response Strategies and Applications in Active Distribution Network Management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
- Liu, Bo & Luan, Wenpeng & Yu, Yixin, 2017. "Dynamic time warping based non-intrusive load transient identification," Applied Energy, Elsevier, vol. 195(C), pages 634-645.
- Song, Chunhe & Jing, Wei & Zeng, Peng & Rosenberg, Catherine, 2017. "An analysis on the energy consumption of circulating pumps of residential swimming pools for peak load management," Applied Energy, Elsevier, vol. 195(C), pages 1-12.
- Nguyen, Hai-Tra & Safder, Usman & Loy-Benitez, Jorge & Yoo, ChangKyoo, 2022. "Optimal demand side management scheduling-based bidirectional regulation of energy distribution network for multi-residential demand response with self-produced renewable energy," Applied Energy, Elsevier, vol. 322(C).
- Jaka Rober & Leon Maruša & Miloš Beković, 2023. "A Machine Learning Application for the Energy Flexibility Assessment of a Distribution Network for Consumers," Energies, MDPI, vol. 16(17), pages 1-20, August.
- Chen, Xiao & Zanocco, Chad & Flora, June & Rajagopal, Ram, 2022. "Constructing dynamic residential energy lifestyles using Latent Dirichlet Allocation," Applied Energy, Elsevier, vol. 318(C).
- Liu, Yinyan & Ma, Jin & Xing, Xinjie & Liu, Xinglu & Wang, Wei, 2022. "A home energy management system incorporating data-driven uncertainty-aware user preference," Applied Energy, Elsevier, vol. 326(C).
- Lu, Qing & Lü, Shuaikang & Leng, Yajun, 2019. "A Nash-Stackelberg game approach in regional energy market considering users’ integrated demand response," Energy, Elsevier, vol. 175(C), pages 456-470.
- Eunjung Lee & Keon Baek & Jinho Kim, 2020. "Evaluation of Demand Response Potential Flexibility in the Industry Based on a Data-Driven Approach," Energies, MDPI, vol. 13(23), pages 1-12, December.
- Woo, C.K. & Sreedharan, P. & Hargreaves, J. & Kahrl, F. & Wang, J. & Horowitz, I., 2014. "A review of electricity product differentiation," Applied Energy, Elsevier, vol. 114(C), pages 262-272.
More about this item
Keywords
Collaborative filtering (CF); Recommender system (RS); Electricity plan recommender system (EPRS);All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:298:y:2021:i:c:s0306261921006176. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.