Appliance level energy characterization of residential electricity demand: prospects, challenges and recommendations
Open accessAbstract
The advent of information and communication technologies has paved the way for smart cities. Residential customers are the major consumers of electrical energy in such cities. Smart meters gather the energy consumption behavior of consumers at the aggregate/household level. Characterization of aggregate demand data has several advantages but significant benefits in terms of energy sustainability require Appliance Level Energy Characterization (ALEC). Various solutions for ALEC rely on sensors, smart plugs, smart appliances, smart meters and/or energy disaggregation algorithms but smart meters with built-in energy disaggregation algorithms seem to be the most scalable option. This work is one of the pioneering contributions to present comprehensive applications and prospects of ALEC for smart residential communities. It also links these applications with 2050 decarbonization pathways and various United Nations (UN) sustainable development goals (SDGs). Prospective uses of ALEC in diverse fields such as power systems, health care, the social sciences, economics, surveillance, marketing, appliance manufacturing, technology development, etc. are highlighted. Moreover, the requirements and challenges hindering the large-scale deployment of the ALEC frameworks are outlined with some recommendations and open research directions. It is envisaged that ALEC of residential electricity can be exploited not only for achieving 2050 decarbonization targets but also for several 2030 SDGs. This work will provide a one-stop source of information on ALEC and will open the doors of cooperation among various stakeholders of smart cities to achieve long-term SDGs.
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Blockchain informs consumers about less-efficient appliances, enabling improved consumption behavior and reduced carbon emissions, and monitors compliance with environmental standards via product traceability, decreasing resource inefficiencies and losses in supply chains.
“Moreover, Blockchain informs consumers and users about the use of less-efficient appliances. It enables them to improve their consumption behavior and thus reduce their carbon emissions [268], in addition to monitoring compliance with environmental standards by utilizing product traceability that can decrease resource inefficiencies and losses at different supply chain stages [269].”
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Cited by
Sorted by citations
Bibri, S. E., Krogstie, J., Kaboli, A., & Alahi, A. (2024) · Environmental Science and Ecotechnology · doi:10.1016/j.ese.2023.100330 · Cited by 536 · see citing works
Bibri, S. E., Alexandre, A., Sharifi, A., & Krogstie, J. (2023) · Energy Informatics · doi:10.1186/s42162-023-00259-2 · Cited by 299 · see citing works
- Authors
- Liaqat, R., Sajjad, I. A., Waseem, M., & Alhelou, H. H.
- Affiliations
- University of Engineering and Technology Taxila (PK)
- University College Dublin (IE)
- Corresponding author
- Alhelou, Hassan Haes
- Venue
- IEEE Access
- Published
- 2021
- Volume
- 9
- Pages
- 148676-148697
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W3210989012
- Cited by
- 39
- References
- 160
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 13 · 2023: 11 · 2022: 5
- FWCI
- 2.13
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- IEEE Access (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Greater South Information System
- Funders
- University of Engineering and Technology, Lahore
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Energy Load and Power Forecasting
- Physical Sciences › Engineering › Electrical and Electronic Engineering › IoT-based Smart Home Systems
- Keywords
- residential electricity demand, non-intrusive load monitoring, smart meters, smart cities, decarbonization pathways, Sustainable Development Goals, smart plugs, smart appliances, energy consumption behavior
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