The DOI matches its Crossref record; 67 of the 72 references it cites were found in a registry or an index.
A review of electric load classification in smart grid environment
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In the citing paper
“Using ML, we can model and cluster individuals based on their climate knowledge, preferences, demographics, and consumption characteristics (e.g., [66,116,166,261,861]), and thus predict who will be most amenable to new technologies and sustainable behavior change.”
From Tackling climate change with machine learning (2023) · cites this paper as [861]
Citations
Cites
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FCM: The fuzzy c-means clustering algorithm
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Survey of Clustering Algorithms
Xu, R., & Wunsch, D. C. (2005) · IEEE Transactions on Neural Networks · doi:10.1109/tnn.2005.845141 · Cited by 6,399
A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters
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Hierarchical Clustering Schemes
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An Examination of Procedures for Determining the Number of Clusters in a Data Set
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A validity measure for fuzzy clustering
Xie, X., & Beni, G. (1991) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.85677 · Cited by 3,421
On cluster validity for the fuzzy c-means model
Pal, N. R., & Bezdek, J. C. (1995) · IEEE Transactions on Fuzzy Systems · doi:10.1109/91.413225 · Cited by 1,859
Research works printed but not linked: 9
- Zhao, 2011, Analysis and forecast of China's electricity load characteristics, China Electric Power Press
- Liu, 2011, Application of k-means clustering algorithm in load curve classification, Power System Protection and Control, 23, 73
- Ju, 2004, Studies on classification and synthesis of composite dynamic loads, Automation of Electric Power Systems, 28, 64
- Li, 2010, A classifying and synthesizing method of power consumer industry based on the daily load profile, Automation of Electric Power Systems, 34, 56
- Li PQ, Li XR, Chen HH, et al. The characteristics classification and synthesis of power load based on fuzzy clustering. In: Proceedings of the Csee; 2005. 25(24): p. 73–78.
- Li, 2008, Power consumers load profile clustering using the SOM neural network, Automation of Electric Power Systems, 15, 8
- Fukuyama Y, Sugeno M. A new method of choosing the number of cluster for the fuzzy c-means method. In: Proceedings of the fifth fuzzy systems symposium; 1989. p. 247–250.
- Liu, 2011, Application of k-means clustering algorithm in load curve classification, Power System Protection and Control, 23, 73
- Zhang ZH. Study on load classification in power system. Thesis. Tianjin University; 2007.
Cited by
Sorted by citations
Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges
Wang, Y., Chen, Q., Hong, T., & Kang, C. (2018) · IEEE Transactions on Smart Grid · doi:10.1109/tsg.2018.2818167 · Cited by 1,384
Big data driven smart energy management: from big data to big insights
Zhou, K., Fu, C., & Yang, S. (2016) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.11.050 · Cited by 841
Self-citationElectricity load forecasting: a systematic review
Nti, I. K., Teimeh, M., Nyarko‐Boateng, O., & Adekoya, A. F. (2020) · Journal of Electrical Systems and Information Technology · doi:10.1186/s43067-020-00021-8 · Cited by 400
Understanding household energy consumption behavior: The contribution of energy big data analytics
Zhou, K., & Yang, S. (2015) · Renewable and Sustainable Energy Reviews · doi:10.1016/j.rser.2015.12.001 · Cited by 406
Self-citationAhmad, T., Chen, H., Guo, Y., & Wang, J. (2018) · Energy and Buildings · doi:10.1016/j.enbuild.2018.01.017 · Cited by 404
Metadata
- Authors
- Zhou, K.-L., Yang, S.-L., & Shen, C.
- Affiliations
- Hefei University of Technology (CN)
- ORCID
- Shen, Chao
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2013-08
- Volume
- 24
- Pages
- 103-110
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W2171208762
- Cited by
- 254
- References
- 72
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 13 · 2023: 19 · 2022: 28 · 2021: 30 · 2020: 28 · 2019: 31 · 2018: 28 · 2017: 18 · 2016: 18 · 2015: 18 · 2014: 8 · 2013: 1
- FWCI
- 9.00
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Renewable and Sustainable Energy Reviews (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- 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 › Smart Grid and Power Systems
- Keywords
- smart grid, clustering algorithms, bad data detection, load forecasting, tariff setting, fuzzy c-means clustering
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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