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Electric Load Clustering in Smart Grid: Methodologies, Applications, and Future Trends
- Source :
- Journal of Modern Power Systems and Clean Energy, Vol 9, Iss 2, Pp 237-252 (2021)
- Publication Year :
- 2021
- Publisher :
- Journal of Modern Power Systems and Clean Energy, 2021.
-
Abstract
- With the increasingly widespread of advanced metering infrastructure, electric load clustering is becoming more essential for its great potential in analytics of consumers' energy consumption patterns and preference through data mining. Moreover, a variety of electric load clustering techniques have been put into practice to obtain the distribution of load data, observe the characteristics of load clusters, and classify the components of the total load. This can give rise to the development of related techniques and research in the smart grid, such as demand-side response. This paper summarizes the basic concepts and the general process in electric load clustering. Several similarity measurements and five major categories in electric load clustering are then comprehensively summarized along with their advantages and disadvantages. Afterwards, eight indices widely used to evaluate the validity of electric load clustering are described. Finally, vital applications are discussed thoroughly along with future trends including the tariff design, anomaly detection, load forecasting, data security and big data, etc.
- Subjects :
- TK1001-1841
Electric load clustering
Electrical load
Renewable Energy, Sustainability and the Environment
Computer science
business.industry
cluster validity indicator
Big data
similarity measurement
TJ807-830
Energy Engineering and Power Technology
Data security
Energy consumption
computer.software_genre
Renewable energy sources
Production of electric energy or power. Powerplants. Central stations
Smart grid
Analytics
clustering technique
Anomaly detection
Data mining
smart grid
Cluster analysis
business
computer
Subjects
Details
- ISSN :
- 21965625
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- Journal of Modern Power Systems and Clean Energy
- Accession number :
- edsair.doi.dedup.....ccc2f0899e97be1b7c04ad59a09c0563