Open Access

ARTICLE

Analysis of Electricity Consumption Pattern Clustering and Electricity Consumption Behavior

Liang Zhu¹, Junyang Liu¹, Chen Hu¹, Yanli Zhi², Yupeng Liu^3,*

1 Power Supply Service Management Center, State Grid Jiangxi Electric Power Corporation Limited, Nanchang, 330077, China
2 State Grid Jiangxi Electric Power Corporation Limited, Nanchang, 330077, China
3 College of Electrical and Information Engineering, Hunan University, Changsha, 410082, China

* Corresponding Author: Yupeng Liu. Email:

Energy Engineering 2024, 121(9), 2639-2653. https://doi.org/10.32604/ee.2024.041441

Received 23 April 2023; Accepted 08 September 2023; Issue published 19 August 2024

Abstract

Studying user electricity consumption behavior is crucial for understanding their power usage patterns. However, the traditional clustering methods fail to identify emerging types of electricity consumption behavior. To address this issue, this paper introduces a statistical analysis of clusters and evaluates the set of indicators for power usage patterns. The fuzzy C-means clustering algorithm is then used to analyze 6 months of electricity consumption data in 2017 from energy storage equipment, agricultural drainage irrigation, port shore power, and electric vehicles. Finally, the proposed method is validated through experiments, where the Davies-Bouldin index and profile coefficient are calculated and compared. Experiments showed that the optimal number of clusters is 4. This study demonstrates the potential of using a fuzzy C-means clustering algorithm in identifying emerging types of electricity consumption behavior, which can help power system operators and policymakers to make informed decisions and improve energy efficiency.

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Keywords

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