Clustering of complementary electricity consumers based on their usage patterns

Sheng Ta Chen, Chi Lun Liu, Ming Hung Lee, Min Fung, Wei-Guang Teng

Research output: Contribution to journalConference article

Abstract

In the electricity market, the real-time balance of electricity generation and consumption is a main task. In view of this, power providers usually sign contracts with their critical consumers (i.e., usually large-scale industrial companies) for managing their capacity demands. On the other hand, aggregators group commercial and residential consumers, and integrate their demands to negotiate with power providers. With a proper grouping of numerous electricity consumers, aggregators help to ensure stable electric supply, and reduce the burden of managing many consumers. In this work, we thus propose a novel data clustering approach to group complementary consumers based on their usage patterns (i.e., daily electricity consumption curves.) Furthermore, we incorporate the technique of discrete wavelet transform to speed up the clustering process. Specifically, approximations reconstructed from only a few wavelet coefficients may precisely capture the shape of original usage patterns. Experimental results based on a real dataset show that our approach is promising in practical applications.

Original languageEnglish
Article number01006
JournalE3S Web of Conferences
Volume72
DOIs
Publication statusPublished - 2018 Dec 5
Event2018 International Conference on Electrical Engineering and Green Energy, CEEGE 2018 - Tokyo, Japan
Duration: 2018 Jun 12018 Jun 3

Fingerprint

wavelet
electricity
Electricity
electricity generation
transform
Discrete wavelet transforms
market
demand
electricity consumption
Industry
contract
consumer group
speed
Power markets

All Science Journal Classification (ASJC) codes

  • Environmental Science(all)
  • Energy(all)
  • Earth and Planetary Sciences(all)

Cite this

Chen, Sheng Ta ; Liu, Chi Lun ; Lee, Ming Hung ; Fung, Min ; Teng, Wei-Guang. / Clustering of complementary electricity consumers based on their usage patterns. In: E3S Web of Conferences. 2018 ; Vol. 72.
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abstract = "In the electricity market, the real-time balance of electricity generation and consumption is a main task. In view of this, power providers usually sign contracts with their critical consumers (i.e., usually large-scale industrial companies) for managing their capacity demands. On the other hand, aggregators group commercial and residential consumers, and integrate their demands to negotiate with power providers. With a proper grouping of numerous electricity consumers, aggregators help to ensure stable electric supply, and reduce the burden of managing many consumers. In this work, we thus propose a novel data clustering approach to group complementary consumers based on their usage patterns (i.e., daily electricity consumption curves.) Furthermore, we incorporate the technique of discrete wavelet transform to speed up the clustering process. Specifically, approximations reconstructed from only a few wavelet coefficients may precisely capture the shape of original usage patterns. Experimental results based on a real dataset show that our approach is promising in practical applications.",
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Clustering of complementary electricity consumers based on their usage patterns. / Chen, Sheng Ta; Liu, Chi Lun; Lee, Ming Hung; Fung, Min; Teng, Wei-Guang.

In: E3S Web of Conferences, Vol. 72, 01006, 05.12.2018.

Research output: Contribution to journalConference article

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AU - Chen, Sheng Ta

AU - Liu, Chi Lun

AU - Lee, Ming Hung

AU - Fung, Min

AU - Teng, Wei-Guang

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