Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Analysis and Application of Power Consumption Patterns for Changing the Power Consumption Behaviors

전력소비행위 변화를 위한 전력소비패턴 분석 및 적용

  • Jang, MinSeok (School of Computer Info. & Comm., Kunsan National University) ;
  • Nam, KwangWoo (School of Computer Info. & Comm., Kunsan National University) ;
  • Lee, YonSik (School of Computer Info. & Comm., Kunsan National University)
  • Received : 2021.03.16
  • Accepted : 2021.04.01
  • Published : 2021.04.30
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Abstract

In this paper, we extract the user's power consumption patterns, and model the optimal consumption patterns by applying the user's environment and emotion. Based on the comparative analysis of these two patterns, we present an efficient power consumption method through changes in the user's power consumption behavior. To extract significant consumption patterns, vector standardization and binary data transformation methods are used, and learning about the ensemble's ensemble with k-means clustering is applied, and applying the support factor according to the value of k. The optimal power consumption pattern model is generated by applying forced and emotion-based control based on the learning results for ensemble aggregates with relatively low average consumption. Through experiments, we validate that it can be applied to a variety of windows through the number or size adjustment of clusters to enable forced and emotion-based control according to the user's intentions by identifying the correlation between the number of clusters and the consistency ratios.

본 논문에서는 사용자의 전력소비패턴을 추출하고 사용자의 환경 및 감성을 적용한 최적 소비패턴을 모델링한 후, 이 두 가지의 패턴을 비교 적용하여 사용자의 전력소비행위 변화를 통한 전력의 효율적 사용 방법을 제시한다. 유의미한 소비패턴을 추출하기 위하여 벡터 표준화 및 이진 데이터 변환방법을 사용하고, k-평균 군집화를 적용한 앙상블의 합집합에 대한 학습과 k값에 따른 지지도를 적용하였으며, 최적 전력소비패턴 모델은 상대적 평균 소비량이 적은 앙상블 합집합에 대한 학습 결과를 기준으로 강제 및 감성 제어를 적용하여 생성하였다. 실험을 통하여 전력소비행위 변화 유도대상 추출 시 클러스터의 수와 일치율 간의 상관관계를 파악함으로써, 사용자의 의도에 따라 강제 및 감성 기반의 제어가 가능하도록 클러스터의 수나 크기 조절을 통한 다양한 윈도우에 적용할 수 있음을 검증하였다.

Keywords

Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2018R1D1A1B07051045) and supported by Academic Research Fund of Kunsan National University in 2020.

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