Validation of Building Power Consumption Prediction Accuracy According to Frozen Number of Layers based on Transfer Learning

Yusun Ahn; Kyung-Il Chin; Yong-Jun Lee

doi:10.7836/kses.2020.40.6.151

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2020 Vol.40, Issue 6 Preview Page Next Page

Research Article

Validation of Building Power Consumption Prediction Accuracy According to Frozen Number of Layers based on Transfer Learning 전이 학습 기반 고정된 레이어 수에 따른 건물 전력 소비량 예측 정확도 검증

30 December 2020. pp. 151-160

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Abstract

Owing to recent advances in data-driven technologies, prediction models can now be utilized in various fields such as energy consumption prediction. Among them, transfer learning, which enables prediction using data collected for a short term, is actively gaining ground. In the field of building energy, attention is focused on predicting the power consumption of buildings with the development of smart grids and micro-grids. The purpose of this study is to implement a machine learning (ML) method using the transfer learning algorithm that enables the prediction of energy consumption of the buildings using data collected for a short-term period. This study also validates the accuracy of the predicted energy consumption by adjusting the number of frozen layers based on the input parameters used in the ML method. A total of 5 layers were set, and the frozen layers were increased from 0 to 5. In addition, to validate the prediction rate of the transfer learning algorithm, only the existing ML model was used. As a result, when 0 through 3 layers were fixed, the accuracy criterion tended to be met. In contrast, when the 4-5 layers were reflected, the accuracy criterion was not met. It should also be noted that the model without using transfer learning showed poor accuracy.

Keywords

Transfer learning

Building power consumption

Prediction

LSTM(Long short-term memory)

Frozen layer

키워드

전이 학습

건물 전력 소비량

예측

LSTM(Long short-term memory)

고정 레이어

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Information

Publisher :Korean Solar Energy Society
Publisher(Ko) :한국태양에너지학회
Journal Title :Journal of the Korean Solar Energy Society
Journal Title(Ko) :한국태양에너지학회 논문집
Volume : 40
No :6
Pages :151-160
Received Date : 2020-11-20
Revised Date : 2020-12-04
Accepted Date : 2020-12-04
DOI :https://doi.org/10.7836/kses.2020.40.6.151

Journal of the Korean Solar Energy Society ISSN:1598-6411(Print) 2508-3562(Online) 한국태양에너지학회 논문집

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