Forecasting Methane Gas Concentration of LFG Power Plant Using Deep Learning

Seung-hyun Won; Dae-ho Seo; Dae-won Park

doi:10.32390/ksmer.2018.55.6.649

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2018 Vol.55, Issue 6 Preview Page Next Page

Technical Report

Forecasting Methane Gas Concentration of LFG Power Plant Using Deep Learning 딥러닝 기법을 활용한 매립가스 발전소 포집공의 메탄가스 농도 예측

31 December 2018. pp. 649-659

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Abstract

In this study, after operational data for a landfill gas power plant were collected, the methane gas concentration was predicted using a deep learning method. Concentrations of methane gas, carbon dioxide, hydrogen sulfide, oxygen concentration, as well as data related to the valve opening degree, air temperature and humidity were collected from 23 pipeline bases for 88 matches from January to November 2017. After the deep learning model learned the collected data, methane gas concentration was estimated by applying other data. Our study yielded extremely accurate estimation results for all of the 23 pipeline bases.

Keywords

Landfill gas

Power plant

Deep learning

Landfill

본 연구는 매립장 매립가스 발전소를 대상으로 발전소 운영 데이터들을 수집 후, 딥러닝(Deep Learning) 기법을 적용하여 향후 메탄가스 농도를 예측하였다. 2017년 1월부터 11월까지 88일치에 대해서 23개 포집공에서 메탄가스 농도, 이산화탄소 농도, 황화수소 농도, 산소 농도, 밸브 개방정도, 기온, 습도 데이터를 수집하였다. 수집 데이터로 딥러닝 모델을 학습한 후 실제 데이터와 비교하였다. 추정 결과 23개 포집공 모두에서 매우 정확한 추정결과를 보였다.

키워드

매립가스

발전소

딥러닝

매립장

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Information

Publisher :The Korean Society of Mineral and Energy Resources Engineers
Publisher(Ko) :한국자원공학회
Journal Title :Journal of the Korean Society of Mineral and Energy Resources Engineers
Journal Title(Ko) :한국자원공학회지
Volume : 55
No :6
Pages :649-659
Received Date : 2018-10-12
Revised Date : 2018-12-19
Accepted Date : 2018-12-20
DOI :https://doi.org/10.32390/ksmer.2018.55.6.649

Journal of the Korean Society of Mineral and Energy Resources EngineersISSN:2288-0291(Print) 2288-2790(Online)한국자원공학회

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