Prediction of SOx-NOx Emission in Coal-Fired Power Plant Using Deep Neural Network

Prediction of SOx-NOx Emission in Coal-Fired Power Plant Using Deep Neural Network

Coal has been used as the most commonly energy source for power plants since it is relatively cheap and readily available. Thanks to these benefits, many countries operate coal-fired power plants. However, the combustion of coal in the coal-fired power plant emits pollutants such as sulfur oxides (S...

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Bibliographic Details
Published in:Machines (Basel) Vol. 11; no. 12; p. 1042
Main Authors: So, Min Seop, Kibet, Duncan, Woo, Tae Kyeong, Kim, Seong-Joon, Shin, Jong-Ho
Format: Journal Article
Language:English
Published: Basel MDPI AG 01-12-2023
Subjects:
Artificial intelligence
Artificial neural networks
Boilers
Calories
Climate change
coal mixture
Coal-fired power plants
Combustion
deep neural network
Electricity generation
Emissions
Energy resources
feature importance
Fossil fuels
Global warming
Heat
Industrial plant emissions
Machine learning
Mixtures
Neural networks
Nitrogen
Nitrogen oxides
pollutant emission
Pollutants
Regulations
Sulfur
Sulfur oxides
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Summary:Coal has been used as the most commonly energy source for power plants since it is relatively cheap and readily available. Thanks to these benefits, many countries operate coal-fired power plants. However, the combustion of coal in the coal-fired power plant emits pollutants such as sulfur oxides (SOx) and nitrogen oxides (NOx) which are suspected to cause damage to the environment and also be harmful to humans. For this reason, most countries have been strengthening regulations on coal-consuming industries. Therefore, the coal-fired power plant should also follow these regulations. This study focuses on the prediction of harmful emissions when the coal is mixed with high-quality and low-quality coals during combustion in the coal-fired power plant. The emission of SOx and NOx is affected by the mixture ratio between high-quality and low-quality coals so it is very important to decide on the mixture ratio of coals. To decide the coal mixture, it is a prerequisite to predict the amount of SOx and NOx emission during combustion. To do this, this paper develops a deep neural network (DNN) model which can predict SOx and NOx emissions associated with coal properties when coals are mixed. The field data from a coal-fired power plant is used to train the model and it gives mean absolute percentage error (MAPE) of 7.1% and 5.68% for SOx and NOx prediction, respectively.
ISSN:2075-1702
2075-1702
DOI:10.3390/machines11121042