Nitrogen Oxide (NOx) Emissions Prediction of Gas Turbine in Coal-Fired Power Plant Using Online Learning Method

Nitrogen oxides(NOx) in coal-fired power plants are significant contributors to air pollution, influencing the formation of ozone and fine particulate matter, thereby adversely affecting health. Therefore, accurate prediction of NOx emissions is essential. Existing researches have mainly performed based on off-line learning methods, leading to poor prediction performance with the limited training dataset. This paper proposes the online learning model of online support vector regression to predict NOx emissions from coal-fired power plants. Online learning model, which updates a model whenever new observations come out, demonstrates high prediction accuracy even when initial data is scarce. The experimental results showed that the performance of online learning prediction was better than existing off-line learning methods. The results indicated online learning method is a valuable tool for predicting NOx emissions, especially in situations where initial data is limited and data is continuously updated in real-time.