[HTML][HTML] Machine Learning for Advanced Emission Monitoring and Reduction Strategies in Fossil Fuel Power Plants
Fossil fuel power plants are a significant contributor to global carbon dioxide (CO2) and
nitrogen oxide (NOx) emissions. Accurate monitoring and effective reduction of these …
nitrogen oxide (NOx) emissions. Accurate monitoring and effective reduction of these …
Artificial intelligence for control and optimization of boilers' performance and emissions: A review
Burning fossil fuels is a major concern for global warming control. In Saudi Arabia, steam
power plants that relay on boilers to produce the steam accounted for around 50% of the …
power plants that relay on boilers to produce the steam accounted for around 50% of the …
Prediction of the NOx emissions from thermal power plant using long-short term memory neural network
G Yang, Y Wang, X Li - Energy, 2020 - Elsevier
Coal combustion in thermal power plant is the main source of the NO x emission. An
effective prediction model should be established for reducing NO x emission. This paper …
effective prediction model should be established for reducing NO x emission. This paper …
Online state of charge and model parameter co-estimation based on a novel multi-timescale estimator for vanadium redox flow battery
A key function of battery management system (BMS) is to provide accurate information of the
state of charge (SOC) in real time, and this depends directly on the precise model …
state of charge (SOC) in real time, and this depends directly on the precise model …
Dynamic modeling for NOx emission sequence prediction of SCR system outlet based on sequence to sequence long short-term memory network
P Xie, M Gao, H Zhang, Y Niu, X Wang - Energy, 2020 - Elsevier
As environmental protection policies become more stringent, lower and lower NOx emission
targets are required. Accurate NOx concentration prediction model plays an important role in …
targets are required. Accurate NOx concentration prediction model plays an important role in …
Combustion optimization of ultra supercritical boiler based on artificial intelligence
A method for optimizing the combustion in an ultra-supercritical boiler is developed and
evaluated in a 660 MWe ultra-supercritical coal fired power plant. In this method, Artificial …
evaluated in a 660 MWe ultra-supercritical coal fired power plant. In this method, Artificial …
Gradient boosting decision tree in the prediction of NOx emission of waste incineration
This paper investigates the real-time prediction of nitrogen oxides (NO x) emission by using
around 17000 samples involved in a collection of three-day real data from a waste …
around 17000 samples involved in a collection of three-day real data from a waste …
Flame images for oxygen content prediction of combustion systems using DBN
As an increasingly popular method in the machine learning field, deep learning is applied to
industrial combustion processes in this work. Using easily available color flame images …
industrial combustion processes in this work. Using easily available color flame images …
Prediction of oxygen-enriched combustion and emission performance on a spark ignition engine using artificial neural networks
P Sun, J Zhang, W Dong, D Li, X Yu - Applied Energy, 2023 - Elsevier
The experiment about gasoline fuel plus oxygen-enriched combustion (OEC) technology is
conducted on a combined injection engine in this paper. OEC is an effective in-cylinder …
conducted on a combined injection engine in this paper. OEC is an effective in-cylinder …
Modeling and reduction of NOX emissions for a 700 MW coal-fired boiler with the advanced machine learning method
P Tan, J Xia, C Zhang, Q Fang, G Chen - Energy, 2016 - Elsevier
This paper focuses on modeling and reducing NO X emissions for a coal-fired boilers with
advanced machine learning approaches. The novel ELM (extreme learning machine) model …
advanced machine learning approaches. The novel ELM (extreme learning machine) model …