Abstract
This paper focuses on improving thermal efficiency and reducing unburned carbon in fly ash by optimizing operating parameters via a novel high-efficient swarm intelligence optimization algorithm (grey wolf optimizer algorithm, GWO) for coal-fired boiler. Mathematical models for thermal efficiency and unburned carbon in fly ash of the discussed boiler are established by artificial neural network (ANN). Based on the ANN models, the grey wolf optimizer algorithm is used to obtain higher thermal efficiency and lower unburned carbon by optimizing the operating parameters. Meanwhile, the comparisons between GWO and particle swarm optimization (PSO) and genetic algorithm (GA) show that GWO has superior performance to GA and PSO regarding the boiler combustion optimization. The proposed method can accurately optimize the boiler combustion performance, and its validity and feasibility have been experimentally validated. Additionally, a run of optimization takes a less time period, which is suitable for the real-time optimization.
Highlights
Motivation: In the recent years, the coal-fired utility boilers face the dual requirements of reducing operating costs, energy saving
The purpose of this paper is to propose a method for simultaneously optimizing thermal efficiency and unburned carbon of coal-fired utility boiler in a shorter period of time
These results clearly show that the grey wolf optimizer (GWO) algorithm is superior to the particle swarm optimization (PSO) and genetic algorithm (GA) algorithms
Summary
Motivation: In the recent years, the coal-fired utility boilers face the dual requirements of reducing operating costs, energy saving. Efficient combustion optimization technology has attracted increasing attention in related fields. In the ‘‘National Guideline on Medium and Long-term Program for Science and Technology Development’’, the State Council of China pointed out that energy saving is a top. In order to significantly improve the efficiency in the use of energy, overcoming technological snag is an urgent problem to solve. It is necessary to improve thermal efficiency and reduce unburned carbon in fly ash so as to use coal in a highly utilization and economically viable way. The thermal efficiency called here denotes the utilization of coal heat of boiler, which could represent boiler combustion conditions. As one of the main economic index, the level of unburned carbon reflects the
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