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Energies 2019, 12(6), 1036; https://doi.org/10.3390/en12061036

Combustion Optimization for Coal Fired Power Plant Boilers Based on Improved Distributed ELM and Distributed PSO

1
College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China
2
College of Information and Computer, Taiyuan University of Technology, Taiyuan 030024, China
*
Author to whom correspondence should be addressed.
Received: 23 February 2019 / Revised: 9 March 2019 / Accepted: 11 March 2019 / Published: 17 March 2019
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Abstract

Increasing the combustion efficiency of power plant boilers and reducing pollutant emissions are important for energy conservation and environmental protection. The power plant boiler combustion process is a complex multi-input/multi-output system, with a high degree of nonlinearity and strong coupling characteristics. It is necessary to optimize the boiler combustion model by means of artificial intelligence methods. However, the traditional intelligent algorithms cannot deal effectively with the massive and high dimensional power station data. In this paper, a distributed combustion optimization method for boilers is proposed. The MapReduce programming framework is used to parallelize the proposed algorithm model and improve its ability to deal with big data. An improved distributed extreme learning machine is used to establish the combustion system model aiming at boiler combustion efficiency and NOx emission. The distributed particle swarm optimization algorithm based on MapReduce is used to optimize the input parameters of boiler combustion model, and weighted coefficient method is used to solve the multi-objective optimization problem (boiler combustion efficiency and NOx emissions). According to the experimental analysis, the results show that the method can optimize the boiler combustion efficiency and NOx emissions by combining different weight coefficients as needed. View Full-Text
Keywords: boiler combustion model; MapReduce; distributed extreme learning machine; distributed particle swarm optimization; weight coefficient method boiler combustion model; MapReduce; distributed extreme learning machine; distributed particle swarm optimization; weight coefficient method
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Xu, X.; Chen, Q.; Ren, M.; Cheng, L.; Xie, J. Combustion Optimization for Coal Fired Power Plant Boilers Based on Improved Distributed ELM and Distributed PSO. Energies 2019, 12, 1036.

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