Information and Communications Technology and Policy

Information and Communications Technology and Policy

Information and Communications Technology and Policy ›› 2021, Vol. 47 ›› Issue (3): 76-82.doi: 10.12267/j.issn.2096-5931.2021.03.013

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Genetic optimization model of power supply coal consumption for thermal power unit based on random forest

SUN Yongping1, WANG Lifeng2, ZHANG Zhenwei1, YANG Qin1   

  1. 1. Zhejiang Energy Group Research and Development, Hangzhou 311121, China;
    2. Shandong Luneng Software Technology Co., Ltd., Jinan 250001, China
  • Online:2021-03-15 Published:2021-03-31

Abstract: Since the coal consumption of thermal power plants is related to their capacity, it is necessary to optimize coal consumption in order to increase production capacity and revenue. The random forest regression algorithm can mine the regression model of coal consumption, main steam pressure, main steam temperature and other related parameters from historical data, and then propose the optimal operation strategy with the goal of the lowest coal consumption. Through the test of one unit, the results show that the genetic optimization model of coal consumption for power supply of thermal power units based on random forest regression algorithm can reduce coal consumption for power supply.

Key words: thermal power unit, power supply coal consumption, random forest algorithm, genetic optimization