Life cycle assessment of coal-fired power plants and sensitivity analysis of CO2 emissions from power generation side

2017 2nd Asia Conference on Power and Electrical Engineering

能源学;电工学

Yin, Libao^1 ; Liao, Yanfen^2 ; Zhou, Lianjie^1 ; Wang, Zhao^2 ; Ma, Xiaoqian^2

Electric Power Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou

510080, China^1

School of Electric Power, South China University of Technology, Guangzhou

510640, China^2

关键词: BP neural networks;    Carbon balance method;    Coal-fired power plant;    Electric energies;    Guangdong Province;    Life Cycle Assessment (LCA);    Pollutant emission;    Total energy consumption;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/199/1/012055/pdf
DOI  :  10.1088/1757-899X/199/1/012055

来源: IOP

【 摘 要 】

The life cycle assessment and environmental impacts of a 1000MW coal-fired power plant were carried out in this paper. The results showed that the operation energy consumption and pollutant emission of the power plant are the highest in all sub-process, which accounts for 93.93% of the total energy consumption and 92.20% of the total emission. Compared to other pollutant emissions from the coal-fired power plant, CO2reached up to 99.28%. Therefore, the control of CO2emission from the coal-fired power plants was very important. Based on the BP neural network, the amount of CO2emission from the generation side of coal-fired power plants was calculated via carbon balance method. The results showed that unit capacity, coal quality and unit operation load had great influence on the CO2emission from coal-fired power plants in Guangdong Province. The use of high volatile and high heat value of coal also can reduce the CO2emissions. What's more, under higher operation load condition, the CO2emissions of 1 kWh electric energy was less.