基于粒子群优化(PSO)方法的中爪哇省电厂CO2排放经济调度与绩效优化经济调度的相关性与比较

Denis, E. W. Sinuraya, S. Handoko, Yosua Alvin Adi Soetrisno, Moh Samudro
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摘要

发电厂利用能量变化的过程来发电。最主要的发电成本来自燃料成本。在现有的发电厂中,以煤为燃料的蒸汽发电厂是提供最重要的电能需求的发电厂,因为这种发电厂非常经济,能够产生高容量的电力。在这一切的背后,与其他发电厂相比,这个蒸汽发电厂是一个排放系数很高的发电厂,所以它会对环境产生影响。因此,有必要通过优化经济交付和排放来限制蒸汽电厂的运行,以最小的运行成本获得最小排放值的电厂调度。仿真结果与拉格朗日乘法相一致。在每一项支出中,与经济调度优化中的排放相比,经济调度和排放调度优化结果的排放价值将有所减少。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Correlation and Comparison between Economic Dispatch with CO2 Emissions and Economic Emission Dispatch as Performance Optimization of Power Plants in Central Java Province with Particle Swarm Optimization (PSO) Methods
Power Plants use the process of changing energy to produce electricity. The most substantial electricity generation costs are derived from fuel costs. Among the existing power plants, steam power plants with coal fuel are power plants that supply the most significant electrical energy needs because this type of power plant is very economical and capable of producing high capacity electricity. Behind all that, this steam power plant is a power plant with very high emission factors when compared to other power plants so that it will have an impact on the environment. Therefore, it is necessary to limit the operation of Steam Power Plants by optimising economic deliveries and emissions to get the scheduling of plants with the smallest emission values with minimum operating costs. The simulation results are identical to the Lagrange multiplier method. At each expenditure, there will be a decrease in the value of emissions in the results of the optimisation of Economic and Emissions Dispatch when compared to emissions in the optimisation of Economic Dispatch.
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