基于粒子群优化算法分析约束条件对配煤最优价格的影响

发布时间：2018-05-11 07:18

本文选题：粒子群优化算法 + 配煤　；参考：《热力发电》2017年12期

【摘要】：电厂配煤是一个满足所有约束条件的寻优过程,而每种约束条件对目标函数的影响均不相同。本文利用粒子群优化算法建立配煤寻优模型,分析发热量、挥发分、水分、灰分与硫分等约束条件对配煤最优价格的影响趋势,并具体分析了配煤过程中调整发热量与挥发分约束范围对配煤经济性的影响。研究表明:各个约束条件对混煤价格的影响趋势基本符合分段线性函数;约束范围经济性由函数的斜率决定,斜率绝对值越小经济性越优,越大则经济性越差;合理制定调整配煤约束条件,可进一步提高配煤的经济效应,并获得较高的煤质参数指标。本文研究方法对电厂工作人员制定配煤约束条件有很好的指导作用,有利于电厂获得更加经济的配煤掺烧方案。
[Abstract]:Power plant coal blending is an optimization process that meets all constraints, and the effect of each constraint on the objective function is different. In this paper, particle swarm optimization (PSO) algorithm is used to set up a coal blending optimization model, and to analyze the influence of heat, volatile, moisture, ash and sulfur on the optimal price of coal blending. The influence of adjusting the restriction range of heat and volatile matter on the economy of coal blending is analyzed in detail. The results show that the influence trend of each constraint condition on the price of coal mixture basically accords with the piecewise linear function, the economy of the constraint range is determined by the slope of the function, the smaller the absolute value of the slope is, the better the economy is, and the more the economic efficiency is, the worse the economy is. The economic effect of coal blending can be further improved and a higher index of coal quality parameters can be obtained by rationally formulating and adjusting the constraint conditions of coal blending. The research method in this paper has a good guiding function for the power plant staff to formulate the constraint conditions of coal blending, and is helpful to obtain a more economical blending coal blending scheme for the power plant.
【作者单位】：西安热工研究院有限公司;
【分类号】：F426.21;F764.1

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