Method and application for raw coal blending in coal preparation plants based on nonlinear programming
In the process of coal blending and washing in coal preparation plants,there are numerous types of raw coal with significant differences in coal quality,which results in complex calculation of coal blending scheme and low clean coal yield.A nonlinear program-ming based optimization method for raw coal blending in coal preparation plants was proposed to address this issue.The method uses segmented cubic Hermite interpolation to obtain the expression of the selectivity curve for each raw coal,and establishes a raw coal blending optimization model with the goal of maximizing clean coal yield and constraints on coal quality indicators and inventory.For the complex nonlinear terms in the model,particle swarm optimization algorithm is used to solve them.In order to verify the effectiveness of the proposed method,an application case study of a domestic coal preparation plant was analyzed.Results indicated that the proposed method was suitable for practical production and has strong universality,which can effectively overcome the disadvantages of low calcu-lation accuracy and poor effect of coal blending methods based on linear programming and also have significant advantages in improving clean coal yield.
coal preparationoptimization of coal blendingparticle swarm algorithmwashability curve
万方数据
维普
