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首页> 外文会议>DSC-vol.74-1; American Society of Mechanical Engineers(ASME) International Mechanical Engineering Congress and Exposition; 20051105-11; Orlando,FL(US) >PSO - A NOVEL TECHNIQUE TO OPTIMIZE A COAL PREPARATION PLANT
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PSO - A NOVEL TECHNIQUE TO OPTIMIZE A COAL PREPARATION PLANT

机译：PSO-优化选煤厂的新技术

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摘要

A coal preparation plant typically has multiple cleaning circuits based on size of coal particles. Each circuit is operated to produce the same product quality so that the blend of clean coal meets the targeted product quality constraints. Though, this approach of producing the clean coal satisfies the product quality constraints as given by the customer, it may suffer from the loss of overall clean coal yield by 1-2%. Numerous studies conducted in the past illustrate that the optimal yield can be obtained by operating each circuit to produce the same incremental product quality. However, this approach is good enough for single product quality constraints but it fails to produce optimal yield with multiple product quality constraints. A newer optimization technique known as particle swarming is developed for the yield optimization of a coal preparation plant while satisfying multiple product quality constraints. The optimization model incorporates two product quality constraints - product ash and sulfur assay. The results indicate that an increment of 2.73% in the yield could be achieved by both equal incremental ash quality approach and particle swarm optimization. The additional yield can generate extra revenue of $5,460,000 per annum without significantly adding to the implementation/operation cost.
机译：选煤厂通常根据煤颗粒的大小具有多个清洁回路。每个回路的运行均产生相同的产品质量，以使清洁煤的混合物满足目标产品质量的限制。虽然，这种生产清洁煤的方法满足了客户给出的产品质量限制，但可能会导致清洁煤总产量损失1-2％。过去进行的大量研究表明，通过操作每个电路以产生相同的增量产品质量，可以获得最佳产量。但是，这种方法对于单个产品质量约束已经足够好，但是无法在多个产品质量约束下产生最佳产量。为满足选煤厂的产量优化要求，同时又满足多种产品质量要求，开发了一种称为粒子群更新的更新优化技术。优化模型包含两个产品质量约束-产品灰分和硫含量测定。结果表明，通过相等的增量灰质方法和粒子群优化，可以使产量增加2.73％。额外的收益每年可产生546万美元的额外收入，而不会显着增加实施/运营成本。

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