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Optimization of a typical biomass fueled power plant using Genetic algorithm and binary particle swarm optimization

机译:使用遗传算法和二元粒子群优化优化典型生物量燃料发电厂

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Over thousands tons of animal manures are produced in Iran. The major animal manures producers are located in central regions. Animal manures collection is an autochthonous and important renewable energy sources that in most cases are released in nature by ranchers. In this paper, a typical animal manure producer region is considered and optimal location and size of a typical biomass fueled power plant is determined. Genetic algorithm (GA) is used as the major approach of determination and effectively this approach will make possible to determine the optimal location, biomass supply area and power plant size that offer the best profitability for investor. Binary particle swarm optimization algorithm is also used as the second approach of optimization and eventually results obtained from both algorithm are compared. In this work we use profitability index (PI) as the fitness function of Genetic algorithm and the point with the maximum PI is selected.
机译:伊朗生产出超过数千吨的动物粪便。主要的动物粪便生产商位于中部地区。动物粪便收集是一种自动紧张和重要的可再生能源,在大多数情况下由牧场主释放。在本文中,确定了典型的动物粪便生产区和典型生物量燃料发电厂的最佳位置和尺寸。遗传算法(GA)用作测定的主要方法,有效地,这种方法将实现最佳位置,生物量供应区域和发电厂尺寸,为投资者提供最佳盈利能力。二进制粒子群优化算法也用作优化的第二种方法,并最终进行了两种算法获得的结果。在这项工作中,我们使用盈利性指数(PI)作为遗传算法的健身功能,选择最大PI的点。

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