Investigation of Coal Blending Optimization for Power Plants Based on Particle Swarm Optimization Algorithm

In the process of coal blending for power plants,the stability and economics of boiler must be consider synthetically.The coal blending model of power plant was established by using particle swarm optimization algorithm,where the economics of coal blending was acted as an object function,moreover,six industrial and economical target of coal acted as constraint conditions,concluding price and calorific value and volatile matter and ash constituent and water constituent and sulfur content.Based on coal obtaining condition of a power plant in Inner Mongolia,the coal optimization blending proportion was investigated by using the model.The simulation result showed that the method that applying a modified particle swarm optimization algorithm to optimize blending coal system is feasible,which has a better global search capability.Consequently,it can quickly search the best ratio between high quality coal and bad one as well as the best economical price of blending coal.