摘要
在火电厂的配煤过程中,需要综合考虑锅炉运行的稳定性与经济性。利用粒子群算法建立火电厂经济性配煤优化模型,主要以配煤经济性作为目标函数,并以单煤的价格、发热量、灰分、挥发分、水分以及硫分等6项指标值作为约束条件。基于内蒙古某电厂的来煤条件,采用本模型进行配煤优化计算。仿真实验表明:带惯性权重的粒子群算法(标准PSO)具有较好的全局搜索能力,能够快速、准确地搜索到最佳的优劣质煤配比关系和最经济的配煤价格。
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.
出处
《锅炉技术》
北大核心
2012年第5期18-24,共7页
Boiler Technology
关键词
配煤优化
火电厂经济性
粒子群优化算法
约束条件
惯性权重因子
适应度函数
coal blending optimization
economics of power plant
particle swarm optimization algorithm
constraint condition
inertial weight factor
fitness function