基于灰狼优化算法的火电机组负荷优化分配经济性研究

Research on Economical Efficiency of Optimized Load Distribution of Thermal Power Generating Units Based on Grey Wolf Optimization Algorithm

火电机组运行负荷优化分配问题直接影响着整个电网的经济性运行,对供电可靠性、稳定性和安全性都至关重要。为此,针对传统算法在负荷优化分配上存在收敛性差以及容易陷入局部最优解的问题,提出了一种灰狼优化算法(GWO)用于火电机组运行负荷的优化分配中的方案,并以三台火电机组进行负荷优化分配为例,建立以机组煤耗量最小为优化目标的数学模型,验证了算法的收敛性和实用性。最后使用灰狼优化算法(GWO)与传统遗传算法(GA)对比求解,结果表明,所提方法制定的负荷分配方案最优,能够很好地实现了机组的最经济化运行。

Optimized load distribution of the thermal power unit directly affects economic operation of the entire power grid,and it is of great importance for the reliability,stability and safety of power supply.In view of poor convergence of the traditional algorithm with respect to optimized load distribution as well as high likelihood of locally optimized solution,the grey wolf optimization(GWO)algorithm was proposed for the optimized operational load distribution scheme of the thermal power generating unit.Furthermore,taking three thermal power units for optimized load distribution as example,a mathematical model aiming at minimizing coal consumption of the unit was set up to verify the convergence and practicability of the proposed algorithm.Finally,GWO and traditional genetic algorithm(GA)were compared and the results indicated that the load distribution scheme formulated by using the proposed method was the best one,and could achieve most economical operation of the power unit.