本文从机组经济性的角度出发，建立了在假定目标下的最优负荷分配模型，并结合由多种智能算法改进后的鱼群算法对模型进行最优值的求取，切实提高了算法的收敛速度及寻优的准确度。在实例中，选择3台机组进行负荷优化分配，仿真结果表明了模型的合理性及改进算法的可行性，同时本文在最后的内容当中对模型进行变化，引入了“附加经济函数”，即在原有目标函数的基础上增添了新的目标函数，利用目标函数的变化去限制机组负荷分配过程中的频繁变动，进而达到减少机组负荷的频繁反调的目的。

In the environment of market competition,the power generation enterprise must fully exploit the economic benefit of operating the generator set,so that the thermal power unit can fully respond to the new environmental situation and the current energy situation.In this paper,the optimal load allocation model with assumed targets is configured from the economic point of view,and a variety of intelligent algorithms are combined to improve the fish swarm algorithm for the optimal value of the model and to improve the convergence rate and the accuracy of the search.In the case study,three units are chosen to conduct the load allocation optimization.The simulation results show the rationality of the model,and the feasibility of the improved algorithm.At the same time,the model is modified by introducing “the additional economic function”,that is,the original objective function is now enriched and expanded.Then the changes in the objective function can be used to limit the frequent changes during the unit load allocation process,reducing the frequent antiregulation.

TP301