考虑环境温度的负荷经济调度

Load economic dispatch considering environmental temperature

随着发电成本的不断上升,负荷经济调度被给予了高度的重视。将环境温度作为电厂负荷经济调度的影响因素,比只考虑总负荷的研究具有更强的工况适应性。文中介绍粒子群算法在负荷经济调度中的应用。结合2台典型机组的实际运行数据对考虑环境温度与不考虑环境温度的负荷经济调度进行对比分析。分析结果表明:考虑环境温度和不考虑环境温度的结果都是机组热耗率随着总负荷的上升而下降,随着温度的上升而上升。考虑环境温度的机组热耗率始终低于不考虑环境温度的机组热耗率。并且随着温度的下降,二者的差值越来越大。分析结论对当前的电厂负荷经济调度有一定的参考意义。

The load economic dispatch have been played high attentions with rising cost of power generation.The environmental temperature is considered as a factor that affects the load economic dispatch of power plant,and the working condition of the research is more adaptive than previous research that considered only total load.The particle swarm optimization is used to load economic dispatch.Load economic dispatch considering environmental temperature and without consideration of environmental temperature are compared with the actual operation datas of two typical units.The results show that heat consumption rate decreases with increase of total load,while it increases with temperature in load economic dispatch considering environmental temperature and without consideration of environmental temperature.The heat consumption rate of considering the environmental temperature is always lower than the heat consumption rate of the unit without considering the environmental temperature.And with the decrease of temperature,the difference is more and more heavy.The conclutions are certain reference value for current researchs of load distribution optimization.