基于免疫粒子群的调峰炉热力站优化调度

Optimal dispatching research of heating station with peak-shaving boiler based on immune particle swarm

为了实现供热节能,对调峰炉热力站进行优化调度.首先结合供热能耗最小和运行费用最小两种调度模型,建立一种综合节能最优的调度模型,该模型可适应不同调峰模式下的供热需要.然后将免疫粒子群算法(Immune particle swarm optimization,IPSO)应用于优化调度的寻优计算,采用免疫算法,对粒子群算法(PSO)进行改进,避免了粒子群算法中存在的算法早熟、容易陷入局部极值等问题,能更准确快速地求解出优化调度结果.通过实例验证了该算法的优越性,计算结果表明调峰炉热力站的优化调度达到了节能的目的。

To achieve energy-saving,optimal dispatching of heat load in heating station with peak-shaving boiler is necessary.First,a dispatch model of integrated optimal energy-saving was built on the combination with the minimum heat energy consumption model and minimum operation cost model,this model can applicable to different heating mode.Then,a immune particle swarm algorithm（IPSO） was used to solve optimal dispatching problems,compared with PSO,this algorithm is not easy to fall into Premature and local extremum,the convergence speed is faster than PSO.An experiment results show the advantages of IPSO,optimal dispatching of heating station with peak-shaving boiler can achieve energy-saving.