基于智能优化算法的多时段可中断负荷调度

Multi-period dispatch of interruptible loads by intelligent optimization algorithms

探讨智能优化算法在多时段可中断负荷调度问题中的应用,建立了的优化模型,可考虑中断补偿费用最小化和中断频率最小化等多个优化目标,并可计入不同可中断用户的不同中断特性.并给出了的算例分析,着重比较了基于离散二元粒子群优化算法和遗传算法的结果,表明离散粒子群算法在收敛性和精度上均优于遗传算法,具有较好的应用价值.

Application of intelligent optimization algorithms to the multi-period interruptible load dispatch problem is discussed in this paper. Multi objectives, such as minimizing the interruption payments and interruption frequency, can be included in the proposed interruptible load dispatch model. The characteristics of different interruptible loads are also considered. Numerical simulations using discrete binary particle swarm optimization（BPSO） and the genetic algorithm（GA） show that the BPSO has a performance on convergence and precision than that of the GA. Thus the BPSO presents better potentials in solving the interruptible load dispatch problem.