针对大电力系统可靠性评估并行计算中静态任务分配方法存在的进程间通信次数多、过度计算等不足,在详细分析Monte-Carlo仿真过程中可靠性指标方差系数和抽样次数变化规律的基础上,提出基于De Miovre-Laplace中心极限定理和曲线拟合相结合的启发式动态任务分配方法,并提出基于动态任务分配的大规模电力系统可靠性评估并行算法.在并行任务分配过程中,根据已有的仿真信息对总抽样次数进行合理估计,使得单次任务分配量尽可能多,以达到减少进程间通信次数的目的.算例分析表明所述的动态任务分配方法可较好地提高并行效率.%To overcome the excessive communication and calculation problems in the bulk power system reliability evaluation with the static task allocation technique, the rules of reliability index square coefficients varying with the sampling times in Monte-Carlo method are analyzed. Based on the analyzing results, a parallel computation model for reliability evaluation of bulk power system is proposed using a dynamic task allocation technique, which is designed using the De Moivre-Laplace central limit theorem and the curve fitting method. Using the simulating information in the parallel task allocation process, a conservative evaluation technique for total sampling times can be used to maximize allocated processes in a single task and minimize the total communication times. Case studies show that the proposed dynamic task allocation method can improve the efficiency of parallel computation.
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