中文摘要：

电力系统中模型参数的辨识值常因优化算法、收敛区间、迭代次数等的差异而不同,此时常规的误差分析方法很难判断并选择合理的参数组。为解决这一问题,文中提出采用一种定量的不确定性分析方法——随机响应面法对仿真结果进行动态一致性检验的新观点,并提出了相应的检验标准。由于随机响应面法能克服传统的蒙特卡洛法仿真次数多、时间长的缺点,利用随机响应面法可快速计算出参数组中多个参数的联合不确定度,从而得到仿真结果的均值和置信区间,校验模型参数的有效性,为参数的合理选择提供参考依据。某大区电网的负荷实测记录验证了该方法的有效性。

英文摘要：

The identified values of parameters in power system models often differ owing to different optimization algorithms,convergence intervals and iterative numbers and so on,making it difficult to determine and select a rational parameter set.A new method of dynamic consistency test is proposed based on the stochastic response surface method（SRSM） as well as the relative consistency test criteria.Since SRSM can solve the limitations in the conventional methods of quantitative uncertainty analysis,such as immense computation time-consumption and large model runs,the uncertainty of responses arising from uncertainty of models and parameters can be quickly calculated.Therefore the expectation value and confidence interval can be obtained,providing useful information for checking parameters validity and selecting a rational parameter set.The method proposed is verified by load measuring data in a certain power grid.