The large-scale use of home appliances based on Switch Mode Power Supplies (SMPSs) raises the interest in power quality problems they might cause. Accurate modeling of SMPS-based loads allows predicting the collective impact caused on low voltage networks. However, model parameter values for a specific load are not often available. This paper proposes a nonintrusive Optimal Parameter Estimation (OPE) process for an SMPS Equivalent Circuit Model (ECM) through an optimization problem formulation using only current measurements. This OPE process is composed of the Narrow Search (NS) and Data Fitting (DF) methods. The NS method advantage is that it limits the parameter region using datasheets, measurements, and manufacturing standards to obtain optimal parameters for a specific supply voltage. The DF method leading convenience is that it computes the parameters from equations, as a function of nominal voltage and rated power by using data regression. The parameters estimated by the NS method induce errors that exceed about five times the DF method; in addition, the DF method results improve by about 10% methods available in the state-of-the-art. Thereby, the OPE process is helpful in practical applications related to demand-side management or collective harmonic impact for a wide range of SMPS-based loads.

大规模使用基于开关电源 (SMPS) 的家用电器引起了人们对其可能导致的电能质量问题的关注。基于 SMPS 的负载的准确建模允许预测对低压网络造成的集体影响。但是，特定负载的模型参数值通常不可用。本文通过仅使用电流测量的优化问题公式，为 SMPS 等效电路模型 (ECM) 提出了一种非侵入式优化参数估计 (OPE) 过程。此 OPE 过程由窄搜索 (NS) 和数据拟合 (DF) 方法组成。NS 方法的优势在于它使用数据表、测量和制造标准来限制参数区域，以获得特定电源电压的最佳参数。DF 方法的主要便利之处在于它通过使用数据回归从方程计算参数，作为标称电压和额定功率的函数。NS方法估计的参数引起的误差超过DF方法的5倍左右；此外，DF 方法的结果比最先进的方法提高了约 10%。因此，OPE 过程在与需求侧管理或针对各种基于 SMPS 的负载的集体谐波影响相关的实际应用中很有帮助。