Online modeling method for composite load model including EVs and battery storage based on measurement data - Yin, Yanhe; Zhong, Yi; He, Yi; Li, Guohao; Li, Zhuohuan; Pan, Shixian (Frontiers in Energy Research, 2024)
Load models have a significant influence on power system simulation. However, current load modeling approaches can hardly satisfy the diversity and time-varying characteristics of loads [including electric vehicles (EVs) and battery storage] in terms of model accuracy and computing efficiency. An online modeling method for composite load models based on measurement information is proposed in this paper. Firstly, the dominant factors in load model output are analyzed based on the active subspace of parameter space. Then the clustering algorithm is applied to cluster the large number of underlying loads based on the characteristics of load daily output curves. Finally, the underlying loads are equivalently aggregated from the low voltage levels to the high voltage levels to construct the composite load model. Simulation results obtained based on PSCAD/EMTDC demonstrate that the load model constructed by the proposed approach can accurately reflect the actual load characteristics of a power system.