1.School of Electrical and Power Engineering, Hohai University, Nanjing 211100, China;2.Power Grid Planning & Research Center of Guizhou Power Grid Co., Ltd., Guiyang 550000, China

Power aggregation model remains crucial for the analysis and calculation of new distribution networks. Traditional power sources in the power system are generators with clear mechanisms and similar characteristics, making it easier to establish equivalent aggregation models. As a high proportion of renewable energy sources are connected to the distribution network, their time-varying and non-linear characteristics pose a huge challenge to the equivalent modeling of power sources. First, the model structure of the aggregated generator is constructed, and six parameters of the model are identified based on small disturbances of loads without considering the short-term time-varying characteristic. Then, aiming at the time-varying characteristic of renewable energy sources, assuming that the internal voltage of the traditional generator in the model remains unchanged, the Taylor formula is used to expand the power balance equation and solve the four model parameters related to the time-varying characteristic. Euclidean distance for the above four parameters is constructed and the distance is used to determine whether there is time-varying inside the power source. If so, the Taylor expansion method will continue to be used for solving. If there is no time-varying inside the power source and the load meets the small disturbance requirements, six model parameters will be identified again, which can timely correct the error accumulation caused by the time-varying characteristic on the generator side. Subsequent extensions can be continued according to this rule. Finally, the feasibility and effectiveness of the proposed method are verified through numerical cases. By using the above rules, an equivalent power source model that takes into account time-varying characteristic and is suitable for continuous analysis and calculation of high proportion of renewable energy connected to distribution networks can be obtained.

This work is supported by National Natural Science Foundation of China (No. 51837004).