Typical scenario construction for fast assessment of renewable energy absorption capacity

With the increasing proportion of renewable energy units in the power grid, in order to better plan the operation of the power system, it is necessary to predict and simulate the typical application scenarios of renewable energy. The medium and long-term planning and economic operation optimization of power system need to construct typical scenarios through historical data that can reflect the characteristics of renewable energy. In this paper, a renewable typical scenario construction method based on improved FCM clustering algorithm is proposed and applied to renewable energy absorption capacity assessment of power system with renewable energy. Taking a regional power grid in China as an example, the performance of scenario construction method based on improved clustering algorithm, annual time series method and typical day method is compared in the field of power system operation cost optimization. The results show that the improved clustering algorithm used in this paper has both computational accuracy and efficiency, and has practical application value.