Optimization control of energy storage in complementary distributed energy systems for predicting new energy output in cold regions

In response to the volatility and intermittency of new energy generation in cold regions, as well as the impact of extreme weather on energy systems, a complementary distributed energy system energy storage optimization control method for predicting new energy output in cold regions is proposed. In response to the significant impact of harsh weather conditions such as low temperatures and freezing on new energy generation in cold regions, the uncertainty of new energy output and its impact on grid stability were first analyzed. Subsequently, a new energy output prediction method based on the PSO-LS-SVM prediction model was proposed. On this basis, the construction of a complementary distributed energy system was studied, which integrates multiple renewable energy sources such as solar and wind energy. Finally, through case verification, the complementary distributed energy system energy storage optimization control strategy proposed in this article has significant advantages in cold regions, which can effectively improve the utilization rate of new energy and the stability of the system, providing reliable guarantees for energy supply in cold regions.