Short-Term Electricity Price Forecast Based on SSA-SVM Model

In the electricity market environment, price forecast has the characteristics of periodicity and unpredictability. Based on these characteristics, this paper proposes a sparrow-algorithm-optimized support vector machine (SSA-SVM) model to predict short-term electricity prices. The sparrow algorithm (SSA) has high convergence performance and local search ability, and the parameters of SVM are optimized, the SSA-SVM prediction model is established, and the electricity price data is predicted and analyzed, and then compared with the simulation results of the SSA-SVM model. Finally, the SSA-SVM method has a good effect, error, and convergence speed of the SSA-SVM model are improved.