Electricity Market Price Prediction Based on Quadratic Hybrid Decomposition and THPO Algorithm

Electricity price forecasting is a crucial aspect of spot trading in the electricity market and optimal scheduling microgrids. However, stochastic periodic nature sequences often results low accuracy forecasting. To address this issue, study proposes quadratic hybrid decomposition method based on ensemble empirical modal (EEMD) wavelet packet (WPD), along with deep extreme learning machine (DELM) optimized by THPO algorithm to enhance prediction. overcome problem optimization falling into local optima, an improved strategy proposed optimization-seeking ability HPO. The series decomposed components using EEMD WPD decomposition, DELM model built for each component separately. predicted values all are then superimposed obtain final prediction evaluated data from Australian market. demonstrate that significantly improves convergence performance algorithm, effectively enhances stability prediction, as compared several other models.