Hybrid KAN+XGBoost model outperforms SARIMAX, LSTM, standalone KAN and XGBoost on week-ahead electricity price forecasting in the Australian NEM, cutting MAE by ~12% versus XGBoost and over 50% versus naive baseline.
Facing the high share of variable renewable energy in the power system: Flexibility and stability requirements,
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Hybrid Kolmogorov-Arnold Network and XGBoost Framework for Week-Ahead Price Forecasting in Australia's National Electricity Market
Hybrid KAN+XGBoost model outperforms SARIMAX, LSTM, standalone KAN and XGBoost on week-ahead electricity price forecasting in the Australian NEM, cutting MAE by ~12% versus XGBoost and over 50% versus naive baseline.