GMDH-enhanced temporal convolutional network for short-term wind forecasting and microgrid operation

• Hybrid polynomial network feature construction boosts short-term wind forecast accuracy. • Proposed model cuts 1‑hour wind speed prediction error by 47% versus persistence. • Forecast‑driven model predictive control reduces simulated operating cost by 23.7%. • Simulation achieves near‑zero diesel use in a remote wind‑diesel microgrid. The inherent variability of wind power poses a problem for the stability and cost-effectiveness of remote microgrids. Hence, accurate short-term forecasting is v