Assessing the Impact of Green Energy Transition, Technological Innovation, and Natural Resources on Load Capacity Factor in Algeria: Evidence from Dynamic Autoregressive Distributed Lag Simulations and Machine Learning Validation

Algeria’s resource-dependent economy faces significant challenges in balancing hydrocarbon reliance with environmental sustainability, yet existing research largely overlooks the comprehensive load capacity factor (LCF) metric in favor of traditional emissions analyses. This study examines the relationships between the LCF and key economic–environmental factors in Algeria from 1980 to 2023, including total natural resource rents, energy transition, technological innovation, GDP, primary energy consumption, and urbanization. Using ARDL and DARDL econometric approaches complemented by a kernel-based regularized least squares analysis, the research captures both linear and nonlinear relationships while accounting for asymmetric dynamics in short- and long-term perspectives. The findings reveal that natural resource rents, technological innovation, and urbanization significantly impair Algeria’s LCF, while primary energy consumption shows a minimal positive impact. The energy transition initiatives demonstrate mixed effects, highlighting the complexities of green energy implementation in resource-dependent economies. These results suggest that Algeria’s sustainable development requires targeted policies focusing on resource management efficiency, environmentally conscious urban planning, and green technology adoption, providing valuable insights for other resource-rich nations pursuing similar sustainability transitions.