Natural resource endowments and renewable energy technology adoption: insights from a heterogeneous-agent optimization model

Abstract Renewable energy transitions are critical for sustainability, yet adoption is affected by heterogeneous resource distributions among entities. We employ a heterogeneous-agent model to investigate how resource heterogeneity and inter-agent trade influence the adoption of renewable energy technology at the system-level, in contrast to traditional models that assume centralized decision-making and unconstrained resource availability. Our model incorporates four distinct agent types, each defined by a unique resource profile: abundant traditional resources, abundant renewable resources, both, or neither. It also allows for the trade of resources and products under a cooperative cost-minimization objective. Simulation results reveal that, compared to a centralized planner model, our heterogeneous-agent framework shows that heterogeneity in agents’ resource endowments has a significant influence on the adoption of renewable energy technology. Sensitivity analyses identify key levers for promoting the adoption of renewable energy technology: improving power transmission infrastructure efficiency, reducing the initial cost of renewable energy technology, lowering barriers to product transactions, and implementing carbon emission constraints. Our findings offer insights into how infrastructure efficiency, technology costs, and transaction barriers shape renewable energy technology diffusion, with implications for policy design.