Strategic Renewable Investment Under Cap-and-Trade: A Prospect Theory Approach

This study examines renewable energy investment decisions by power generation companies under cap-and-trade regulations and renewable output uncertainty. Although existing research predominantly employs expected utility theory (EUT) to model risk-neutral cost-minimisation strategies, empirical evidence highlights discrepancies between EUT assumptions and real-world decision-making. To bridge this gap, we introduce a behavioural economics framework grounded in prospect theory (PT), which explicitly incorporates risk preferences and cognitive biases into the analysis. We develop a nonconvex optimisation model to determine optimal renewable investment levels for PT-driven firms, resolving computational challenges by exploiting the unimodal structure of the objective function. Our theoretical and numerical analyses reveal three key insights: (1) Firms with higher reference points exhibit greater risk tolerance and renewable investment due to elevated outcome expectations; (2) probability distortion under PT incentivises higher renewable investments when the likelihood of high renewable output is low; (3) PT-driven firms achieve lower expected profits than EUT-modelled counterparts but secure higher guaranteed minimum profits, reflecting a preference for loss aversion over risk-neutral optimisation. These findings underscore the critical role of behavioural factors in shaping energy transition strategies under emission constraints, offering policymakers and firms actionable insights for aligning investments with risk profiles and sustainability goals.