نمونه کارها تحقیق و توسعه بهینه از فن آوری های انرژی کم کربن: مطالعه از چین

To support decision-making for an optimal portfolio strategy for low-carbon energy technology research and development (R&D), this study proposes a dynamic two-stage stochastic programming model, taking into account both the uncertainty of technological change and damages of climate change. Based on China's economic and technology level and expert elicitation, an R&D investment portfolio strategy looking at three low-carbon technologies (carbon capture and storage [CCS], solar photovoltaic [PV], and nuclear), including nine projects, is investigated through the proposed model. The optimized results show that the optimal R&D technology portfolio is robust to different levels of risk in climate damage. However, the total social costs for the optimal R&D technology portfolio is lowest in the medium risk of climate damage scenario. Under different opportunity costs, the composition of the optimal R&D portfolio varies. However, projects for each of the three technologies always constitute the optimal R&D portfolio. Furthermore, the implication is that a technology synergistic R&D strategy is conducive to enhancing the level of CO2 abatement and reducing the total social cost.