Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8099489 | Journal of Cleaner Production | 2018 | 13 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Energy
Renewable Energy, Sustainability and the Environment
Authors
Kaiming Wang, Yong Mao, Jiangtao Chen, Shiwei Yu,