全球能源互联网（英文）2020，Vol.3Issue(2)：99-110,12.DOI:10.14171/j.2096-5117.gei.2020.02.001
东北亚能源互联网电力和碳联合市场研究
Joint electricity and carbon market for Northeast Asia energy interconnection
摘要
Abstract
Decarbonization of the electricity sector is crucial to mitigate the impacts of climate change and global warming over the coming decades. The key challenges for achieving this goal are carbon emission trading and electricity sector regulation, which are also the major components of the carbon and electricity markets, respectively. In this paper, a joint electricity and carbon market model is proposed to investigate the relationships between electricity price, carbon price, and electricity generation capacity, thereby identifying pathways toward a renewable energy transition under the transactional energy interconnection framework. The proposed model is a dynamically iterative optimization model consisting of upper-level and lower-level models. The upper-level model optimizes power generation and obtains the electricity price, which drives the lower-level model to update the carbon price and electricity generation capacity. The proposed model is verified using the Northeast Asia power grid. The results show that increasing carbon price will result in increased electricity price, along with further increases in renewable energy generation capacity in the following period. This increase in renewable energy generation will reduce reliance on carbon-emitting energy sources, and hence the carbon price will decline. Moreover, the interconnection among zones in the Northeast Asia power grid will enable reasonable allocation of zonal power generation. Carbon capture and storage (CCS) will be an effective technology to reduce the carbon emissions and further realize the emission reduction targets in 2030-2050. It eases the stress of realizing the energy transition because of the less urgency to install additional renewable energy capacity.关键词
电碳联合市场/东北亚能源互联网/动态迭代优化模型Key words
Joint electricity and carbon market/Northeast Asia Energy Interconnection/Dynamically iterative optimization model引用本文复制引用
Tao Ding,Runzhao Lu,Yiting Xu,Qingrun Yang,Yuanbing Zhou,Yun Zhang,Ya Wen..东北亚能源互联网电力和碳联合市场研究[J].全球能源互联网（英文）,2020,3(2):99-110,12.基金项目
This work was supported in part by National Key Research and Development Program of China (2016YFB0901900) and in part by the Science and Technology Foundation of GEIDCO (SGGEIG00JYJS1900016). （2016YFB0901900）
