Simulating the impact of investment preference on low-carbon transition in power sector

被引:31
作者
Chen, Huadong [1 ,2 ]
Wang, Can [1 ,2 ,3 ]
Cai, Wenjia [3 ]
Wang, Jianhui [4 ]
机构
[1] Tsinghua Univ, State Key Joint Lab Environm Simulat & Pollut Con, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Sch Environm, Beijing 100084, Peoples R China
[3] Tsinghua Univ, Minist Educ, Key Lab Earth Syst Modeling & Dept Earth Syst Sci, Beijing 100084, Peoples R China
[4] Argonne Natl Lab, Energy Syst Div, Lemont, IL 60439 USA
基金
中国国家自然科学基金;
关键词
Risk preference; Adaptive technical preference; Long-term low-carbon transition; China's power sector; Agent-based model; MULTIREGION OPTIMIZATION MODEL; REAL-OPTIONS; RESOURCE ASSESSMENT; SOLAR POWER; CHINA; ELECTRICITY; GENERATION; POLICY; RISK; UNCERTAINTIES;
D O I
10.1016/j.apenergy.2018.02.152
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
With the deepening marketization of the electric power industry in China, its low-carbon transition relies increasingly on enterprise investment decisions. These decisions can be influenced by the risk preferences and technical preferences of the enterprises, thus deviating traditional estimation with respect to both economic optimization and uncertainty. To evaluate the impacts of investment preferences on the development path of the power sector, we developed an agent-based model combined with Monte Carlo simulation to quantitatively capture the risk preferences and adaptive technical preferences of power enterprises in their decision-making process. Two scenarios were established with and without risk preferences and adaptive technical preferences, respectively. The results indicate that both the risk aversion and the adaptive technical preference of power generation enterprises play significant roles in promoting the low-carbon transition of the power sector and that they exhibit a synergistic effect. In addition, the risk aversion of power generation enterprises increases the stability of transition in the power sector. However, these two preferences lead to income loss and additional subsidy burden in the power sector. The preferences of power generation enterprises should be recognized and considered in the design and evaluation of low-carbon policies in China's power sector.
引用
收藏
页码:440 / 455
页数:16
相关论文
共 54 条
[1]  
[Anonymous], 2014, WORLD EN OUTL 2014
[2]   Profitability of wind energy investments in China using a Monte Carlo approach for the treatment of uncertainties [J].
Caralis, George ;
Diakoulaki, Danae ;
Yang, Peijin ;
Gao, Zhiqiu ;
Zervos, Arthouros ;
Rados, Kostas .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2014, 40 :224-236
[3]   An uncertainty analysis of subsidy for carbon capture and storage (CCS) retrofitting investment in China's coal power plants using a real-options approach [J].
Chen, Huadong ;
Wang, Can ;
Ye, Minhua .
JOURNAL OF CLEANER PRODUCTION, 2016, 137 :200-212
[4]   LONG-TERM IMPACTS OF CARBON TAX AND FEED-IN TARIFF POLICIES ON CHINA'S GENERATING PORTFOLIO AND CARBON EMISSIONS: A MULTI-AGENT-BASED ANALYSIS [J].
Chen, Lin-Ju ;
Zhu, Lei ;
Fan, Ying ;
Cai, Sheng-Hua .
ENERGY & ENVIRONMENT, 2013, 24 (7-8) :1271-1293
[5]   Preliminary exploration on low-carbon technology roadmap of China's power sector [J].
Chen, Qixin ;
Kang, Chongqing ;
Xia, Qing ;
Guan, Dabo .
ENERGY, 2011, 36 (03) :1500-1512
[6]   Impacts of low-carbon power policy on carbon mitigation in Guangdong Province, China [J].
Cheng, Beibei ;
Dai, Hancheng ;
Wang, Peng ;
Xie, Yang ;
Chen, Li ;
Zhao, Daiqing ;
Masui, Toshihiko .
ENERGY POLICY, 2016, 88 :515-527
[7]  
China Electricity Council, 2016, STAT EL PROD IND 201
[8]   Potential impact of (CET) carbon emissions trading on China's power sector: A perspective from different allowance allocation options [J].
Cong, Rong-Gang ;
Wei, Yi-Ming .
ENERGY, 2010, 35 (09) :3921-3931
[9]   Greenhouse gas emissions from current and enhanced policies of China until 2030: Can emissions peak before 2030? [J].
den Elzen, Michel ;
Fekete, Hanna ;
Hohne, Niklas ;
Admiraal, Annemiek ;
Forsell, Nicklas ;
Hof, Andries F. ;
Olivier, Jos G. J. ;
Roelfsema, Mark ;
van Soest, Heleen .
ENERGY POLICY, 2016, 89 :224-236
[10]   Electricity capacity investment under risk aversion: A case study of coal, gas, and concentrated solar power [J].
Fan, Lin ;
Norman, Catherine S. ;
Patt, Anthony G. .
ENERGY ECONOMICS, 2012, 34 (01) :54-61