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

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  • Chen, Huadong
  • Wang, Can
  • Cai, Wenjia
  • Wang, Jianhui

Abstract

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.

Suggested Citation

  • Chen, Huadong & Wang, Can & Cai, Wenjia & Wang, Jianhui, 2018. "Simulating the impact of investment preference on low-carbon transition in power sector," Applied Energy, Elsevier, vol. 217(C), pages 440-455.
    • Handle: RePEc:eee:appene:v:217:y:2018:i:c:p:440-455
    DOI: 10.1016/j.apenergy.2018.02.152
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    1. Yuan, Jiahai & Xu, Yan & Kang, Junjie & Zhang, Xingping & Hu, Zheng, 2014. "Nonlinear integrated resource strategic planning model and case study in China's power sector planning," Energy, Elsevier, vol. 67(C), pages 27-40.
    2. Hui, Jingxuan & Cai, Wenjia & Wang, Can & Ye, Minhua, 2017. "Analyzing the penetration barriers of clean generation technologies in China’s power sector using a multi-region optimization model," Applied Energy, Elsevier, vol. 185(P2), pages 1809-1820.
    3. He, Gang & Kammen, Daniel M., 2016. "Where, when and how much solar is available? A provincial-scale solar resource assessment for China," Renewable Energy, Elsevier, vol. 85(C), pages 74-82.
    4. Nie, S. & Li, Y.P. & Liu, J. & Huang, Charley Z., 2017. "Risk management of energy system for identifying optimal power mix with financial-cost minimization and environmental-impact mitigation under uncertainty," Energy Economics, Elsevier, vol. 61(C), pages 313-329.
    5. Elzen, Michel den & Fekete, Hanna & Höhne, Niklas & Admiraal, Annemiek & Forsell, Nicklas & Hof, Andries F. & Olivier, Jos G.J. & Roelfsema, Mark & van Soest, Heleen, 2016. "Greenhouse gas emissions from current and enhanced policies of China until 2030: Can emissions peak before 2030?," Energy Policy, Elsevier, vol. 89(C), pages 224-236.
    6. Lai, Chun Sing & McCulloch, Malcolm D., 2017. "Levelized cost of electricity for solar photovoltaic and electrical energy storage," Applied Energy, Elsevier, vol. 190(C), pages 191-203.
    7. Stanek, Wojciech & Szargut, Jan & Kolenda, Zygmunt & Czarnowska, Lucyna, 2016. "Exergo-ecological and economic evaluation of a nuclear power plant within the whole life cycle," Energy, Elsevier, vol. 117(P2), pages 369-377.
    8. Chen, Qixin & Kang, Chongqing & Xia, Qing & Guan, Dabo, 2011. "Preliminary exploration on low-carbon technology roadmap of China’s power sector," Energy, Elsevier, vol. 36(3), pages 1500-1512.
    9. Tietjen, Oliver & Pahle, Michael & Fuss, Sabine, 2016. "Investment risks in power generation: A comparison of fossil fuel and renewable energy dominated markets," Energy Economics, Elsevier, vol. 58(C), pages 174-185.
    10. Zhao, Xiaoli & Lyon, Thomas P. & Song, Cui, 2012. "Lurching towards markets for power: China’s electricity policy 1985–2007," Applied Energy, Elsevier, vol. 94(C), pages 148-155.
    11. Wang, Can & Ye, Minhua & Cai, Wenjia & Chen, Jining, 2014. "The value of a clear, long-term climate policy agenda: A case study of China’s power sector using a multi-region optimization model," Applied Energy, Elsevier, vol. 125(C), pages 276-288.
    12. Lin-Ju Chen & Lei Zhu & Ying Fan & Sheng-Hua Cai, 2013. "Long-Term Impacts of Carbon Tax and Feed-in Tariff Policies on China's Generating Portfolio and Carbon Emissions: A Multi-Agent-Based Analysis," Energy & Environment, , vol. 24(7-8), pages 1271-1293, December.
    13. Wu, Yang & Yu, Zichao & Ngan, H.W. & Tan, Zhongfu, 2014. "Sustaining China׳s electricity market development," Energy Policy, Elsevier, vol. 73(C), pages 30-37.
    14. Cong, Rong-Gang & Wei, Yi-Ming, 2010. "Potential impact of (CET) carbon emissions trading on China’s power sector: A perspective from different allowance allocation options," Energy, Elsevier, vol. 35(9), pages 3921-3931.
    15. Cheng, Beibei & Dai, Hancheng & Wang, Peng & Xie, Yang & Chen, Li & Zhao, Daiqing & Masui, Toshihiko, 2016. "Impacts of low-carbon power policy on carbon mitigation in Guangdong Province, China," Energy Policy, Elsevier, vol. 88(C), pages 515-527.
    16. Zhao, Zhen-Yu & Zuo, Jian & Wu, Pan-Hao & Yan, Hong & Zillante, George, 2016. "Competitiveness assessment of the biomass power generation industry in China: A five forces model study," Renewable Energy, Elsevier, vol. 89(C), pages 144-153.
    17. Wiebe, Kirsten S. & Lutz, Christian, 2016. "Endogenous technological change and the policy mix in renewable power generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 739-751.
    18. Wang, Xingwei & Cai, Yanpeng & Dai, Chao, 2014. "Evaluating China's biomass power production investment based on a policy benefit real options model," Energy, Elsevier, vol. 73(C), pages 751-761.
    19. Zhu, Lei & Fan, Ying, 2013. "Modelling the investment in carbon capture retrofits of pulverized coal-fired plants," Energy, Elsevier, vol. 57(C), pages 66-75.
    20. Qi, Tianyu & Winchester, Niven & Karplus, Valerie J. & Zhang, Da & Zhang, Xiliang, 2016. "An analysis of China's climate policy using the China-in-Global Energy Model," Economic Modelling, Elsevier, vol. 52(PB), pages 650-660.
    21. Richstein, Jörn C. & Chappin, Emile J.L. & de Vries, Laurens J., 2014. "Cross-border electricity market effects due to price caps in an emission trading system: An agent-based approach," Energy Policy, Elsevier, vol. 71(C), pages 139-158.
    22. Zhu, Lei & Fan, Ying, 2011. "A real options–based CCS investment evaluation model: Case study of China’s power generation sector," Applied Energy, Elsevier, vol. 88(12), pages 4320-4333.
    23. Pisciella, P. & Vespucci, M.T. & Bertocchi, M. & Zigrino, S., 2016. "A time consistent risk averse three-stage stochastic mixed integer optimization model for power generation capacity expansion," Energy Economics, Elsevier, vol. 53(C), pages 203-211.
    24. Tang, Ling & Wu, Jiaqian & Yu, Lean & Bao, Qin, 2015. "Carbon emissions trading scheme exploration in China: A multi-agent-based model," Energy Policy, Elsevier, vol. 81(C), pages 152-169.
    25. He, Gang & Kammen, Daniel M., 2014. "Where, when and how much wind is available? A provincial-scale wind resource assessment for China," Energy Policy, Elsevier, vol. 74(C), pages 116-122.
    26. Fan, Lin & Norman, Catherine S. & Patt, Anthony G., 2012. "Electricity capacity investment under risk aversion: A case study of coal, gas, and concentrated solar power," Energy Economics, Elsevier, vol. 34(1), pages 54-61.
    27. Caralis, George & Diakoulaki, Danae & Yang, Peijin & Gao, Zhiqiu & Zervos, Arthouros & Rados, Kostas, 2014. "Profitability of wind energy investments in China using a Monte Carlo approach for the treatment of uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 224-236.
    28. Jano-Ito, Marco A. & Crawford-Brown, Douglas, 2017. "Investment decisions considering economic, environmental and social factors: An actors' perspective for the electricity sector of Mexico," Energy, Elsevier, vol. 121(C), pages 92-106.
    29. Piao, M.J. & Li, Y.P. & Huang, G.H. & Nie, S., 2015. "Risk analysis for Shanghai's electric power system under multiple uncertainties," Energy, Elsevier, vol. 87(C), pages 104-119.
    30. Mo, Jian-Lei & Agnolucci, Paolo & Jiang, Mao-Rong & Fan, Ying, 2016. "The impact of Chinese carbon emission trading scheme (ETS) on low carbon energy (LCE) investment," Energy Policy, Elsevier, vol. 89(C), pages 271-283.
    31. Rubin, Edward S. & Azevedo, Inês M.L. & Jaramillo, Paulina & Yeh, Sonia, 2015. "A review of learning rates for electricity supply technologies," Energy Policy, Elsevier, vol. 86(C), pages 198-218.
    32. Ngan, H.W., 2010. "Electricity regulation and electricity market reforms in China," Energy Policy, Elsevier, vol. 38(5), pages 2142-2148, May.
    33. Meybodi, Mehdi Aghaei & Beath, Andrew C., 2016. "Impact of cost uncertainties and solar data variations on the economics of central receiver solar power plants: An Australian case study," Renewable Energy, Elsevier, vol. 93(C), pages 510-524.
    34. Zhang, Qin & Zhou, Dequn & Zhou, Peng & Ding, Hao, 2013. "Cost Analysis of straw-based power generation in Jiangsu Province, China," Applied Energy, Elsevier, vol. 102(C), pages 785-793.
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