Cong, Rong-Gang and Shen, Shaochuan (2014): How to Develop Renewable Power in China? A Cost-Effective Perspective. Published in: The Scientific World Journal
Preview |
PDF
MPRA_paper_112209.pdf Download (686kB) | Preview |
Abstract
To address the problems of climate change and energy security, Chinese government strived to develop renewable power as an important alternative of conventional electricity. In this paper, the learning curve model is employed to describe the decreasing unit investment cost due to accumulated installed capacity; the technology diffusion model is used to analyze the potential of renewable power. Combined with the investment cost, the technology potential, and scenario analysis of China social development in the future, we develop the Renewable Power Optimization Model (RPOM) to analyze the optimal development paths of three sources of renewable power from 2009 to 2020 in a cost-effective way. Results show that (1) the optimal accumulated installed capacities of wind power, solar power, and biomass power will reach 169000, 20000, and 30000 MW in 2020; (2) the developments of renewable power show the intermittent feature; (3) the unit investment costs of wind power, solar power, and biomass power will be 4500, 11500, and 5700 Yuan/KW in 2020; (4) the discounting effect dominates the learning curve effect for solar and biomass powers; (5) the rise of on-grid ratio of renewable power will first promote the development of wind power and then solar power and biomass power.
Item Type: | MPRA Paper |
---|---|
Original Title: | How to Develop Renewable Power in China? A Cost-Effective Perspective |
Language: | English |
Keywords: | Renewable energy; Sustainable development; Cost-efficient; Carbon-emission |
Subjects: | Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q40 - General |
Item ID: | 112209 |
Depositing User: | Rong-Gang Cong |
Date Deposited: | 08 Mar 2022 03:26 |
Last Modified: | 08 Mar 2022 03:26 |
References: | [1] State Council, Twelfth Five-Year Plan about Renewable Energy Development, State Council, Beijing, China, 2012. [2] A. Abanades, “The challenge of hydrogen production for the transition to a CO2-free economy,” Agronomy Research, vol. 10, no. 1, pp. 11–16, 2012. [3] J. P. Painuly, “Barriers to renewable energy penetration: a framework for analysis,” Renewable Energy, vol. 24, no. 1, pp. 73–89, 2001. [4] I. Dincer, “Renewable energy and sustainable development: a crucial review,” Renewable & Sustainable Energy Reviews, vol. 4, no. 2, pp. 157–175, 2000. [5] S. Carley, “State renewable energy electricity policies: an empirical evaluation of effectiveness,” Energy Policy, vol. 37, no. 8, pp. 3071–3081, 2009. [6] R. Wustenhagen, M. Wolsink, and M. J. Burer, “Social acceptance of renewable energy innovation: an introduction to the concept,” Energy Policy, vol. 35, no. 5, pp. 2683–2691, 2007. [7] C. Cormio, M. Dicorato, A. Minoia, and M. Trovato, “A regional energy planning methodology including renewable energy sources and environmental constraints,” Renewable and Sustainable Energy Reviews, vol. 7, no. 2, pp. 99–130, 2003. [8] L. Bird, M. Bolinger, T. Gagliano, R. Wiser, M. Brown, and B. Parsons, “Policies and market factors driving wind power development in the United States,” Energy Policy, vol. 33, no. 11, pp. 1397–1407, 2005. [9] J. Al-Amir and B. Abu-Hijleh, “Strategies and policies from promoting the use of renewable energy resource in the UAE,” Renewable and Sustainable Energy Reviews, vol. 26, pp. 660–667, 2013. [10] M. Ortega, P. del R´ıo, and E. A. Montero, “Assessing the benefits and costs of renewable electricity. The Spanish case,” Renewable and Sustainable Energy Reviews, vol. 27, pp. 294–304, 2013. [11] J. A. Cherni and J. Kentish, “Renewable energy policy and electricity market reforms in China,” Energy Policy, vol. 35, no. 7, pp. 3616–3629, 2007. [12] R.-G. Cong and Y.-M. Wei, “Potential impact of (CET) carbon emissions trading on China’s power sector: a perspective from different allowance allocation options,” Energy, vol. 35, no. 9, pp. 3921–3931, 2010. [13] L. Neij, “Cost dynamics of wind power,” Energy, vol. 24, no. 5, pp. 375–389, 1999. [14] J. Goldemberg, S. T. Coelho, P. M. Nastari, and O. Lucon, “Ethanol learning curve—the Brazilian experience,” Biomass and Bioenergy, vol. 26, no. 3, pp. 301–304, 2004. [15] A. McDonald and L. Schrattenholzer, “Learning rates for energy technologies,” Energy Policy, vol. 29, no. 4, pp. 255–261, 2001. [16] L. Neij, “Use of experience curves to analyse the prospects for diffusion and adoption of renewable energy technology,” Energy Policy, vol. 25, no. 13, pp. 1099–1107, 1997. [17] J. Goldemberg, “Ethanol for a sustainable energy future,” Science, vol. 315, no. 5813, pp. 808–810, 2007. [18] R. Gross, M. Leach, and A. Bauen, “Progress in renewable energy,” Environment International, vol. 29, no. 1, pp. 105–122, 2003. [19] N. Johnstone, I. Haˇsci ˇ c, and D. Popp, “Renewable energy policies and technological innovation: evidence based on patent counts,” Environmental and Resource Economics, vol. 45, no. 1, pp. 133–155, 2010. [20] P. del Rıo, “Analysing future trends of renewable electricity in the EU in a low-carbon context,” Renewable and Sustainable Energy Reviews, vol. 15, no. 5, pp. 2520–2533, 2011. [21] Z. Peidong, Y. Yanli, S. jin, Z. Yonghong, W. Lisheng, and L. Xinrong, “Opportunities and challenges for renewable energy policy in China,” Renewable and Sustainable Energy Reviews, vol. 13, no. 2, pp. 439–449, 2009. [22] M. Nieto, F. Lopez, and F. Cruz, “Performance analysis of technology using the S curve model: the case of digital signal processing (DSP) technologies,” Technovation, vol. 18, no. 6-7, pp. 439–457, 1998. [23] P. A. Geroski, “Models of technology diffusion,” Research Policy, vol. 29, no. 4-5, pp. 603–625, 2000. [24] F. M. Bass, “A new product growth for model consumer durables,” Management Science, vol. 15, no. 5, pp. 215–227, 1969. [25] S. Kiiski and M. Pohjola, “Cross-country diffusion of the Internet,” Information Economics and Policy, vol. 14, no. 2, pp. 297–310, 2002. [26] A. B. Jaffe and R. N. Stavins, “The energy paradox and the diffusion of conservation technology,” Resource and Energy Economics, vol. 16, no. 2, pp. 91–122, 1994. [27] M. Carolin Mabel and E. Fernandez, “Growth and future trends of wind energy in India,” Renewable and Sustainable Energy Reviews, vol. 12, no. 6, pp. 1745–1757, 2008. [28] S. Nikolova, A. Causevski, and A. Al-Salaymeh, “Optimal operation of conventional power plants in power system with integrated renewable energy sources,” Energy Conversion and Management, vol. 65, pp. 697–703, 2013. [29] B. C. Jain, “Rural energy centres based on renewables-case study on an effective and viable alternative,” IEEE Transactions on Energy Conversion EC, vol. 2, no. 3, pp. 329–335, 1987. [30] K. Ashenayi and R. Ramakumar, “IRES—A program to design integrated renewable energy systems,” Energy, vol. 15, no. 12, pp. 1143–1152, 1990. [31] R. Ramakumar, P. S. Shetty, and K. Ashenayi, “A linear programming approach to the design of integrated renewable energy systems for developing countries,” IEEE Transactions on Energy Conversion EC, vol. 1, no. 4, pp. 18–24, 1986. [32] S. Iniyan and T. R. Jagadeesan, “On the development of a reliability based optimal renewable energy model for the sustainable energy scene in India,” International Journal of Ambient Energy, vol. 18, no. 3, pp. 153–164, 1997. [33] S. Iniyan, L. Suganthi, and A. A. Samuel, “Energy models for commercial energy prediction and substitution of renewable energy sources,” Energy Policy, vol. 34, no. 17, pp. 2640–2653, 2006. [34] R. Romero, A. F. Zobaa, E. N. Asada, andW. Freitas, “Mathematical optimisation techniques applied to power system operation and planning,” International Journal of Energy Technology and Policy, vol. 5, no. 4, pp. 393–403, 2007. [35] F. Zaro and M.. Abido, “Multi-objective particle swarm optimization for optimal power flow in a deregulated environment of power systems,” in Proceedings of the 11th International Conference on Intelligent Systems Design and Applications (ISDA ’11), pp. 1122–1127, November 2011. [36] R. G. Cong, “An optimization model for renewable energy generation and its application in China: a perspective of maximum utilization,” Renewable and Sustainable Energy Reviews, vol. 17, pp. 94–103, 2013. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/112209 |