Literature review on renewable energy development and China’s roadmap
Dequn ZHOU, Hao DING, Qunwei WANG, Bin SU
Literature review on renewable energy development and China’s roadmap
The low carbon energy transition has attracted worldwide attention to mitigate climate change. Renewable energy (RE) is the key to this transition, with significant developments to date, especially in China. This study systematically reviews the literature on RE development to identify a general context from many studies. The goal is to clarify key questions related to RE development from the current academic community. We first identify the forces driving RE development. Thereafter, we analyze methods for modeling RE developments considering the systematic and multiple complexity characteristics of RE. The study concludes with insights into the target selection and RE development roadmap in China.
renewable energy / energy transition / technology innovation / technology diffusion / development preference / energy system modeling
[1] |
Alizamir S, de Véricourt F, Sun P (2016). Efficient feed-in-tariff policies for renewable energy technologies. Operations Research, 64(1): 52–66
CrossRef
Google scholar
|
[2] |
Anatolitis V, Welisch M (2017). Putting renewable energy auctions into action—An agent-based model of onshore wind power auctions in Germany. Energy Policy, 110: 394–402
CrossRef
Google scholar
|
[3] |
Axsen J, Bailey J, Castro M A (2015). Preference and lifestyle heterogeneity among potential plug-in electric vehicle buyers. Energy Economics, 50: 190–201
CrossRef
Google scholar
|
[4] |
Bai J H, Xin S X, Liu J, Zheng K (2015). Roadmap of realizing the high penetration renewable energy in China. Proceedings of the CSEE, 35(14): 3699–3705 (in Chinese)
|
[5] |
Baker E, Bosetti V, Anadon L D, Henrion M, Aleluia Reis L (2015). Future costs of key low-carbon energy technologies: Harmonization and aggregation of energy technology expert elicitation data. Energy Policy, 80: 219–232
CrossRef
Google scholar
|
[6] |
Bass F M (1969). A new product growth for model consumer durables. Management Science, 15(5): 215–227
CrossRef
Google scholar
|
[7] |
Bauner C, Crago C L (2015). Adoption of residential solar power under uncertainty: Implications for renewable energy incentives. Energy Policy, 86: 27–35
CrossRef
Google scholar
|
[8] |
Benson C L, Magee C L (2014). On improvement rates for renewable energy technologies: Solar PV, wind turbines, capacitors, and batteries. Renewable Energy, 68: 745–751
CrossRef
Google scholar
|
[9] |
Bergmann A, Colombo S, Hanley N (2008). Rural versus urban preferences for renewable energy developments. Ecological Economics, 65(3): 616–625
CrossRef
Google scholar
|
[10] |
Bhagwat P C, Richstein J C, Chappin E J, de Vries L J (2016). The effectiveness of a strategic reserve in the presence of a high portfolio share of renewable energy sources. Utilities Policy, 39: 13–28
CrossRef
Google scholar
|
[11] |
Böhringer C (1998). The synthesis of bottom-up and top-down in energy policy modeling. Energy Economics, 20(3): 233–248
CrossRef
Google scholar
|
[12] |
Boie I (2016). Determinants for the Market Diffusion of Renewable Energy Technologies—An Analysis of the Framework Conditions for Non-residential Photovoltaic and Onshore Wind Energy Deployment in Germany, Spain and the UK. Dissertation for the Doctoral Degree. Devon: University of Exeter
|
[13] |
Bollinger B, Gillingham K (2012). Peer effects in the diffusion of solar photovoltaic panels. Marketing Science, 31(6): 900–912
CrossRef
Google scholar
|
[14] |
Boomsma T K, Meade N, Fleten S E (2012). Renewable energy investments under different support schemes: A real options approach. European Journal of Operational Research, 220(1): 225–237
CrossRef
Google scholar
|
[15] |
Chen R, Zhang X L, He J K, Yue L (2008). Provincial level renewable energy planning based on the MESSAGE model. Journal of Tsinghua University (Science and Technology), 48(9): 1525–1528 (in Chinese)
|
[16] |
Chu S, Majumdar A (2012). Opportunities and challenges for a sustainable energy future. Nature, 488(7411): 294–303
CrossRef
Pubmed
Google scholar
|
[17] |
Collantes G O (2007). Incorporating stakeholders’ perspectives into models of new technology diffusion: The case of fuel-cell vehicles. Technological Forecasting and Social Change, 74(3): 267–280
CrossRef
Google scholar
|
[18] |
de Coninck H, Puig D (2015). Assessing climate change mitigation technology interventions by international institutions. Climatic Change, 131(3): 417–433
CrossRef
Google scholar
|
[19] |
Ding H, Zhou D, Zhou P (2020a). Optimal policy supports for renewable energy technology development: A dynamic programming model. Energy Economics, 92: 104765
CrossRef
Google scholar
|
[20] |
Ding H, Zhou D Q, Liu G Q, Zhou P (2020b). Cost reduction or electricity penetration: Government R&D-induced PV development and future policy schemes. Renewable & Sustainable Energy Reviews, 124: 109752
CrossRef
Google scholar
|
[21] |
Dobrotkova Z, Surana K, Audinet P (2018). The price of solar energy: Comparing competitive auctions for utility-scale solar PV in developing countries. Energy Policy, 118: 133–148
CrossRef
Google scholar
|
[22] |
Du X W (2014). Energy revolution for sustainable future. Journal of Beijing Institute of Technology (Social Sciences Edition), 16(5): 1–8 (in Chinese)
|
[23] |
Eppstein M J, Grover D K, Marshall J S, Rizzo D M (2011). An agent-based model to study market penetration of plug-in hybrid electric vehicles. Energy Policy, 39(6): 3789–3802
CrossRef
Google scholar
|
[24] |
Fernandes B, Cunha J, Ferreira P (2011). The use of real options approach in energy sector investments. Renewable & Sustainable Energy Reviews, 15(9): 4491–4497
CrossRef
Google scholar
|
[25] |
Fisher-Vanden K, Jefferson G H, Liu H, Tao Q (2004). What is driving China’s decline in energy intensity? Resource and Energy Economics, 26(1): 77–97
CrossRef
Google scholar
|
[26] |
Fisher-Vanden K, Jefferson G H, Ma J K, Xu J Y (2006). Technology development and energy productivity in China. Energy Economics, 28(5–6): 690–705
CrossRef
Google scholar
|
[27] |
Frankfurt School (2019). Global trends in renewable energy investment 2019. Frankfurt School-UNEP Collaborating Centre for Climate & Sustainable Energy Finance
|
[28] |
Geroski P A (2000). Models of technology diffusion. Research Policy, 29(4–5): 603–625
CrossRef
Google scholar
|
[29] |
Gillingham K, Newell R G, Pizer W A (2008). Modeling endogenous technological change for climate policy analysis. Energy Economics, 30(6): 2734–2753
CrossRef
Google scholar
|
[30] |
Gonçalves da Silva C (2010). The fossil energy/climate change crunch: Can we pin our hopes on new energy technologies? Energy, 35(3): 1312–1316
CrossRef
Google scholar
|
[31] |
Grubb M, Köhler J, Anderson D (2002). Induced technical change in energy and environmental modeling: Analytic approaches and policy implications. Annual Review of Energy and the Environment, 27(1): 271–308
CrossRef
Google scholar
|
[32] |
Islam T (2014). Household level innovation diffusion model of photo-voltaic (PV) solar cells from stated preference data. Energy Policy, 65: 340–350
CrossRef
Google scholar
|
[33] |
Jacobsson S, Lauber V (2006). The politics and policy of energy system transformation—Explaining the German diffusion of renewable energy technology. Energy Policy, 34(3): 256–276
CrossRef
Google scholar
|
[34] |
Jaffe A B, Newell R G, Stavins R N (2005). A tale of two market failures: Technology and environmental policy. Ecological Economics, 54(2–3): 164–174
CrossRef
Google scholar
|
[35] |
Jakeman G, Hanslow K, Hinchy M, Fisher B S, Woffenden K (2004). Induced innovations and climate change policy. Energy Economics, 26(6): 937–960
CrossRef
Google scholar
|
[36] |
Jin Y Q (2016). Energy structure transformation goals and path: Comparison between US and Germany. Inquiry into Economic Issues, (2): 166–172 (in Chinese)
|
[37] |
Jorgenson D W, Wilcoxen P J (1993). Reducing US carbon emissions: An econometric general equilibrium assessment. Resource and Energy Economics, 15(1): 7–25
CrossRef
Google scholar
|
[38] |
Kardooni R, Yusoff S B, Kari F B (2016). Renewable energy technology acceptance in Peninsular Malaysia. Energy Policy, 88: 1–10
CrossRef
Google scholar
|
[39] |
Kouvaritakis N, Soria A, Isoard S (2000). Modelling energy technology dynamics: Methodology for adaptive expectations models with learning by doing and learning by searching. International Journal of Global Energy Issues, 14(1–4): 104–115
CrossRef
Google scholar
|
[40] |
Kriegler E, Weyant J P, Blanford G J, Krey V, Clarke L, Edmonds J, Fawcett A, Luderer G, Riahi K, Richels R, Rose S K, Tavoni M, van Vuuren D P (2014). The role of technology for achieving climate policy objectives: Overview of the EMF27 study on global technology and climate policy strategies. Climatic Change, 123(3–4): 353–367
CrossRef
Google scholar
|
[41] |
Langbroek J H, Franklin J P, Susilo Y O (2016). The effect of policy incentives on electric vehicle adoption. Energy Policy, 94: 94–103
CrossRef
Google scholar
|
[42] |
Levi P G, Pollitt M G (2015). Cost trajectories of low carbon electricity generation technologies in the UK: A study of cost uncertainty. Energy Policy, 87: 48–59
CrossRef
Google scholar
|
[43] |
Li J, Wang X C, Li X Z (2017). Japan’s energy situation and renewable energy utilization. Solar Energy, (12): 10–16 (in Chinese)
|
[44] |
Li L, Liu J, Zhu L, Zhang X B (2019). How to design a dynamic feed-in tariffs mechanism for renewables—A real options approach. International Journal of Production Research, 58(14): 4352–4366
|
[45] |
Li X, Wen J (2014). Review of building energy modeling for control and operation. Renewable & Sustainable Energy Reviews, 37: 517–537
CrossRef
Google scholar
|
[46] |
Lin B Q, Li J L (2015). Transformation of China’s energy structure under environmental governance constraints: A peak value analysis of coal and carbon dioxide. Social Sciences in China, (9): 84–107, 125 (in Chinese)
|
[47] |
Löschel A (2002). Technological change in economic models of environmental policy: A survey. Ecological Economics, 43(2–3): 105–126
CrossRef
Google scholar
|
[48] |
Luderer G, Krey V, Calvin K, Merrick J, Mima S, Pietzcker R, van Vliet J, Wada K (2014). The role of renewable energy in climate stabilization: Results from the EMF27 scenarios. Climatic Change, 123(3–4): 427–441
CrossRef
Google scholar
|
[49] |
Lund P (2006). Market penetration rates of new energy technologies. Energy Policy, 34(17): 3317–3326
CrossRef
Google scholar
|
[50] |
Lv F, Xu H H, Wang S C (2018). National survey report of PV power applications in China 2018. International Energy Agency Photovoltaic Power Systems Programme
|
[51] |
Ma L M, Shi D, Pei Q B (2018). Low-carbon transformation of China’s energy in 2015–2050: Renewable energy development and feasible path. China Population, Resources and Environment, 28(2): 8–18 (in Chinese)
|
[52] |
MacCracken C N, Edmonds J A, Kim S H, Sands R D (1999). The economics of the Kyoto Protocol. Energy Journal, 20(Special Issue): 25–72
|
[53] |
Mahajan V, Muller E, Bass F M (1990). New product diffusion models in marketing: A review and directions for research. Journal of Marketing, 54(1): 1–26
CrossRef
Google scholar
|
[54] |
Malhotra P, Hyers R W, Manwell J F, McGowan J G (2012). A review and design study of blade testing systems for utility-scale wind turbines. Renewable & Sustainable Energy Reviews, 16(1): 284–292
CrossRef
Google scholar
|
[55] |
Masini A, Menichetti E (2012). The impact of behavioural factors in the renewable energy investment decision making process: Conceptual framework and empirical findings. Energy Policy, 40: 28–38
CrossRef
Google scholar
|
[56] |
Maslin M, Scott J (2011). Carbon trading needs a multi-level approach. Nature, 475(7357): 445–447
CrossRef
Pubmed
Google scholar
|
[57] |
Matteson S, Williams E (2015). Residual learning rates in lead-acid batteries: Effects on emerging technologies. Energy Policy, 85: 71–79
CrossRef
Google scholar
|
[58] |
Murakami K, Ida T, Tanaka M, Friedman L (2015). Consumers’ willingness to pay for renewable and nuclear energy: A comparative analysis between the US and Japan. Energy Economics, 50: 178–189
CrossRef
Google scholar
|
[59] |
Newell R G, Jaffe A B, Stavins R N (1999). The induced innovation hypothesis and energy-saving technological change. Quarterly Journal of Economics, 114(3): 941–975
CrossRef
Google scholar
|
[60] |
Noailly J, Smeets R (2015). Directing technical change from fossil-fuel to renewable energy innovation: An application using firm-level patent data. Journal of Environmental Economics and Management, 72: 15–37
CrossRef
Google scholar
|
[61] |
Nordhaus W D (1994). Managing the Global Commons: The Economics of Climate Change. Cambridge, MA: MIT Press
|
[62] |
Ockwell D, Sagar A, de Coninck H (2015). Collaborative research and development (R&D) for climate technology transfer and uptake in developing countries: Towards a needs driven approach. Climatic Change, 131(3): 401–415
CrossRef
Google scholar
|
[63] |
Peter R, Ramaseshan B, Nayar C V (2002). Conceptual model for marketing solar based technology to developing countries. Renewable Energy, 25(4): 511–524
CrossRef
Google scholar
|
[64] |
Pillai U (2015). Drivers of cost reduction in solar photovoltaics. Energy Economics, 50: 286–293
CrossRef
Google scholar
|
[65] |
Pizer W A (1999). The optimal choice of climate change policy in the presence of uncertainty. Resource and Energy Economics, 21(3–4): 255–287
CrossRef
Google scholar
|
[66] |
Popp D C (2001). The effect of new technology on energy consumption. Resource and Energy Economics, 23(3): 215–239
CrossRef
Google scholar
|
[67] |
Purohit P, Kandpal T C (2005). Renewable energy technologies for irrigation water pumping in India: Projected levels of dissemination, energy delivery and investment requirements using available diffusion models. Renewable & Sustainable Energy Reviews, 9(6): 592–607
CrossRef
Google scholar
|
[68] |
Radomes Jr A A, Arango S (2015). Renewable energy technology diffusion: An analysis of photovoltaic-system support schemes in Medellín, Colombia. Journal of Cleaner Production, 92: 152–161
CrossRef
Google scholar
|
[69] |
REN21 (2018). Renewables 2018 Global Status Report. Paris: REN21 Secretariat
|
[70] |
Reddy S, Painuly J P (2004). Diffusion of renewable energy technologies—barriers and stakeholders’ perspectives. Renewable Energy, 29(9): 1431–1447
CrossRef
Google scholar
|
[71] |
Ringler P, Keles D, Fichtner W (2016). Agent-based modelling and simulation of smart electricity grids and markets—A literature review. Renewable & Sustainable Energy Reviews, 57: 205–215
CrossRef
Google scholar
|
[72] |
Shafiei E, Thorkelsson H, Ásgeirsson E I, Davidsdottir B, Raberto M, Stefansson H (2012). An agent-based modeling approach to predict the evolution of market share of electric vehicles: A case study from Iceland. Technological Forecasting and Social Change, 79(9): 1638–1653
CrossRef
Google scholar
|
[73] |
Shi D, Wang L (2015). Energy revolution and its effects on economic development. Industrial Economics Research, (1): 1–8 (in Chinese)
|
[74] |
Shi Y, Zhu Y B, Wang Z (2015). The cost-effective path of energy mix evolution for China under the emissions budgets. Journal of Management Sciences in China, 18(10): 26–37 (in Chinese)
|
[75] |
Snape J R, Boait P J, Rylatt R M (2015). Will domestic consumers take up the renewable heat incentive? An analysis of the barriers to heat pump adoption using agent-based modelling. Energy Policy, 85: 32–38
CrossRef
Google scholar
|
[76] |
Sue Wing I (2008). Explaining the declining energy intensity of the US economy. Resource and Energy Economics, 30(1): 21–49
CrossRef
Google scholar
|
[77] |
Sundt S, Rehdanz K (2015). Consumers’ willingness to pay for green electricity: A meta-analysis of the literature. Energy Economics, 51: 1–8
CrossRef
Google scholar
|
[78] |
Usha Rao K, Kishore V V N (2009). Wind power technology diffusion analysis in selected states of India. Renewable Energy, 34(4): 983–988
CrossRef
Google scholar
|
[79] |
Usha Rao K, Kishore V V N (2010). A review of technology diffusion models with special reference to renewable energy technologies. Renewable & Sustainable Energy Reviews, 14(3): 1070–1078
CrossRef
Google scholar
|
[80] |
Viklund M (2004). Energy policy options—From the perspective of public attitudes and risk perceptions. Energy Policy, 32(10): 1159–1171
CrossRef
Google scholar
|
[81] |
Wang Y, Zhang D, Ji Q, Shi X (2020). Regional renewable energy development in China: A multidimensional assessment. Renewable & Sustainable Energy Reviews, 124: 109797
CrossRef
Google scholar
|
[82] |
Weiss M, Junginger M, Patel M K, Blok K (2010). A review of experience curve analysis for energy demand technologies. Technological Forecasting and Social Change, 77(3): 411–428
CrossRef
Google scholar
|
[83] |
Yang X, Heidug W, Cooke D (2019). An adaptive policy-based framework for China’s Carbon Capture and Storage development. Frontiers of Engineering Management, 6(1): 78–86
CrossRef
Google scholar
|
[84] |
Yao X, Fan Y, Zhu L, Zhang X (2020). Optimization of dynamic incentive for the deployment of carbon dioxide removal technology: A nonlinear dynamic approach combined with real options. Energy Economics, 86: 104643
CrossRef
Google scholar
|
[85] |
York R (2012). Asymmetric effects of economic growth and decline on CO2 emissions. Nature Climate Change, 2(11): 762–764
CrossRef
Google scholar
|
[86] |
Yu Y (2019). Low-carbon technology calls for comprehensive electricity-market redesign. Frontiers of Engineering Management, 6(1): 128–130
CrossRef
Google scholar
|
[87] |
Zeng Y, Guo W, Wang H, Zhang F (2020). A two-stage evaluation and optimization method for renewable energy development based on data envelopment analysis. Applied Energy, 262: 114363
CrossRef
Google scholar
|
[88] |
Zhang H, Wu K, Qiu Y, Chan G, Wang S, Zhou D, Ren X (2020a). Solar photovoltaic interventions have reduced rural poverty in China. Nature Communications, 11(1): 1969
CrossRef
Pubmed
Google scholar
|
[89] |
Zhang M, Zhou D, Zhou P (2014). A real option model for renewable energy policy evaluation with application to solar PV power generation in China. Renewable & Sustainable Energy Reviews, 40: 944–955
CrossRef
Google scholar
|
[90] |
Zhang M M, Zhou P, Zhou D Q (2016). A real options model for renewable energy investment with application to solar photovoltaic power generation in China. Energy Economics, 59: 213–226
CrossRef
Google scholar
|
[91] |
Zhang R, Shimada K, Ni M, Shen G Q, Wong J K (2020b). Low or no subsidy? Proposing a regional power grid based wind power feed-in tariff benchmark price mechanism in China. Energy Policy, 146: 111758
CrossRef
Google scholar
|
[92] |
Zhao Y Q (2017). International renewable energy development and global energy management transformation. Macroeconomics, (4): 43–54 (in Chinese)
|
[93] |
Zhou D, Chong Z, Wang Q (2020). What is the future policy for photovoltaic power applications in China? Lessons from the past. Resources Policy, 65: 101575
CrossRef
Google scholar
|
[94] |
Zhou D, Ding H, Zhou P, Wang Q (2019). Learning curve with input price for tracking technical change in the energy transition process. Journal of Cleaner Production, 235: 997–1005
CrossRef
Google scholar
|
[95] |
Zhou Y H, Pu Y L, Chen S Y, Fang F (2015). Government support and development of emerging industries: A new energy industry survey. Economic Research Journal, 50(6): 147–160 (in Chinese)
|
[96] |
Zhou Z, Zhao F, Wang J (2011). Agent-based electricity market simulation with demand response from commercial buildings. IEEE Transactions on Smart Grid, 2(4): 580–588
CrossRef
Google scholar
|
[97] |
Zhu L, Fan Y (2011). A real options-based CCS investment evaluation model: Case study of China’s power generation sector. Applied Energy, 88(12): 4320–4333
CrossRef
Google scholar
|
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