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An analysis of the optimum renewable energy portfolio using the bottom–up model: Focusing on the electricity generation sector in South Korea

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  • Park, Sang Yong
  • Yun, Bo-Yeong
  • Yun, Chang Yeol
  • Lee, Duk Hee
  • Choi, Dong Gu

Abstract

The deployment of renewable energy is considered as one of the important alternative solutions for reducing greenhouse gas emissions caused by electricity generation. As one of the key measures for promoting the deployment of renewable energy, the Renewable Portfolio Standard (RPS), which obligates power operators with a power equipment capacity of 500MW or larger (excluding renewable energy equipment) to supply over a specific portion of their total electricity generation output in the form of renewable energy, was enacted in South Korea in 2012. However, there are still many disputes concerning the appropriate renewable energy deployment goal and the optimum portfolio for each renewable energy source which enable to minimize the economic burden while achieving the deployment target. Therefore, this paper intends to deduce the optimum portfolio up to 2050 based on explicit representation of renewable energy technologies and analyze the cost effect using the bottom–up energy system analysis model of electricity generation sector in South Korea. The result indicates that the potential for a reduction of the cost of PV was the highest and that, in the long term, it would account for the highest portion of the renewable energy portfolio as it was the most cost competitive technology. The additional cost for increasing the renewable deployment target 20% compared with the 3rd Energy Basic Plan was predicted to be between 107 and 115 USD/MWh. Therefore the renewable energy will be able to play a greater role in reducing GHG emission if the R&D to reduce investment and operation cost of PV and wind power is conducted successfully.

Suggested Citation

  • Park, Sang Yong & Yun, Bo-Yeong & Yun, Chang Yeol & Lee, Duk Hee & Choi, Dong Gu, 2016. "An analysis of the optimum renewable energy portfolio using the bottom–up model: Focusing on the electricity generation sector in South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 319-329.
    • Handle: RePEc:eee:rensus:v:53:y:2016:i:c:p:319-329
    DOI: 10.1016/j.rser.2015.08.029
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    as
    1. Sen, Rohit & Bhattacharyya, Subhes C., 2014. "Off-grid electricity generation with renewable energy technologies in India: An application of HOMER," Renewable Energy, Elsevier, vol. 62(C), pages 388-398.
    2. Huva, Robert & Dargaville, Roger & Caine, Simon, 2012. "Prototype large-scale renewable energy system optimisation for Victoria, Australia," Energy, Elsevier, vol. 41(1), pages 326-334.
    3. Boubaker, K., 2012. "A review on renewable energy conceptual perspectives in North Africa using a polynomial optimization scheme," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 4298-4302.
    4. Connolly, D. & Lund, H. & Mathiesen, B.V. & Leahy, M., 2010. "A review of computer tools for analysing the integration of renewable energy into various energy systems," Applied Energy, Elsevier, vol. 87(4), pages 1059-1082, April.
    5. Føyn, T. Helene Ystanes & Karlsson, Kenneth & Balyk, Olexandr & Grohnheit, Poul Erik, 2011. "A global renewable energy system: A modelling exercise in ETSAP/TIAM," Applied Energy, Elsevier, vol. 88(2), pages 526-534, February.
    6. Bhattacharya, Anindya & Kojima, Satoshi, 2012. "Power sector investment risk and renewable energy: A Japanese case study using portfolio risk optimization method," Energy Policy, Elsevier, vol. 40(C), pages 69-80.
    7. Lee, Duk Hee & Park, Sang Yong & Hong, Jong Chul & Choi, Sang Jin & Kim, Jong Wook, 2013. "Analysis of the energy and environmental effects of green car deployment by an integrating energy system model with a forecasting model," Applied Energy, Elsevier, vol. 103(C), pages 306-316.
    8. Frei, Christoph W. & Haldi, Pierre-Andre & Sarlos, Gerard, 2003. "Dynamic formulation of a top-down and bottom-up merging energy policy model," Energy Policy, Elsevier, vol. 31(10), pages 1017-1031, August.
    9. Ahn, Joongha & Woo, JongRoul & Lee, Jongsu, 2015. "Optimal allocation of energy sources for sustainable development in South Korea: Focus on the electric power generation industry," Energy Policy, Elsevier, vol. 78(C), pages 78-90.
    10. Jaccard, Mark & Murphy, Rose & Rivers, Nic, 2004. "Energy-environment policy modeling of endogenous technological change with personal vehicles: combining top-down and bottom-up methods," Ecological Economics, Elsevier, vol. 51(1-2), pages 31-46, November.
    11. Pina, André & Silva, Carlos & Ferrão, Paulo, 2012. "The impact of demand side management strategies in the penetration of renewable electricity," Energy, Elsevier, vol. 41(1), pages 128-137.
    12. Lind, Arne & Rosenberg, Eva & Seljom, Pernille & Espegren, Kari & Fidje, Audun & Lindberg, Karen, 2013. "Analysis of the EU renewable energy directive by a techno-economic optimisation model," Energy Policy, Elsevier, vol. 60(C), pages 364-377.
    13. Huh, Sung-Yoon & Lee, Chul-Yong, 2014. "Diffusion of renewable energy technologies in South Korea on incorporating their competitive interrelationships," Energy Policy, Elsevier, vol. 69(C), pages 248-257.
    14. Cong, Rong-Gang, 2013. "An optimization model for renewable energy generation and its application in China: A perspective of maximum utilization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 17(C), pages 94-103.
    15. Labriet, Maryse & Cabal, Helena & Lechón, Yolanda & Giannakidis, George & Kanudia, Amit, 2010. "The implementation of the EU renewable directive in Spain. Strategies and challenges," Energy Policy, Elsevier, vol. 38(5), pages 2272-2281, May.
    16. Arnette, Andrew & Zobel, Christopher W., 2012. "An optimization model for regional renewable energy development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(7), pages 4606-4615.
    17. Klinge Jacobsen, Henrik, 1998. "Integrating the bottom-up and top-down approach to energy-economy modelling: the case of Denmark," Energy Economics, Elsevier, vol. 20(4), pages 443-461, September.
    18. Shin, Jungwoo & Woo, JongRoul & Huh, Sung-Yoon & Lee, Jongsu & Jeong, Gicheol, 2014. "Analyzing public preferences and increasing acceptability for the Renewable Portfolio Standard in Korea," Energy Economics, Elsevier, vol. 42(C), pages 17-26.
    19. Boubaker, K., 2012. "Renewable energy in upper North Africa: Present versus 2025-horizon perspectives optimization using a Data Envelopment Analysis (DEA) framework," Renewable Energy, Elsevier, vol. 43(C), pages 364-369.
    20. Azadeh, A. & Babazadeh, R. & Asadzadeh, S.M., 2013. "Optimum estimation and forecasting of renewable energy consumption by artificial neural networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 605-612.
    21. Wilson, Deborah & Swisher, Joel, 1993. "Exploring the gap : Top-down versus bottom-up analyses of the cost of mitigating global warming," Energy Policy, Elsevier, vol. 21(3), pages 249-263, March.
    22. Park, Nyun-Bae & Yun, Sun-Jin & Jeon, Eui-Chan, 2013. "An analysis of long-term scenarios for the transition to renewable energy in the Korean electricity sector," Energy Policy, Elsevier, vol. 52(C), pages 288-296.
    23. Erdinc, O. & Uzunoglu, M., 2012. "Optimum design of hybrid renewable energy systems: Overview of different approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1412-1425.
    24. Böhringer, Christoph & Rutherford, Thomos F., 2009. "Integrated assessment of energy policies: Decomposing top-down and bottom-up," Journal of Economic Dynamics and Control, Elsevier, vol. 33(9), pages 1648-1661, September.
    25. Koopmans, Carl C. & te Velde, Dirk Willem, 2001. "Bridging the energy efficiency gap: using bottom-up information in a top-down energy demand model," Energy Economics, Elsevier, vol. 23(1), pages 57-75, January.
    26. Kim, Seunghyok & Koo, Jamin & Lee, Chang Jun & Yoon, En Sup, 2012. "Optimization of Korean energy planning for sustainability considering uncertainties in learning rates and external factors," Energy, Elsevier, vol. 44(1), pages 126-134.
    27. Bhattacharyya, Subhes C. & Timilsina, Govinda R., 2009. "Energy demand models for policy formulation : a comparative study of energy demand models," Policy Research Working Paper Series 4866, The World Bank.
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