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A Demand-Side Perspective on Developing a Future Electricity Generation Mix: Identifying Heterogeneity in Social Preferences

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  • Sung-Yoon Huh

    (Haas School of Business, University of California Berkeley, 2220 Piedmont Avenue, Berkeley, CA 94720, USA)

  • Chul-Yong Lee

    (Korea Energy Economics Institute (KEEI), 405-11 Jongga-ro, Jung-gu, Ulsan 44543, Korea)

Abstract

Public support is an important factor in failure or success of the government decisions with respect to the electricity generation mix, which highlights the necessity of developing an electricity mix that reflects social preferences and acceptance. This study explores heterogeneity in social preferences for power sources and develops an electricity mix from a demand-side perspective. The study utilizes the choice-based conjoint survey and latent class model, and bases its empirical analysis on South Korea’s electric power sector. Results demonstrate that preferences for power sources in Korean society consist of two classes: one that is sensitive to the environment and one that is sensitive to risk. An electricity mix for Korea that reflects social preferences is 16.5–19.8% coal-fired, 13.3–24.9% liquefied natural gas (LNG), 9.0–11.2% oil, 22.3–32.9% nuclear, and 18.5–38.9% renewables, depending on the scenario. The study confirms that renewables are the power source with the least potential to cause social conflict, compared to nuclear and coal-fired sources. Moreover, increasing the proportion of renewables (currently only 3.9%) while decreasing the proportion of coal-fired power sources (currently 39.9%) to less than half its current level will result in an electricity mix that is accordance with social preferences in the long run.

Suggested Citation

  • Sung-Yoon Huh & Chul-Yong Lee, 2017. "A Demand-Side Perspective on Developing a Future Electricity Generation Mix: Identifying Heterogeneity in Social Preferences," Energies, MDPI, vol. 10(8), pages 1-19, August.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:8:p:1127-:d:106550
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    as
    1. Huang, Yun-Hsun & Wu, Jung-Hua, 2008. "A portfolio risk analysis on electricity supply planning," Energy Policy, Elsevier, vol. 36(2), pages 627-641, February.
    2. Aguilera, Roberto F., 2014. "The role of natural gas in a low carbon Asia Pacific," Applied Energy, Elsevier, vol. 113(C), pages 1795-1800.
    3. Huh, Sung-Yoon & Woo, JongRoul & Lim, Sesil & Lee, Yong-Gil & Kim, Chang Seob, 2015. "What do customers want from improved residential electricity services? Evidence from a choice experiment," Energy Policy, Elsevier, vol. 85(C), pages 410-420.
    4. van Rijnsoever, Frank J. & van Mossel, Allard & Broecks, Kevin P.F., 2015. "Public acceptance of energy technologies: The effects of labeling, time, and heterogeneity in a discrete choice experiment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 817-829.
    5. Shimon Awerbuch, 2006. "Portfolio-Based Electricity Generation Planning: Policy Implications For Renewables And Energy Security," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 11(3), pages 693-710, May.
    6. Byun, Hyunsuk & Lee, Chul-Yong, 2017. "Analyzing Korean consumers’ latent preferences for electricity generation sources with a hierarchical Bayesian logit model in a discrete choice experiment," Energy Policy, Elsevier, vol. 105(C), pages 294-302.
    7. Andrew A. Goett & Kathleen Hudson & Kenneth E. Train, 2000. "Customers' Choice Among Retail Energy Suppliers: The Willingness-to-Pay for Service Attributes," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-28.
    8. Yoo, James & Ready, Richard C., 2014. "Preference heterogeneity for renewable energy technology," Energy Economics, Elsevier, vol. 42(C), pages 101-114.
    9. Contu, Davide & Strazzera, Elisabetta & Mourato, Susana, 2016. "Modeling individual preferences for energy sources: The case of IV generation nuclear energy in Italy," Ecological Economics, Elsevier, vol. 127(C), pages 37-58.
    10. 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.
    11. Grösche, Peter & Schröder, Carsten, 2011. "Eliciting public support for greening the electricity mix using random parameter techniques," Energy Economics, Elsevier, vol. 33(2), pages 363-370, March.
    12. Ryu, Hanee & Dorjragchaa, Shonkhor & Kim, Yeonbae & Kim, Kyunam, 2014. "Electricity-generation mix considering energy security and carbon emission mitigation: Case of Korea and Mongolia," Energy, Elsevier, vol. 64(C), pages 1071-1079.
    13. Kim, Younghwan & Kim, Wonjoon & Kim, Minki, 2014. "An international comparative analysis of public acceptance of nuclear energy," Energy Policy, Elsevier, vol. 66(C), pages 475-483.
    14. Gracia, Azucena & Barreiro-Hurlé, Jesús & Pérez y Pérez, Luis, 2012. "Can renewable energy be financed with higher electricity prices? Evidence from a Spanish region," Energy Policy, Elsevier, vol. 50(C), pages 784-794.
    15. 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.
    16. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    17. van Putten, Marloes & Lijesen, Mark & Özel, Tanju & Vink, Nancy & Wevers, Harm, 2014. "Valuing the preferences for micro-generation of renewables by househoulds," Energy, Elsevier, vol. 71(C), pages 596-604.
    18. Borchers, Allison M. & Duke, Joshua M. & Parsons, George R., 2007. "Does willingness to pay for green energy differ by source?," Energy Policy, Elsevier, vol. 35(6), pages 3327-3334, June.
    19. Thangavelu, Sundar Raj & Khambadkone, Ashwin M. & Karimi, Iftekhar A., 2015. "Long-term optimal energy mix planning towards high energy security and low GHG emission," Applied Energy, Elsevier, vol. 154(C), pages 959-969.
    20. Rentizelas, Athanasios & Georgakellos, Dimitrios, 2014. "Incorporating life cycle external cost in optimization of the electricity generation mix," Energy Policy, Elsevier, vol. 65(C), pages 134-149.
    21. 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.
    22. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    23. Welsch, Heinz & Biermann, Philipp, 2014. "Electricity supply preferences in Europe: Evidence from subjective well-being data," Resource and Energy Economics, Elsevier, vol. 38(C), pages 38-60.
    24. Zong Woo Geem & Jin-Hong Kim, 2016. "Optimal Energy Mix with Renewable Portfolio Standards in Korea," Sustainability, MDPI, vol. 8(5), pages 1-14, May.
    25. Foley, A.M. & Ó Gallachóir, B.P. & Hur, J. & Baldick, R. & McKeogh, E.J., 2010. "A strategic review of electricity systems models," Energy, Elsevier, vol. 35(12), pages 4522-4530.
    26. Vidal-Amaro, Juan José & Østergaard, Poul Alberg & Sheinbaum-Pardo, Claudia, 2015. "Optimal energy mix for transitioning from fossil fuels to renewable energy sources – The case of the Mexican electricity system," Applied Energy, Elsevier, vol. 150(C), pages 80-96.
    27. Bronfman, Nicolás C. & Jiménez, Raquel B. & Arévalo, Pilar C. & Cifuentes, Luis A., 2012. "Understanding social acceptance of electricity generation sources," Energy Policy, Elsevier, vol. 46(C), pages 246-252.
    28. Verbruggen, Aviel, 2008. "Renewable and nuclear power: A common future?," Energy Policy, Elsevier, vol. 36(11), pages 4036-4047, November.
    29. Kaenzig, Josef & Heinzle, Stefanie Lena & Wüstenhagen, Rolf, 2013. "Whatever the customer wants, the customer gets? Exploring the gap between consumer preferences and default electricity products in Germany," Energy Policy, Elsevier, vol. 53(C), pages 311-322.
    30. Purwanto, Widodo Wahyu & Pratama, Yoga Wienda & Nugroho, Yulianto Sulistyo & Warjito, & Hertono, Gatot Fatwanto & Hartono, Djoni & Deendarlianto, & Tezuka, Tetsuo, 2015. "Multi-objective optimization model for sustainable Indonesian electricity system: Analysis of economic, environment, and adequacy of energy sources," Renewable Energy, Elsevier, vol. 81(C), pages 308-318.
    31. Sithole, H. & Cockerill, T.T. & Hughes, K.J. & Ingham, D.B. & Ma, L. & Porter, R.T.J. & Pourkashanian, M., 2016. "Developing an optimal electricity generation mix for the UK 2050 future," Energy, Elsevier, vol. 100(C), pages 363-373.
    32. Willis, Ken & Scarpa, Riccardo & Gilroy, Rose & Hamza, Neveen, 2011. "Renewable energy adoption in an ageing population: Heterogeneity in preferences for micro-generation technology adoption," Energy Policy, Elsevier, vol. 39(10), pages 6021-6029, October.
    33. J. Cabello & M. Luque & F. Miguel & A. Ruiz & F. Ruiz, 2014. "A multiobjective interactive approach to determine the optimal electricity mix in Andalucía (Spain)," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(1), pages 109-127, April.
    34. Chee Tahir, Aidid & Bañares-Alcántara, René, 2012. "A knowledge representation model for the optimisation of electricity generation mixes," Applied Energy, Elsevier, vol. 97(C), pages 77-83.
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