Advertisement

Optimal Combination of Energy Sources for Electricity Generation in Thailand with Lessons from Japan Using Maximum Entropy

  • Tatcha Sudtasan
  • Komsan Suriya
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 251)

Abstract

This study uses maximum entropy method to find an optimal combination of energy sources for electricity generation in Thailand. It sets three targets including unit cost, risk and pollution. In the optimization process, it forms three constraints according to these three targets. It solves the system following the guideline of Golan, Judge and Miller (1996). It analyses six scenarios of the targets. For the major results, it finds that hydropower, nuclear, wind and solar energy are major sources of electricity generation. The country cannot avoid adopting nuclear energy for its electricity generation in order to meet all the three targets that are optimal for its electricity generation and economic development.

Keywords

Electricity Generation Nuclear Power Plant Maximum Entropy Wind Power Risk Index 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bera, A.K., Park, S.Y.: Optimal Portfolio Diversification Using Maximum Entropy Principle. Econometric Reviews 27, 484–512 (2008)MathSciNetCrossRefMATHGoogle Scholar
  2. 2.
    Gartner, I.R.: Differentiated Risk Models in Portfolio Optimization: A Comparative Analysis of the Degree of Diversification and Performance in the Sao Paulo Stock Exchange (Bovespa). Pesquisa Operacional 32(2), 271–292 (2012)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Golan, A., Judge, G.G., Miller, D.: Maximum Entropy Econometrics: Robust Estimation with Limited Data. John Wiley & Sons (1996)Google Scholar
  4. 4.
    Hochreiter, R., Pflug, G.C., Wozabal, D.: Multi-stage stochastic electricity portfolio optimization in liberalized energy markets. Working Paper on Optimal Energy Portfolios, Department of Statistics and Decision Support System, University of Vienna (2005)Google Scholar
  5. 5.
    Inhaber, H.: Is Solar Power More Dangerous Than Nuclear? IAEA Bulletin 21(1), 11–17 (1982)Google Scholar
  6. 6.
    Jiang, Y., He, S., Li, X.: A Maximum Entropy Model for Large Scale Portfolio Optimization. In: Proceedings of the International Conference on Risk Management and Engineering Management 2008, pp. 610–615 (2008)Google Scholar
  7. 7.
    Liu, M.: Portfolio optimization in electricity markets. Electric Power Systems Research 77, 1000–1009Google Scholar
  8. 8.
    Ministry of Energy of Thailand. Thailand electricity generation by source in 2011. Ministry of Energy, Bangkok (2011)Google Scholar
  9. 9.
    Mitsubishi Corporation. Annual Report, Power Business (2012), http://www.mitsubishicorp.com
  10. 10.
    Park, S.Y.: Optimal Portfolio Diversification Using Maximum Entropy Principle. Chapter 3 in Sung Yong Park, Essays on Maximum Entropy Principles with Applications to Econometrics and Finance. ProQuest (2007)Google Scholar
  11. 11.
    Qin, Z., Li, X., Ji, X.: Portfolio selection based on cross-entropy. Journal of Computational and Applied Mathematics 228, 139–149 (2009)MathSciNetCrossRefMATHGoogle Scholar
  12. 12.
    Rebennack, S., Kallrath, J., Pardalos, P.M.: Energy Portfolio Optimization for Electric Utilities: Case Study for Germany. In: Energy, Natural Resources and Environmental Economics Energy Systems, pp. 221–246 (2010)Google Scholar
  13. 13.
    Rodriguez, J.: A New Portfolio Optimization Based on Entropy. Master thesis, Section of Mathematics, Faculty of Sciences, University of Geneva (2007)Google Scholar
  14. 14.
    Roeddner, W., Gartner, I.R., Rudolph, S.: Entropy-Driven Portfolio Selection: A Downside and Upside Risk Framework. Discussion Paper Number 437. Faculty of Economic Sciences, University of Hagen (2009)Google Scholar
  15. 15.
    Sovacool, B.K.: Valuing the greenhouse gas emissions from nuclear power: A critical survey. Energy Policy 36, 2940–2953 (2009)Google Scholar
  16. 16.
    Sudtasan, T., Suriya, K.: Nuclear power plant after Fukushima incident: Lessons from Japan to Thailand for choosing power plant options. The Empirical Econometrics and Quantitative Economics Letters 1(3), 1–8 (2012)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of EconomicsChiang Mai UniversityChiang MaiThailand

Personalised recommendations