Abstract
Decision-making processes need the support of analytical methods that are able to adequately capture the complexity of reality. Welldeveloped and well-established theories, such as the modern portfolio theory introduced by Harry M. Markowitz in 1952, are often based on probability theory and widely used for both financial and real assets. However, a number of empirical studies have shown that the Markowitz approach captures reality only to a very limited extent. In this paper, we propose fuzzy set theory as an alternative to the classical probabilistic approach. More specifically, we investigate the usefulness of a fuzzy portfolio selection model, where an investor’s aspiration levels of a portfolio’s return and risk are taken into account and expressed by membership functions. We define portfolio risk as a downside risk measure and introduce a fuzzy semi-mean absolute deviation portfolio selection model that is applied in order to optimize mixes of power generation plants.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
S. Awerbuch and M. Berger. Applying portfolio theory to EU electricity planning and policy-making. OECD/IEA, Paris, 2003.
D. Bar-Lev and S. Katz. A portfolio approach to fossil fuel procurement in the electric utility industry. Journal of Finance, 31(3):933–947, 1976.
M. Bazilian and F. Roques. Analytical Methods for Energy Diversity and Security – Portfolio Optimization in Energy Sector: A Tribute to the work of Dr Shimon Awerbuch. Elsevier Ltd., 2008.
J. Borchert and R. Schemm. Einsatz der Portfoliotheorie im Asset Allokations-Prozess am Beispiel eines fiktiven Anlageraums von Windkraftstandorten. Zeitschrift für Energiewirtschaft, 31(4):311–322, 2007.
B. Glensk and R. Madlener. Fuzzy portfolio optimization for power generation assets. FCN Working Paper No. 10/2010, Institute for Future Energy Consumer Needs and Behavior, School of Business and Economics/E.ON Energy Research Center, RWTH University, Aachen, August, 2010.
H. Konno and T. Koshizuka. Mean-absolute deviation model. IIE Transactions, 25:893–900, 2005.
H. Konno and H. Yamazaki. Mean-absolute deviation portfolio optimization model and its application to Tokyo stock market. Management Science, 37(5):519–531, 1991.
R. Madlener. Portfolio optimization of power generation assets. In Q.P. Zheng, S. Rebennack, P.M. Pardalos, M.V.F. Pereira, and N.A. Iliadis, editors, Handbook of CO2 in Power Systems. Springer, Berlin/Heidelberg/New York, 2012.
R. Madlener and B. Glensk. Portfolio impact of new power generation investments of E.ON in Germany, Sweden and in UK. FCN Working Paper No. 17/2010, Institute for Future Energy Consumer Needs and Behavior, School of Business and Economics/E.ON Eenrgy Research Center, RWTH University, Aachen, November, 2010.
R. Madlener, B. Glensk, and P. Raymond. Investigation of E.ON’s power generation assets by using mean-variance portfolio analysis. FCN Working Paper No. 12/2009, Institute for Future Energy Consumer Needs and Behavior, School of Business and Economics/ E.ON Energy Research Center, RWTH University, Aachen, November, 2009.
R. Madlener, B. Glensk, and V. Weber. Fuzzy portfolio optimization on onshore wind power plants. FCN Working Paper No. 10/2011, Institute for Future Energy Consumer Needs and Behavior, School of Business and Economics/E.ON Energy Research Center, RWTH University, Aachen, November, 2011.
H.M. Markowitz. Portfolio selection. The Journal of Finance, 7(1): 77–91, 1952.
F.A. Roques, D.M. Newbery, and W.J. Nuttall. Fuel mix diversification in liberalized electricity markets: A mean-variance portfolio theory approach. Energy Economics, 30(4):1831–1849, 2007.
J. Watada. Fuzzy portfolio selection and its applications to decision making. Tatra Mountains Mathematical Publications, 13(4):219–248, 1997.
L.A. Zadeh. Fuzzy sets. Information and Control, 8(3):338–353, 1965.
L.A. Zadeh. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1(1):3–28, 1978.
H.J. Zimmermann. Fuzzy programming and linear programming with several objective functions. Fuzzy Sets and Systems, 1(1):45–55, 1978.
H.J. Zimmermann. Fuzzy set theory – and its applications. Kluwer Academic Publishers, Dordrecht, the Netherlands, 2001.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer Fachmedien Wiesbaden
About this chapter
Cite this chapter
Glensk, B., Madlener, R. (2014). On the Use of Fuzzy Set Theory for Optimizing Portfolios of Power Generation Assets. In: Lübbecke, M., Weiler, A., Werners, B. (eds) Zukunftsperspektiven des Operations Research. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-05707-7_17
Download citation
DOI: https://doi.org/10.1007/978-3-658-05707-7_17
Published:
Publisher Name: Springer Gabler, Wiesbaden
Print ISBN: 978-3-658-05706-0
Online ISBN: 978-3-658-05707-7
eBook Packages: Business and Economics (German Language)