Investment Profitability Analysis for Wind Power Project in Taiwan

Abstract:

In this paper, fuzzy financial evaluation models are derived to analysis investment financial profitability and possibility for wind power generation project in Penghu, Taiwan. The financial subsidy and feed-in tariff (FIT) are two effective market mechanisms to promote wind power development in Taiwan. The performances of the proposed fuzzy profit models are verified by considering their application to a simulation case. The study shows the fuzzy financial indexes of the simulated 2,400 kW wind power project may little uneconomic possibility, with negative net present value, with benefit cost ratio smaller than 1, and with payback years longer than its life span, in both two scenarios. The FIT rates should be revised to match wind power current market to give more attractiveness for potential investors. The studied results are also consistent with those provided by the conventional crisp models, and provide readily implemented possibility analysis tools for use in the arena of uncertain finance.

• Periodical: Applied Mechanics and Materials (Volume 835)
• Pages: 753-759
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.835.753
• Online since: May 2016
• Authors: J.N. Sheen*
• Keywords: Feed-In Tariff, Financial Return, Fuzzy Ranking, Possibility Analysis, Wind Generation

References

[1] Bureau of Energy, MOE Taiwan, Framework of Taiwan's sustainable energy policy, available: http: /www. moeaboe. gov. tw/, May (2015).

[2] Green Energy and Environment Research Laboratories, Industrial Technology Research Institute, Thousand Turbines Project, http: /www. twtpo. org. tw/eng/Home.

[3] J.N. Sheen, Fuzzy financial profitability analyses of demand side management alternatives from participant perspective, Inform. Sci. 169 (2005) 329-364.

DOI: 10.1016/j.ins.2004.05.007

[4] J.N. Sheen, Fuzzy financial decision-making: load management programs case study, IEEE T. Power. Syst. 20 (2005) 1808-1817.

DOI: 10.1109/tpwrs.2005.856994

[5] J.J. Buckley, The Fuzzy Mathematics of Finance, Fuzzy Sets. Syst. 21 (1987) 257-273.

DOI: 10.1016/0165-0114(87)90128-x

[6] A. Kaufmann and M.M. Gupta, Fuzzy Mathematical Models in Engineering and Management Science, Elsevier Science Publishers B.V. (1988).

[7] C.Y. Chiu and C.S. Park, Fuzzy Cash Flow Analysis using Present Worth Criterion, Eng. Economist. 39 (1994) 113-137.

DOI: 10.1080/00137919408903117

[8] C. Kahraman, D. Ruan and E. Tolga, Capital budgeting techniques using discounted fuzzy versus probabilistic cash flows, Inform. Sci. 142 (2002) 57-76.

DOI: 10.1016/s0020-0255(02)00157-3

[9] L.A. Zadeh, The concepts of a linguistic variable and its application to approximate reasoning, Part 1, 2 and 3, Inform. Sci. 8 (1975) 199-249, 301-357 and 9 (1975) 43-80.

DOI: 10.1016/0020-0255(75)90046-8

[10] D. Dubois and H. Prade, Fuzzy Sets and Systems: Theory and Applications, Academic Press, New York, (1980).

[11] C.S. Park, The Mellin Transform in Probabilistic Cash Flow Modeling, Eng. Economist, 32 (1987) 115-134.

DOI: 10.1080/00137918608902958

[12] W.C. Giffin, Transform Techniques for Probability Modeling, Academic Press, New York, (1975).

[13] J.N. Sheen, MT Tsay and S.W. Wu, A benefits analysis for wind turbine allocation in a power distribution system, Energ. Convers. Manage. 68 (2013) 305-312.

DOI: 10.1016/j.enconman.2012.12.022

[14] T.P. Chang, Wind energy assessment incorporating particle swarm optimization method, Energ. Convers. Manage. 52 (2011) 1630-1637.

DOI: 10.1016/j.enconman.2010.10.024

[15] Y.K. Wu, et. Al. Planning 10 onshore wind farms with corresponding interconnection network and power system analysis for low-carbone-island development on Penghu Island, Taiwan, Renew. Sust. Energ. Rev. 19 (2013) 531-540.

DOI: 10.1016/j.rser.2012.10.043