Abstract
One of the most difficult issues for using wind power in practice is that the power output largely depends on the wind condition, and as a result, the future output may be volatile or uncertain. Therefore, the forecast of power output is considered important and is key to electric power generating industries making the wind power electricity market work properly. However, the use of forecasts may cause other problems due to “forecast errors”. The objective of this chapter is to summerize conventional tools to manage such risks in the wind power electricity market. In particular, we focus on possible insurance claims or the so-called weather derivatives, which are contracts written on weather indices whose values are constructed from weather data.
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Notes
- 1.
See http://www.wrma.org/.
- 2.
- 3.
All the data used in this chapter were provided by ITOCHU Techno-Solutions Corporation.
References
Jewson S, Brix A and Ziehmann C (2005) Weather derivative valuation—the meteorological statistical financial and mathematical foundations. Cambridge University Press, Cambridge
Yamada Y (2008) Optimal hedging of prediction errors using prediction errors. Asia-Pacific Finan Mark 15(1):67–95
Brody DC, Syroka J, Zervos M (2002) Dynamical pricing of weather derivatives. Quant Financ 2:189–198
Cao M, Wei J (2004) Weather derivatives valuation and market price of weather risk. J Futures Mark 24(11):1065–1089
Davis M (2001) Pricing weather derivatives by marginal value. Quant Financ 1:305–308
Kariya T (2003) Weather risk swap valuation Working Paper Institute of Economic Research. Kyoto University, Japan
Platen E, West J (2004) Fair pricing of weather derivatives. Asia-Pacific Finan Mark 11(1):23–53
Yamada Y (2007) Valuation and hedging of weather derivatives on monthly average temperature. J Risk 10(1):101–125
Yamada Y, Iida M, and Tsubaki H (2006) Pricing of weather derivatives based on trend prediction and their hedge effect on business risks. Proc inst stat math 54(1):57–78 (in Japanese)
Harrison JM, Pliska SR (1981) Martingales and stochastic integrals in the theory of continuous trading. Stoch Process Appl 11(3):215–260
Black F, Scholes M (1973) The pricing of options and corporate liabilities. J Polit Econ 81:637–654
Merton RC (1973) Theory of rational option pricing. Bell J Econ Manage Sci 4(1):141–183
Shreve SE (2004) Stochastic calculus for finance (2): continuous-time models. Springer, New York
Takano T (2006) Natural Energy Power and Energy Storing Technology, trans Inst Electri Eng Jpn (B) 126(9):857–860 (in Japanese)
Wood SN (2006) Generalized additive models: an introduction with R. Chapman and Hall, London
Hastie T, Tibshirani R (2005) Generalized additive models. Cambridge University Press, Cambridge
Enomoto S, Inomata N, Yamada T, Chiba H, Tanikawa R, Oota T and Fukuda H (2001)Prediction of power output from wind farm using local meteorological analysis. Proceedings of European Wind Energy Conference, Copenhagen, Denmark, p 749–752
Tanikawa R (2001) Development of the wind simulation model by LOCALS and examination of some studies, Nagare, p.405–415 (in Japanese)
Yamada Y (2008) Optimal design of wind derivatives based on prediction errors. JAFEE J 7:152–181 (in Japanese)
Tanabe T, Sato T, Tanikawa R, Aoki I, Funabashi T, and Yokoyama R (2008) Generation scheduling for wind power generation by storage battery system and meteorological forecast. IEEE Power and Energy Society General Meeting—Conversion and Delivery of Electrical Energy in the 21st Century, pp 1–7
Geman H (1999) Insurance and Weather Derivatives, Risk Books
Takezawa K (2006) Introduction to nonparametric regression. Wiley, New Jersey
Acknowledgments
The author would like to thank H. Fukuda, R. Tanikawa, and N. Hayashi from ITOCHU Techno-Solutions Corporation for their helpful comments and discussions.
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Yamada, Y. (2013). Risk Management Tools for Wind Power Trades: Weather Derivatives on Forecast Errors. In: Pardalos, P., Rebennack, S., Pereira, M., Iliadis, N., Pappu, V. (eds) Handbook of Wind Power Systems. Energy Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41080-2_3
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