Using Copulas for Modeling Dependence in Wind Power
Keywords:Wind Speed, COPULA Method, Marginal Modeling.
Wind power is clean and renewable source of energy in all countries and circles. Moreover, wind power is one of the worldâ€™s largest and most accessible sources of renewable energy. In this paper, marginal distributions were fitted to each of the variables and to examine the relationship between wind speed of Elazig, Bitlis and Van with COPULA method. The results show that there is a weak dependence between wind speed of Elazig, Bitlis and Van.
Grothe, O., & Schnieders, J. 2011. Spatial dependence in wind and optimal wind power allocation: A copula- based analysis. Energy policy, 39(9):4742-4754.
Hagspiel, S., Papaemannouil, A., Schmid, M., & Andersson, G. 2012. Copula-based modeling of stochastic wind power in Europe and implications for the Swiss power grid. Applied energy, 96: 33-44.
DÃaz, G., GÃ³mez-Aleixandre, J., & Coto, J. 2014. Statistical characterization of aggregated wind power from small clusters of generators. International Journal of Electrical Power & Energy Systems, 62: 273-283.
Haghi, H. V., Bina, M. T., Golkar, M. A., & Moghaddas-Tafreshi, S. M. 2010. Using Copulas for analysis of large datasets in renewable distributed generation: PV and wind power integration in Iran. Renewable Energy, 35(9): 1991-2000.
Bilgen, S., KeleÅŸ, S., Kaygusuz, A., SarÄ±, A., & Kaygusuz, K. 2008. Global warming and renewable energy sources for sustainable development: a case study in Turkey. Renewable and sustainable energy reviews, 12(2): 372-396.
Kaplan, Y. A. 2015. Overview of wind energy in the world and assessment of current wind energy policies in Turkey. Renewable and Sustainable Energy Reviews, 43: 562-568.
IlkÄ±lÄ±Ã§, C., AydÄ±n, H., & BehÃ§et, R. (2011). The current status of wind energy in Turkey and in the world. Energy policy, 39(2): 961-967.
Sklar. 1959. Fonctions de rÃ©partition Ã n dimensions et leurs marges. Publ. Inst. Statist. Univ. Paris, 229-231.
Genest, C., MacKay, J. 1986. The joy of copulas: Bivariate distributions with uniform marginals. The American Statistician, 40(4): 280-283.
Genest, C., & Rivest, L. P. 1993. Statistical inference procedures for bivariate Archimedean copulas. Journal of the American Statistical Association, 88(423): 1034-1043.
CapÃ©raÃ , P., FougÃ¨res, A. L., Genest, C. 1997. A nonparametric estimation procedure for bivariate extreme value copulas. Biometrika, 84(3): 567-577.
Nelsen, R. B. 1997. Dependence and order in families of Archimedean copulas. Journal of Multivariate Analysis, 60(1): 111-122.
R. B. Nelsen, (2006) An Introduction to Copulas, 2nd ed., Springer, New York.
Genest, C., Favre, A. C. 2007. Everything you always wanted to know about copula modeling but were afraid to ask. Journal of hydrologic engineering, 12(4): 347-368.
Genest, C., NeÅ¡lehovÃ¡, J. 2007. A primer on copulas for count data. ASTIN Bulletin: The Journal of the IAA, 37(2): 475-515.
Nelsen, R. B., Quesada-Molina, J. J., RodrÃguez-Lallena, J. A., Ãšbeda-Flores, M. 2008. On the construction of copulas and quasi-copulas with given diagonal sections. Insurance: Mathematics and Economics, 42(2): 473-483.
Genest, C., RÃ©millard, B., Beaudoin, D. 2009. Goodness-of-fit tests for copulas: A review and a power study. Insurance: Mathematics and economics, 44(2): 199-213.
Bessa, R. J., Miranda, V., Botterud, A., Zhou, Z., & Wang, J. 2012. Time-adaptive quantile-copula for wind power probabilistic forecasting. Renewable Energy, 40(1): 29-39.
BouyÃ©, E., Salmon, M. 2013. Dynamic copula quantile regressions and tail area dynamic dependence in Forex markets. In Copulae and Multivariate Probability Distributions in Finance (pp. 125-154). Routledge.
Lu, Q., Hu, W., Min, Y., Yuan, F., & Gao, Z. 2014. Wind power uncertainty modeling considering spatial dependence based on pair-copula theory. In PES General Meeting| Conference & Exposition, 2014 IEEE (pp. 1-5). IEEE.
Zhang, N., Kang, C., Xia, Q., & Liang, J. 2014. Modeling conditional forecast error for wind power in generation scheduling. IEEE Transactions on Power Systems, 29(3):1316-1324.
How to Cite
- Papers must be submitted on the understanding that they have not been published elsewhere (except in the form of an abstract or as part of a published lecture, review, or thesis) and are not currently under consideration by another journal published by any other publisher.
- It is also the authors responsibility to ensure that the articles emanating from a particular source are submitted with the necessary approval.
- The authors warrant that the paper is original and that he/she is the author of the paper, except for material that is clearly identified as to its original source, with permission notices from the copyright owners where required.
- The authors ensure that all the references carefully and they are accurate in the text as well as in the list of references (and vice versa).
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Attribution-NonCommercial 4.0 International that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
- The journal/publisher is not responsible for subsequent uses of the work. It is the author's responsibility to bring an infringement action if so desired by the author.