Abstract—In mathematical optimization uncertainty is expressed through scenarios. auto-regressive integrated moving average (ARIMA) is one of the known practice to generate scenarios. This paper is about scenario generation using multivariate data: electrical power demand, wind power generation and energy market price. An ARIMA model along with Copula is implemented for scenario generation. The results are presented and discussed.
Index Terms—Multivariate scenario generation, ARIMA, Copula, Stochastic programming
S. Mishra and I. Palu are with Tallinn University of Technology, Tallinn, Estonia (e-mail: sambeet.mishra@ttu.ee).
C. Würsig is with Leibniz Universität Hannover, Germany
C. Bordin is with SINTEF Energy Research, Trondheim, Norway
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Cite: S. Mishra, C. Würsig, C. Bordin, and I. Palu, "Multivariate Scenario Generation －An Arima and Copula Approach," International Journal of Modeling and Optimization vol. 9, no. 3, pp. 146-149, 2019.
