Abstract
Despite widespread availability, the nature of renewable energy resources is yet to understand fully to harness their optimum benefits. The aggregated portfolio and inter-play of geographically spread wind farms/resources is critical for intelligent extrapolation, yet less explored. In this paper, we focus on understanding the dependency structure of wind speeds. A multivariate cumulative distribution function- ”Copula” is used to find the joint distribution of wind speed pairs. We have investigated copula family selection for varying wind speed pair distances ranging from 3 to 2700km. A case study for Joe-Frank (BB8) copula shows efficient joint distribution fit for a selected wind speed pair with a standard error of 0.0094.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
