From human mobility to renewable energies: Big data analysis to approach worldwide multiscale phenomena
arXiv:1406.2489 · doi:10.1140/epjst/e2014-02252-5
Abstract
We address and discuss recent trends in the analysis of big data sets, with the emphasis on studying multiscale phenomena. Applications of big data analysis in different scientific fields are described and two particular examples of multiscale phenomena are explored in more detail. The first one deals with wind power production at the scale of single wind turbines, the scale of entire wind farms and also at the scale of a whole country. Using open source data we show that the wind power production has an intermittent character at all those three scales, with implications for defining adequate strategies for stable energy production. The second example concerns the dynamics underlying human mobility, which presents different features at different scales. For that end, we analyze -month data of the Eduroam database within Portuguese universities, and find that, at the smallest scales, typically within a set of a few adjacent buildings, the characteristic exponents of average displacements are different from the ones found at the scale of one country or one continent.
12 pages, 4 figures
References in corpus (10)
- Understanding individual human mobility patterns
- The scaling laws of human travel
- A system of mobile agents to model social networks
- Modeling river delta formation
- Multiple-Time Scaling and Universal Behavior of the Earthquake Interevent Time Distribution
- Quantitative analysis of numerical estimates for the permeability of porous media from lattice-Boltzmann simulations
- Impact of Perturbations on Watersheds
- Statistical Physics Approaches to Seismicity
- How to share underground reservoirs
- Principal wind turbines for a conditional portfolio approach to wind farms