مدل موی فاقی فصلی دوره ای برای شبیه سازی جریان چند سایت

Operational strategies of the Brazilian Electric Sector have direct impacts on operating costs, energy prices, planning the expansion of the system, etc. These decisions are taken under a high level of uncertainty, as the future availability of water for energy generation is a stochastic variable. Computational models, routinely based on stochastic optimization, support these decisions. Some of them make use of streamflow scenarios as entries. In this way, the aim of this paper is to develop a sophisticated statistical model for multi-site stochastic streamflow simulation. Our approach is based on the extension of vine copulas for high dimensional spatial applications. The proposed model copes with both temporal and spatial dependencies of streamflows. At the same time, it can simulate numerous sites concurrently. We tested our approach on streamflow data from 39 Brazilian hydroelectric power plants. The results indicate that the model can simulate streamflow scenarios largely preserving the features observed in the recorded streamflow data.