Jorge Machado Damázio

Optimal scenario tree reduction for stochastic streamflows in power generation planning problems

The mid-term operation planning of hydro-thermal power systems needs a large number of synthetic sequences to represent accurately stochastic streamflows. These sequences are generated by a periodic autoregressive model. If the number of synthetic sequences is too big, the optimization planning problem may be too difficult to solve. To select a small set of sequences representing the stochastic process well enough, this work employs two variants of the Scenario Optimal Reduction technique. The first variant applies such a technique at the last stage of a tree defined a priori for the whole planning horizon while the second variant combines a stage-wise reduction, preserving the periodic autoregressive structure, with resampling. Both approaches are assessed numerically on hydrological sequences generated for real configurations of the Brazilian power system.

Use Of The Graph Model For Conflict ResolutionIn Water Resources Problems In Brazil

This paper presents an application of the Graph Model for Conflict Resolution (GMCR), developed by Fang et al. [1], for water resources management problems in Brazil. The main aspects of the formal development of the GMCR model are described in terms of its basic components (decision makers, options, strategies and preferences), key concepts (stable states, equilibrium states and stability criteria), and mathematical representation of conflicts by sets of oriented graphs and payoff functions. The equations for the stability analysis of conflicts with at least two decision makers for different stability criteria are provided. The model is used to analyze the importance of the water management institutional system in the solution of a conflict over the use of the water in the Lima Campos/Oros system of reservoirs located in the Northeast of Brazil.