• Energy Research

The objective of the predispatch of a hydroelectric system is to produce an hourly generation schedule that does not violate electrical constraints and meets weekly generation targets for each hydro plant. The predispatch can therefore be seen as a link between operation planing and the on-line generation scheduling. This paper presents a decomposition approach to the solution of the predispatch problem, which is modeled as a large-scale linear program and solved by Dantzig-Wolfe decomposition. The subproblems in this decomposition correspond to hourly optimal rescheduling problems and are solved by an efficient version of the Dual Simplex method. Core and CPU requirements are thus greatly reduced. A case study with the Brazilian Southeast netwrk is presented and discussed.

In this paper we describe a new Benders decomposition approach to solve power transmission network expansion planning problems. This new approach is characterized by using a linear (0-1) disjuntctive model which ensures the optimality of the solution found and by using additional constraints, iteratively evaluated, besides the traditional Benders cuts. The results obtained, considering a real world power transmission network expansion planning study with the southeastern Brazilian system, show the efficiency of this approach.

Artículos en revistas This paper discusses the challenges in the procurement of electricity. The primary challenge faced by the countries in Latin America is to ensure sufficient capacity and investment to reliably serve their growing economies. The turn of the century brought different challenges to the energy supply in the region and to its market policy emphasis, coupled with a worldwide rocketing up of fuel prices. info:eu-repo/semantics/publishedVersion

Abstract This paper describes an algorithm for calculating optimal operating strategies in a multi-reservoir hydroelectric system, which can take into account inflow stochasticity and does not require discretization of the state space. The solution approach, called stochastic dual dynamic programming (SDDP), is based on the approximation of the expected-cost-to-go functions of stochastic dynamic programming at each stage by piecewise linear functions. These approximate functions are obtained from the dual solutions of the scheduling problem at each stage and may be interpreted as Benders' cuts in a stochastic, multistage decomposition algorithm. Case studies with the Brazilian systems are presented and discussed.

Hydrothermal systems optimal scheduling requires the representation of uncertainties in future inflows in order to hedge against adverse future low inflows by committing thermal plants, and also to store water in reservoirs while avoiding spillage when high future inflows occur. Stochastic optimization technics has been widely used as a tool for long-term hydrothermal scheduling. These models rely on Monte Carlo simulation in order to capture the inflow uncertainty during the planning horizon. Since the parameters of these models are typically estimated from historical data, it is not surprising that the actual performance of a chosen reservoirs strategy often significantly differs from the designer's initial expectations due to unavoidable modeling ambiguity. The objective of this work is to assess the impact of inflow parameter uncertainty on the stochastic hydrothermal scheduling. The results presented in this work may be useful for the improvement of stochastic optimization techniques. The results presented show that the uncertainty on the parameters of the stochastic model consists on a supplementary source of risk that should be taken into account in the scheduling model.

The authors describe the implementation of existing power system applications in a concurrent programming environment. The tools used comprise a multiprocessor computing system with concurrent processing software facilities and a concurrent processing simulator for assisting in problem partition and debugging. The goal is to obtain shorter execution times taking into account the solution structure. Three case studies are used to illustrate the application of the above tools and the development methodology: multiarea reliability, system analysis model, and security-constrained dispatch with postcontingency corrective rescheduling. Results obtained show a very high efficiency in the use of the concurrent processors. >

Artículos en revistas The optimal scheduling of hydrothermal systems requires the representation of uncertainties in future streamflows to devise a cost-effective operations policy. Stochastic optimization has been widely used as a powerful tool to solve this problem but results will necessarily depend on the stochastic model used to generate future scenarios for streamflows. Periodic autoregressive (PAR) models have been widely used in this task. However, its parameters are typically unknown and must be estimated from historical data, incorporating a natural estimation error. Furthermore, the model is just a linear approximation of the real stochastic process. The consequence is that the operator will be uncertain about the correct linear model that should be used at each period. The objective of this work is to assess the impacts of incorporating the uncertainty of the parameters of the PAR models into a stochastic hydrothermal scheduling model. The proposed methodology is tested with case studies based on data from the Brazilian hydroelectric system. It is shown that when the uncertainty of the parameters is ignored, the policies given by the stochastic optimization tend to be too optimistic. info:eu-repo/semantics/publishedVersion

This paper presents a technique for the evaluation of loss of load probalility (LOLP) in hydrothermal generating systems. LOLP evaluation is carried out by a mixed simulation/analytical approach that takes into account the effect of reservoir depletion on the output capacities of the hydroelectric units. The characteristic behaviour of generation reliability indices in hydro systems is illustrated by a case study using the Brazilian South/Southeast configuration.