Djalma M. Falcão

Simultaneous tuning of power system damping controllers using genetic algorithms

This paper presents a method that simultaneously tune multiple power system damping controllers using genetic algorithms (GAs). Damping controller structures are assumed to be fixed consisting basically of lead-lag filters. The tuning method takes robustness into consideration as it guarantees system stabilization over a prespecified set of operating conditions. Modified GA operators are used in the simultaneous optimization of both phase compensations and gain settings for the stabilizers. The method is applied for global PSS tuning to the well-known New England system and to the coordinated tuning of 22 PSSs in a 1762-bus modified equivalent South-Southeastern Brazilian system.

Parallel and distributed state estimation

The need for higher frequency in state estimation execution covering larger supervised networks has led to the investigation of faster and numerically more stable state estimation algorithms. However, technical developments in distributed Energy Management Systems, based on fast data communication networks, open up the possibility of parallel or distributed state estimation implementation. In this paper, this possibility is exploited to derive a solution methodology based on conventional state estimation algorithms and a coupling constraints optimization technique. Numerical experiments show suitable performance of the proposed method with regard to estimation accuracy, convergence robustness and computational efficiency. The results of these experiments also indicate the decoupled nature of the state estimation problem. >

Impact of distributed generation allocation and sizing on reliability, losses and voltage profile

This work presents a methodology for evaluating the impact of DG units installation on electric losses, reliability and voltage profile of distribution networks. The losses and voltage profile evaluation is based on a power flow method with the representation of generators as PV buses. The reliability indices evaluation is based on analytic methods modified to handle multiple generations. The methodology may be used to evaluate the influence of the local of installation and the capacity of DG on these system performance characteristics for different generation expansion planning alternatives. The results obtained with the proposed methodology for systems extracted from the literature demonstrates its applicability.

Probabilistic Wind Farms Generation Model for Reliability Studies Applied to Brazilian Sites

This paper presents a computer model for the probabilistic representation of wind farms generation for reliability studies, which can provide an annual estimation of energy production and calculate several performance indexes. The model combines the stochastic characteristics of wind speed with the operational information of the turbines, such as the failure and repair rates, representing the wind farm by a Markov process. The simulations are made with real time series of wind speed of several Brazilian regions and actual turbine models. The influence of some wind farm and installation site characteristics on the results are evaluated, such as the wind speed statistical clustering technique, the number and type of the turbines, and the failure and repair rates. The results obtained reproduce successfully the behavior of the components considered in the model

Bibliography on power system state estimation (1968-1989)

A comprehensive bibliography on power system state estimation, covering a period of approximately two decades, is presented. As no similar work had been published previously, this bibliography was elaborated to be a consulting guide for researchers interested in the subject. It is noted that there was a growing interest in power system state estimation, particularly in the first 15 years of research, with focus on the development of algorithms and bad-data processing. It is also noted that, some relevant areas still need special attention, such as the integrated analysis of bad data and topological errors. >

Composite reliability evaluation by sequential Monte Carlo simulation on parallel and distributed processing environments

This paper describes two parallel methodologies for composite reliability evaluation using sequential Monte Carlo simulation. The methodologies are based on coarse grain asynchronous implementations. In the first methodology, a complete simulation year is analyzed on a single processor and the many simulated years necessary for convergence are analyzed in parallel. In the second methodology, the adequacy analysis of the system operating states within the simulated years is performed in parallel and the convergence is checked on one processor at the end of each simulated year. The methodologies are implemented on a 10 nodes IBM RS/6000 SP scalable distributed memory parallel computer and on a network of 8 IBM RS/6000 43P workstations. The results obtained in tests with actual power system models showed high speedup and efficiency on both parallel platforms.

Conjugate gradient methods for power system dynamic simulation on parallel computers

Parallel processing is a promising technology for the speedup of the dynamic simulations required in power system transient stability analysis. In this paper, three methods for dynamic simulation on parallel computers are described and compared. The methods are based on the concepts of spatial and/or time parallelization. In all of them, sets of linear algebraic equations are solved using different versions of conjugate gradient methods which have been successfully applied in other scientific and engineering applications. The algorithms presented in the paper were tested in a commercially available parallel computer using an actual large power system model. The results obtained in the tests showed a considerable reduction in computation time.

Parallel implementation of a power system dynamic simulation methodology using the conjugate gradient method

The authors present results of tests with a parallel implementation of a power system dynamic simulation methodology for transient stability analysis in a parallel computer. The test system is a planned configuration of the interconnected Brazilian South-Southeastern power system with 616 buses, 995 lines, and 88 generators. The parallel machine used in the computer simulation is a distributed memory multiprocessor arranged in a hypercube topology architecture. The nodes are based on the Inmos T800 processors with 4 Mbytes of local memory. The simulation methodology is based on the interlaced alternating implicit integration scheme in which the network equations are re-ordered such that the network admittance matrix appears in the block bordered diagonal form and is then solved by a combined application of the LU factorization and the conjugate gradient method. The results obtained show considerable reduction in the simulation time. >

State estimation and observability analysis based on echelon forms of the linearized measurement models

This paper introduces an alternative approach for power system state estimation and observability analysis. The method is based on the analysis of the active and reactive linearized measurement models in the echelon form. This form is a generalization of matrix triangular factorization for the case of rectangular matrices. The proposed approach represents an evolution of the least absolute value state estimation method. The state estimate produced by the proposed method presents some of the basic characteristics of that obtained with the least absolute value estimator but the overall methodology is simpler and more general while unifying measurement noise filtering, bad data detection and identification, and observability analysis under the same algorithmic framework. >

High Performance Computing in Power System Applications

This paper presents a review of the research activities developed in recent years in the field of High Performance Computing (HPC) application to power system problems and a perspective view of the utilization of this technology by the power industry. The paper starts with a brief introduction to the different types of HPC platforms adequate to power system applications. Then, the most computer intensive power system computation models are described. Next, the promising areas of HPC application in power system are commented. Finally, a critical review of the recent developed research work in the field, along with prospective developments, is presented.