2009 · 10 citations · 16 references
EngineeringComputer EngineeringElectrical EngineeringField-programmable Gate ArraysOptimizationReconfigurable ComputingDigital Signal ProcessingEvolutionary ComputationField-programmable Gate Array ArchitectureFpga ArchitectureGenetic AlgorithmsPower EstimationField-programmable Gate Arrays (Fpgas)Frequency EstimationGenetic Algorithm OptimizationInstantaneous Frequency EstimationRelay NetworksSignals
This work presents an accurate and precise genetic algorithm (GA) for frequency estimation of electrical power system (EPS) signals. The problem of estimating the frequency of a distorted electrical signal is modeled as an optimization problem. The advantages of GAs in this approach include the use of coding for a number of solutions which facilitates computer implementation, as well as the search for an appropriate solution from a population of possible solutions. The GA is programmed in a FPGA (field-programmable gate array) device and the estimation procedure is performed in real-time. This is made possible due to (a) the implicit parallelism of FPGAs in computing their instructions and (b) the suitable choice of steps of GAs to explore this parallelism. To evaluate the performance of the proposed method, an EPS was simulated having typical operation conditions. The resulting signals were analyzed by the proposed GA-FPGA approach and promising results were compared to a commercial relay.
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Genetic algorithms in search, optimization, and machine learning
Choice Reviews Online · 1989 · 49.3K citations
D. E. Goldberg · Medical Entomology and Zoology · 1989 · 10.1K citations