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Correction of power grid parameters using Genetic Algorithms

Power system state estimation (SE) has been widely used in energy management systems for data validation. Power grid parameter values are among the data submitted to SE, since they are often badly affected by inaccurate manufacturer information; poor estimation of transmission line lengths/sags; power grid design changes inadequately updated in the corresponding database; error calculation; etc. This paper presents an intelligent method for the detection, identification, and correction of grid parameter errors, exploring the SE results. An offline procedure for validation of grid parameters using a Micro-Genetic Algorithm (μGA) is proposed. Tests performed on the IEEE 14-bus benchmark system illustrate the proposed methodology.