Tratamento de Dados Espúrios na Estimação de Estados via Algoritmo de Otimização Aritmética

Abstract

The objective of this work is to use a recently developed meta-heuristic and not very widespread in the field of electrical power systems, whose name is Arithmetic Optimization Algorithm (AOA), to correct bad data in the state estimation (SE) process. Thus, a SE algorithm is proposed based on the weighted least squares method and, after its convergence, bad data detection and identification procedures are performed by statistical methods based on the maximum normalized residual. Finally, an optimization problem is formulated with the purpose of calculating calibration factors for the suspicious measurements, ensuring a correct estimate of the electrical quantities with low estimation errors when compared with the actual values. Simulations were performed in the IEEE 30 bus transmission system and the results show the applicability and efficiency of the Arithmetic Optimization Algorithm in solving the problem in terms of the optimality of the solution and the computational effort allowing its use for decision making in real time in control centers.