ARTIFICIAL INTELLIGENT SYSTEM FOR MEASUREMENT OF HARMONIC POWERS - Jovitha Jerome; P. Vinoth (Universitas Gadjah Mada, 2008)
The importance of the electric power quality (PQ) demands new methodologies and measurement tools in the power industry for the analysis and measurement of the basic electric magnitudes necessary. This paper presents a new measurement procedure based on neural networks for the estimation of harmonic amplitudes of current/voltage and respective harmonic powers. The measurement scheme is built with two neural network modules. The first module is an adaptive linear neuron (ADALINE) that is the kernel part of estimation of complex harmonic coefficients of the current/voltage. The second module is feedforward neural network that obtains the harmonic active/reactive powers. In order to perform digital simulation the Feedforward and Adaline neural network tools were developed in LabVIEW. This measurement algorithm was tested for the practical cases and found to be robust, computationally fast and efficient.