Skip to Main Content
Real-time evaluation of power quality is a desired feature in research and industrial projects, especially when embedded systems are employed and/or studied. Fast Fourier Transforms FFT is commonly used to evaluate the harmonic content of electric signals. Artificial Neural Networks (ANN) are also employed for harmonics estimation with short processing time and low implementation complexity. Commercial power quality measurement systems are available and offer good performance, communication and storage capabilities, and other special features, however in most of them the real-time information is not available or it is offered with important communication delays. This paper presents the implementation of a measurement system using Xilinx FPGA target and the Adaptive Linear Neuron (ADALINE) algorithm for real-time evaluation of power quality. Experimental results show that the implemented system can be employed for power quality monitoring and embedded control applications.