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This paper describes an apparatus for generating a signal representative of steady-state and transient disturbances in three-phase waveforms of an ac electrical system as described in IEEE Std 1159-09. It can be configured as a synthesizer of randomly distorted signals for different applications: for testing the effects of disturbed grid on equipment and to generate patterns of electrical disturbances for the training of artificial neural networks, which are used for measuring power quality tasks. For the first purpose, voltage and current amplifiers are added in the output stage, which allows the generation of disturbed signals at grid level.

Power Quality is defined as the study of the quality of electric power lines. The detection and classification of the different disturbances which cause power quality problems is a difficult task which requires a high level of engineering expertise. Thus, neural networks are usually a good choice for the detection and classification of these disturbances. This paper describes a powerful system, developed by the Electronic Technology Department at the University of Seville and the Institute for Natural Resources and Agrobiology at the Scientific Research Council (CSIC) for the generation and detection by means of neural networks of electrical disturbances.

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