Abstract
This paper presents the development of an artificial neural network (ANN) controller for a Static Var Compensator (SVC) system compensating unbalanced fluctuating loads. The proposed controller can balance and reduce the reactive power drawn from the source under unbalanced loads while keeping harmonic injection to the system due to SVC operation low. The first stage of controller development is a fuzzy logic based control algorithm. This algorithm determines a number of possible operating states of SVC for a given load condition and calculates corresponding harmonics injections. Then a fuzzy logic system is used to rank those operating states in terms of the magnitude of the reactive power drawn from the source and the harmonic injection level indicated by Total Demand Distortion (TDD). The best operating state is selected based on the ranking score assigned by the fuzzy logic ranking system. Finally, computational speed of the controller is improved by replacing the analytical and fuzzy computations by a set of neural networks trained with data generated with fuzzy logic based controller.
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