In this paper, both standard IEEE test systems 57-bus and Algerian 59-bus are considered. To enhance the power flow of these two considerable networks in terms of voltage profile and reduce the real and reactive total transmission losses, the inclusion of flexible alternating current transmission systems (FACTS) devices is one of the best solutions. For this, a static synchronous compensator (STATCOM) is proposed. Our code is written in the MATLAB computing environment, based on finding the weakest buses in the network, and placing one or two STATCOMs in an appropriate place; in the next step, there would be recalculation of the power flow again. The results of power flow compared with the popular MATPOWER software environment show the exactitude of our code calculation, and the enhancement of voltage profile, especially in buses where STATCOM is placed. Furthermore, the reduction of real and reactive losses shows the effectiveness of the FACTS device proposed.

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-This paper presents a new method of classification of the induction machine faults using Time Frequency Representation, Particle Swarm Optimization and artificial neural network. The essence of the feature extraction is to project from faulty machine to a low size signal time-frequency representation (TFR), which is deliberately designed for maximizing the separability between classes, a distinct TFR is designed for each class. The feature vectors size is optimized using Particle Swarm Optimization method (PSO). The classifier is designed using an artificial neural network. This method allows an accurate classification independently of load level. The introduction of the PSO in the classification procedure has given good results using the reduced size of the feature vectors obtained by the optimization process. These results are validated on a 5.5-kW induction motor test bench.

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