Abstract:The solar photovoltaic (PV) energy has an important place among the renewable energy sources. Therefore, several researchers have been interested by its modelling and its prediction, in order to improve the management of the electrical systems which include PV arrays. Among the existing techniques, artificial neural networks have proved their performance in the prediction of the solar radiation. However, the existing neural network models don't satisfy the requirements of certain specific situations such as the one analyzed in this paper. The aim of this research work is to supply, with electricity, a race sailboat using exclusively renewable sources. The developed solution predicts the direct solar radiation on a horizontal surface. For that, a Nonlinear Autoregressive Exogenous (NARX) neural network is used. All the specific conditions of the sailboat operation are taken into account. The results show that the best prediction performance is obtained when the training phase of the neural network is performed periodically.

Regarding doubly fed induction generator (DFIG) operation, unbalanced and harmonically distorted grid voltage conditions have been treated as two separate control problems. This paper reports a solution for the rotor-and grid-side power converters, which allows one to keep the DFIG successfully in operation under both grid voltage conditions. The proposed solution is based on sliding-mode control (SMC). The rotor-side converter is commanded so that the electromagnetic torque and the stator reactive power remain free of fluctuations that arise during grid voltage disturbances. Meanwhile, the grid-side converter ensures both constant DC-link voltage and steady active power output from the overall system. The developed algorithms turn out being robust against parameter variations and of fast dynamic response. In addition, none of the converters need either voltage or current positive and negative sequences extraction. The simulation results presented demonstrate the appropriateness of SMC to face such disturbed scenarios. Finally, the stability proof of both converters' control algorithms is provided in the appendices.Index Terms-Doubly fed induction generators, harmonic distortion, power control, unbalanced voltage, variable structure systems, wind power generation . NOMENCLATURE C eqDC-link equivalent capacitance. e n Grid voltage's space vector. i g Grid-side converter current's space vector. i r , i s Rotor and stator currents' space vectors. L g Grid-side line inductance. L m , L r , L s Magnetizing, rotor and stator inductances. L σ r , L σ s Rotor and stator leakage inductances. P Number of pole pairs. P e Electromagnetic power. P g , Q gGrid-side converter output active and reactive powers.

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In this paper, the transient operation of a four-leg inverter equipped with an innovative control strategy under unbalanced load conditions is investigated. The inverter is proposed for transformerless hybrid power system applications, in order to provide simultaneous supply of three-phase and single-phase ac loads with balanced voltage and constant frequency. The four-leg inverter is controlled to ensure balanced voltage by means of a control strategy based on the decomposition of the supply three-phase voltage and current into instantaneous positive, negative, and homopolar sequence components using phasor representation. These three sequences are controlled independently in their own reference frames as dc signals. The implementation derived for the controller design is also described. The transient operation performance of the proposed control strategy has been tested in simulations with an average model and experimentally using a laboratory prototype.Index Terms-Current control, dc-ac power conversion, hybrid power integration, inverters, power quality, symmetrical components, unbalance, voltage control.

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