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.

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.

Smart Grids (SGs) constitute the evolution of the traditional electrical grid towards a new paradigm, which should increase the reliability, the security and, at the same time, reduce the costs of energy generation, distribution and consumption. Electrical microgrids (MGs) can be considered the first stage of this evolution of the grid, because of the intelligent management techniques that must be applied to assure their correct operation. To accomplish this task, sensors and actuators will be necessary, along with wireless communication technologies to transmit the measured data and the command messages. Wireless Sensor and Actuator Networks (WSANs) are therefore a promising solution to achieve an intelligent management of MGs and, by extension, the SG. In this frame, this paper surveys several aspects concerning the application of WSANs to manage MGs and the electrical grid, as well as the communication protocols that could be applied. The main concerns regarding the SG deployment are also presented, including future scenarios where the interoperability of different generation technologies must be assured.