This paper deals with the diagnosis of submarine power cables deployed between a wind turbine floating platform and its seabed electrical substation. These so-called dynamic cables are several hundred meters in length and are subjected to a lifelong motion from the floating structure, waves and marine currents. Another important factor which may greatly affect its hydrodynamic drag and cooling is the undesirable accumulation of biological organisms called either biofouling. Therefore, the diagnosis of these dynamic cables represents nowadays a key issue for the development of floating offshore wind farms. Since 2011, floating technology offers many authentic advantages; In fact wind turbines can be installed in areas of high winds and in deep seas far from the coastline, which represent a promising technology for developing the renewable marine energies. In this paper, we investigate the online diagnosis of dynamic power cables by the model-based approach. The guiding principle is to monitor the R-L-C parameters of a cable transmission line modeling order to diagnose problems such as cable overheating, water-treeing or water ingress. Then, the main challenge is to find the “best” parametric model which must present the best tradeoff between structure complexity for diagnosis ability and simplicity for its identifiability in operating conditions. For this, we use the parametric sensibility analysis to evaluate the diagnosis potential of some diagnostic-dedicated models. First results are promising.

The development of green energy production processes is highly praised due to its advantages in environmental protection and economic growth. Within this framework, this paper analyzes the feasibility of electrical energy production in a grid-connected photovoltaic power system using an advanced sliding mode control (SMC). Our study focused on the implementation of a robust sliding mode control from a nonlinear system to control a photovoltaic system connected to the power grid. In fact, the first goal is achieved by applying an MPPT strategy based on polynomial interpolation technique to maximize the PV power injected to the grid. While the second goal is achieved through nonlinear controls applied for the power inverter using sliding mode control (SMC) and space vector modulation technique (SVM). Simulation results obtained under MATLAB-Simulink environment are validated experimentally with a PV system where the implementation of the control laws was carried out with a dSPACE1104 acquisition and control board. Simulation and practical results confirm the performance of this control strategy under different static and dynamic power flow regimes.

The development of green hydrogen production processes is highly praised due to its advantages in environment protection and economy growth. Within this framework, this paper discusses the feasibility of hydrogen production in grid connected photovoltaic power station. The system is based on the conversion of solar energy into electrical power and hydrogen gas. The produced electrical energy is converted into hydrogen through electrolysis process. Therefore, the produced hydrogen will be used for refueling fuel cell vehicles or any other applications. The paper discusses the economic efficiency and the optimization of the PV grid connected system for the production of hydrogen. The total capacity of the grid connected PV system is 1500 kWp. The system produces 36465 kg of hydrogen per year with an average of 400 kg/day. The Levelized cost of hydrogen production is 4.2 €/kg. The estimated cost of the project depends on the cost of civil works, PV systems, electrolysers, and hydrogen tanks.

This paper deals with the sliding mode control of photovoltaic pumping system using an indirect field oriented control of the induction motor. The pumping system is composed by a photovoltaic generator, an output DC capacitor, an inverter which supplies an induction motor which drives the shaft of a centrifugal pump. After the modeling of the different components of the pumping system the sliding mode control is choosing to be apply in this work thinks to advantages, which present compared to conventional PI controller. Then an (MPPT) algorithm of the maximum power point tracking is used to determine the speed reference of induction motor from the value of illumination. Finally, simulation and experimental results are presented to show the effectiveness of the proposed control strategies.