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The study presents the development of a novel hybrid ozone generator utilizing dielectric barrier discharge (DBD) technology for water treatment applications. This generator features a cylindrical design with multiple stainless steel balls as the internal high-voltage electrode, enhancing the electric field and increasing ozone concentration. Key results indicate that the hybrid configuration outperforms traditional volume and surface DBD systems in both ozone production and energy efficiency. Specifically, the hybrid reactor with smaller balls achieved ozone concentrations approximately 2 to 3 times higher than those produced by surface and volume DBD generators. Additionally, energy efficiency exceeded 500 g/kWh at low voltages for the hybrid system, significantly surpassing the efficiencies of the other configurations. The experimental results demonstrate that the hybrid reactor can decolorize contaminated water more effectively, achieving near-complete discoloration in just 20 min, compared to 30 min for conventional systems. This research highlights the potential of hybrid DBD systems in improving ozone generation efficiency for environmental applications, particularly in water treatment processes.

Electricity consumption is increasing gradually and this trend will continue in the future. In addition, rapid network control systems using the resources offered by power electronics and control microelectronics have been recently studied and developed, and are currently in normal application for some, for others, in pilot applications or as prototypes. This paper attempts to show that these systems are referred to by the general acronym flexible alternative current transmission systems (FACTS) similarly dethroned the traditional systems while offering better solutions and solving the energy quality problem such as the hybrid system (unified power flow controller (UPFC), or universal phase shifter regulator (UPSR)) which opens up new perspectives for more efficient operation of networks by continuous and rapid action on the various parameters of the network (voltage, phase shift, and impedance); thus, the power transits will be better controlled and the voltages better held, which will make it possible to increase the stability margins or tend towards the thermal limits of the lines. In this work, we used a classic control (PI-decoupled) and others while offering more flexibility of control thanks to the development of strategies identification/control based on generalized predictive control (GPC) with neural network to ensure robust control with advanced algorithms.

The study presents the development of a novel hybrid ozone generator utilizing dielectric barrier discharge (DBD) technology for water treatment applications. This generator features a cylindrical design with multiple stainless steel balls as the internal high-voltage electrode, enhancing the electric field and increasing ozone concentration. Key results indicate that the hybrid configuration outperforms traditional volume and surface DBD systems in both ozone production and energy efficiency. Specifically, the hybrid reactor with smaller balls achieved ozone concentrations approximately 2 to 3 times higher than those produced by surface and volume DBD generators. Additionally, energy efficiency exceeded 500 g/kWh at low voltages for the hybrid system, significantly surpassing the efficiencies of the other configurations. The experimental results demonstrate that the hybrid reactor can decolorize contaminated water more effectively, achieving near-complete discoloration in just 20 min, compared to 30 min for conventional systems. This research highlights the potential of hybrid DBD systems in improving ozone generation efficiency for environmental applications, particularly in water treatment processes.

Wind farm development costs remain poorly understood, particularly for manufacturing and transport and installation (T&I) phases. This paper addresses the knowledge gap in understanding how transport and installation (T&I) logistics and wind turbine unit power selection impact the Levelized Cost of Energy (LCOE) of onshore wind farms. Several scenarios for a 12 MW wind farm have been formalized, studied and analyzed based on the variation in the unit power of the wind turbines (from 0.8 to 3 MW) and the pre-assembly method during the transport and installation phase (T&I). For each pre-assembly method, the number of segments (NL) and the required surface area (At) for transporting the turbine are considered. Results indicate that the minimum LCOE is achieved with 1.5 MW wind turbines using pre-assembly method for (At = 3, Nl = 550). This result is supported by the application of the genetic algorithm which confirmed and validated the same choice reducing this cost. In conclusion, the study underscores the critical importance of optimizing pre-assembly methods and turbine powers to minimize T&I costs and thereby reduce the LCOE of onshore wind farms. Additionally, it highlights the efficacy of genetic algorithms in optimizing these parameters within the renewable energy sector.