Superconducting magnetic energy storage (SMES) systems are characterized by their high-power density; they are integrated into high-energy density storage systems, such as batteries, to produce hybrid energy storage systems (HESSs), resulting in the increased performance of renewable energy sources (RESs). Incorporating RESs and HESS into a DC bus to obtain a DC microgrid concept is considered a more attractive option for solving system reliability and stability issues. In this paper, we focus on employing SMES systems based on their characteristics of a fast response and high efficiency, which contribute to increased battery lifespan, and reducing the mismatch between the energy supplied by the renewable energy source and the load demand by compensating for the effects of partial shading on the PV system on the DC bus side and the imbalance in loads on the other side of the AC bus. The incremental conductance algorithm (INC) is used for maximum power point tracking (MPPT) in the PV system. Fuzzy logic control (FLC) is proposed for the generation of control signals for the DC–DC chopper used to charge/discharge the SMES coil. Simulations using MATLAB/Simulink were then carried out to assess the proposed models of the (standalone and grid) connection systems.

The capacitance selection of the three-phase self-excited induction generators (SEIG) driven by wind energy is influences by the iron losses. This paper is dealing with this problem by constructing a steady state model of the generator supplying an induction oil pump. No previous literature studying the requirements of selecting the minimum excitation capacitance under the iron loss impact is found. This work is focusing on: (i) a novel evaluation of the characteristics of the induction generator taking iron loss into account. (ii) the errors caused by neglecting the iron loss. (iii) the importance of including the iron-loss in any accurate analysis. (iv) the errors occurred in the selection of the precise excitation capacitance (Cexct) when the iron-loss neglected. Nodal analysis is suggested to describe the study-state performance of the proposed model. A Matlab/simulation is established to validate the proposed model.

Limitations of conventional wires such as copper wires are causing dispersion and distortion of the message signal for long distances communication especially for the wide bandwidths. The ability of fiber optic to overcome this problem is making it a dominant transmission medium. Despite of this major positive attribute of optic fibers, there is still a downside for using the fiber optic communication; that is the nonlinearity problem especially at the very high frequency bandwidth. For the first time, a desigen of an audio signal is suggested and executed in MatLab with an integration with OptiSystemTM software to discuss and solve this issu. The audio signal is then transmitted in different shapes of modulation signals (NRZ, RZ & RC) for different distances (100 km & 75 km) via a fiber optic media to be received in a receiving part of the simulated system. Three tests are used to do so. The first is the Quality-factor (Q-Factor) against the received power, second test is eye diagram performance and finally is the measuring of the amplitude of output (received) signal for each modulation signal shape using the Oscilloscope Visualizer. The NZR modulation signal was found to be the best one of the three used signals’ types in all three tests. The Q-factor for NRZ pulse shape (=12) was higher than that for RZ (=10) and RC (=8) for a 100 km distance at the same received power level.

Nowadays, a controller that improves the power factor (PF) is automatically designed and implemented to correct the value of the power factor once they falls below a certain one. In industry, day by day, there is an increase in the use of domestic applications and inductive loads such that they consider the essential reason whose responsible on lowering the power factor. Therefore a development method is needed to improve the power factor by adding manually variable capacitors or automatically. Fuzzy algorithm can be used as an intelligent system to estimate the value of the capacitor that should be added to compensate the effect of inductors. In this work, sixteen level of power factor are corrected automatically by new way through using Arduino Uno that programed with the aid of Fuzzy logic idea. A bank of four capacitors with different values is used and the Fuzzy helps taking the decision of which capacitors be ON or OFF. Here, the correction of power factor is from 0.64 to 0.98, and each level gives an increment of 0.02125 in PF. The experimental results are very close to the theoretical one, and the cost is very acceptable since the circuit is built from cheap equipments such as Arduino, potential transformer, relays, zero crossing circuit and current transformer. In addition, the maximum error due to the difference between the capacitor theoretical calculation and the practical is about 4.1%, while the error between the desired and the result value of PF is about 4.08% for maximum.