The conventional electrical grid is undergoing substantial growth for reliable grid operation and for more efficient and sustainable energy use. The traditional grid is now metamorphosing into a smart grid (SG) that incorporates a diverse, heterogeneous blend of operating measures such as smart appliances, meters, and renewable energy resources. With better efficient results and dependability, the SG can be described as a modern electric power grid architecture. The SG is one of the greatest potential advances as a promising solution for the energy crisis. However, it is complex and its decentralization could be of tremendous benefit. Moreover, digitalization and integration of a large number of growing connections make it a target of cyber-attacks. In this sense, blockchain is a promising SG paradigm solution that offers several excellent features. There has been considerable effort put into using blockchains in the smart grid for its decentralization and enhanced cybersecurity; however, it has not been thoroughly studied in both application and architectural perspectives. An in-depth study was conducted on blockchain-enabled SG applications. Blockchain architectures for various applications, such as the synchrophasor applications, electric vehicles, energy management systems, etc., were proposed. The purpose of this article is to provide directions for future research efforts aimed at secure and decentralized SG applications using blockchain.

The design of permanent magnet motors for the battery-powered electric vehicle has different aspects. In this study, the conceptual design process of an electric machine for Sedan Low car is presented. Based on the vehicle requirements an interior permanent magnet motor with a maximum power of 120 kW with different slot/pole combinations is designed. To obtain the best slot/pole combination, The New European Driving Cycle in term of crucial performance characteristics is compared. Given the importance of irreversible demagnetization phenomenon to an electric vehicle application, an accurate approach to determine the irreversible demagnetization rate is first introduced. Design tips are then proposed to reduce the probability of the irreversible demagnetization. Finally, fault-tolerant design in case of irreversible demagnetization withstand capability is carried out using a two-level Taguchi optimization approach. The results obtained from this study indicated that the proposed approach is effective in the fault-tolerant design of the permanent magnet machine for the electric vehicle applications.

Rapid developments in hydrogen fuel cell (FC) energy and DC microgrid systems have extended the applications of multiphase parallel interleaved step-up converters for stabilizing DC bus voltages. DC microgrid applications include vehicle systems, shipboard power systems, and more electric aircraft, which generate power at low voltage levels. The cascade architecture of a power converter in a DC microgrid may cause large oscillations and imbalance given that converters considered as loads have constant power load characteristics. In this work, output DC bus voltage stabilization and current sharing of a multiphase parallel-interleaved-FC boost converter is presented. The proposed robust controller with added integrator action is based on the Hamiltonian-Lyapunov function. The efficacy and robustness of the designed controller were successfully authenticated by experimental results obtained using a 2.5 kW prototype FC converter (via four-phase parallel-interleaved boost converters) and the dSPACE MicroLabBox platform. The main source of the FC is based on a fuel reformer engine that converts fuel methanol and water into H ₂ gas in a polymer-electrolyte-membrane-FC stack (50 V, 2.5 kW).

With growing environmental concerns and the limitations of fuel cell resources, replacing petrol-based engines with electric machines as the traction motor for electric vehicles (EVs) is gaining attention. Among the different electric machines topology, for lower power applications such as three-wheel motorcycle, the Brushless Direct Current (BLDC) motors are the most favorable due to their simple structure, simple control algorithm, etc. One of the key aspects of developing BLDC motors in EV applications is utilizing the fast and efficient optimization algorithm over driving cycles. Another aspect is considering manufacturing tolerances to eliminate the failure product rate in mass production. The combination of optimization algorithms with consideration of manufacturing tolerances leads to a complex and time-consuming optimization procedure. To overcome this problem, the robust design by utilizing the Design of Experiment (DOE) method can be utilized. In this study, first, a developed systematic multi-physics multi-level optimization algorithm with consideration of manufacturing tolerances and driving cycles is proposed. Then, to evaluate the accuracy of the optimization process, a prototype of the optimized motor is manufactured. The efficiency and accuracy of the optimization algorithm are compared through Finite Element Method (FEM) and experimental results, showing the effectiveness of the proposed algorithm.

This work proposes a new indirect filed-oriented control (IFOC) scheme for double-powered induction generators (DPIGs) in multi-rotor wind turbine systems (MRWT_S). The IFOC strategy is characterized by its simplicity, ease of use, and fast dynamic speed. However, there are drawbacks to this method. Among its disadvantages is the presence of ripples in the level of torque, active power, and current. In addition, the total harmonic distortion (THD) value of the electric current is higher compared to the direct torque control method. In order to overcome these shortcomings and in terms of improving the effectiveness and performance of this method, a new algorithm is proposed for the super twisting algorithm (STA). In this work, a new STA method called simplified STA (SSTA) algorithm is proposed and applied to the traditional IFOC strategy in order to reduce the ripples of torque, current, and active power. On the other hand, the inverter of the DPIG is controlled by using a five-level fuzzy simplified space vector modulation (FSSVM) technique to obtain a signal at the inverter output of a fixed frequency. The results obtained from this proposed IFOC-SSTA method with FSSVM strategy are compared with the classical IFOC method which uses the classical controller based on a proportional-integral (PI) controller. The proposed method is achieved using the Matlab/Simulink software, where a generator with a large capacity of 1.5 megawatts is used. The generator is placed in a multi-rotor electric power generation system. On the other hand, the two methods are compared in terms of ripple ratio, dynamic response, durability, and total harmonic distortion (THD) value of the electric current. Through the results obtained from this work, the proposed method based on SSTA provided better results in terms of ripple ratio, response dynamic, and even THD value compared to the classical method, and this shows the robustness of the proposed method in improving the performance and efficiency of the generator in the multi-rotor wind system.

In recent years, the methods of controlling electrical machines have been witnessing increasing development to reduce torque and electric current fluctuations in electrical power generation systems from renewable sources such as wind energy. The generation of electric power from wind plants imposes the need for an efficient and more robust method in order to obtain fewer ripples in active and reactive power. In this work, a new fractional-order proportional-integral (FOPI) controller and intelligent PWM (IPWM) technique are proposed to control an existing asynchronous generator (AG) in variable-speed multi-rotor wind turbines (VSMRWTs). This proposed method depends on combining or using two methods, namely nonlinear area and fractional calculus, to obtain a more robust method and to reduce current and torque ripples. In the framework of this study, the electric power generation system consists of a 1.5 MW AG and VSMRWTs. The AG is controlled using a simpler and easily accomplished method called direct vector control, based on FOPI controllers and the IPWM technique (DVC-FOPI-IPWM). The maximum power point tracking (MPPT) method is used to generate the maximum energy from the VSMRWTs. The proposed DVC-FOPI-IPWM technique is modeled in the Matlab/Simulink platform to obtain good quality current and active power. Simulation results show that the proposed strategy reduces the ripples of torque, current, and active power compared to the classical technique. Moreover, the reduction ratio is about 85%, 99%, and 93.33% for the current, active power, and torque, respectively.