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Open-circuit and short-circuit faults in switches affect the availability of inverters for high-reliability applications such as military, aerospace, and industrial systems, where a continuous supply of power is crucial. In this article, a five-level inverter structure is proposed that can handle both open-circuit and short-circuit faults for single- and multiswitches. In both healthy and faulty operations, the proposed inverter maintains the rated output power and efficiency. In addition to being a reliable and appropriate candidate for emergency loads, the proposed fault-tolerant inverter topology (FTIT) has several promising features, such as a low number of employed devices, a higher efficiency, and a lower total standing voltage. To demonstrate the superior performance of the proposed topology as compared to state-of-the-art structures, comprehensive comparisons have been made in terms of quantitative comparisons, efficiency, and cost. Moreover, this article performs a detailed reliability analysis to evaluate the proposed FTIT and compares its performance with that of other FTITs. Furthermore, a fault detection method based on an extreme learning machine is proposed for detecting the healthy and faulty operation of the proposed FTIT. Simulation and experimental results are presented for different faulty cases to verify the feasibility of the proposed fault-tolerant inverter topology.

The redundant switching states of flying capacitor-based (FC-based) multilevel converters are used to balance the voltages of the FCs. Attempts to balance capacitor voltages have ignored the switching transitions between converter switching states. In this article, we propose a generalized voltage balancing scheme with an optimized switching frequency scheme for FC-based multilevel converters, including the classic flying capacitor multicell (FCM) converter, which needs less computation. All the switching transitions between the switching states of adjacent voltage levels are considered by the overall priority index of switching frequency. In addition, an overall priority index is utilized to balance the voltages of FCs. Using these two indexes, three criteria are developed to select the proper switching state of the converter. Using these criteria, the proposed decoupled space vector modulation scheme is implemented intuitively and simply for FC-based multilevel converters. The proposed scheme is evaluated by simulation results of a five-level FCM converter. Moreover, experimental results demonstrate the robustness of the proposed method in the static load and transient conditions.

This article presents a new modulation method based on nearest level modulation (NLM) and phase voltage level reconstruction for the four-level single flying capacitor (4L-SFC) converter. The reconstruction procedure addresses the voltage balancing issues of the 4L-SFC converter and performs the per-phase modification of the phase voltages. In the proposed reconstructed NLM (R-NLM) method, the modulation procedure is carried out in the abc reference frame to eliminate the complexities associated with the space vector modulation (SVM). It is also compatible with the per-phase implementation of the reconstruction, making the whole process more straightforward. The required computations in the NLM-based reconstruction are also reduced when compared to the SVM-based reconstruction technique. The current control task is carried out using deadbeat predictive control (DBPC) by defining the system model in the abc coordinate. Also, a new approach for estimating the common-mode voltage (CMV) value, required in the abc frame-based system model, is presented. Simulation results demonstrate that the proposed R-NLM simplifies the modulator while retaining the performance of the SVM-based modulation technique for the 4L-SFC converter. The R-NLM alongside DBPC in the abc coordinate is implemented on a laboratory scale setup of the 4L-SFC converter to validate the feasibility of the proposed modulation scheme.

The pump-as-turbine (PaT) system is a cost-effective alternative to harness hydropower from microscale water resources although its best efficiency point (BEP) is difficult to be estimated without experimental results and its efficiency dramatically drops at partial load. The variable-speed operation of PaT-generator system is proposed in this article to run it at BEP despite changing hydrological conditions. The studies are carried out based on an experimental setup comprising a centrifugal pump, running in turbine mode, coupled with a 3-kW induction generator. The speed control method is based on the rotor field-oriented control and is implemented on an experimental ac/dc converter. Various performance characteristics of the system, including constant-head and constant-speed curves, are extracted and investigated. Then, a modified perturb and observe algorithm is proposed to accurately track the maximum power point of the system. The obtained results clearly demonstrated that the raised issues are resolved well by using the proposed solution.

This article proposes a modulation scheme based on the concept of virtual voltage levels for regulating the dc-link capacitor voltages of a four-level diode clamped converter under restricted operating conditions. The proposed virtual-level space vector modulation (SVM) scheme sets the average neutral point currents to zero, which results in no net change in dc-link capacitor voltages and thereby voltage balancing. In addition, a closed-loop algorithm is developed to compensate for any voltage drift due to unideal practical conditions. Consequently, the modulation of the reference voltages results in the desired output voltages while regulating the dc-link capacitor voltages at various operating points. In the proposed modulation scheme, switching frequencies are not significantly increased, and they are lower than those in the classic virtual-vector SVM method. The simulation results demonstrate the effectiveness of the proposed modulation scheme and highlight its main benefits and features. The simulation results are verified through a laboratory-type experimental setup.

The reliabilities of the renewable energy source systems are affected by their inverter structures. So, an inverter topology with higher reliability reduces the maintenance cost of the system. In this article, a multilevel inverter structure is proposed with improved reliability and reduced component count. The proposed structure produces 7 and 11 voltage levels in symmetrical and asymmetrical configurations, respectively. This inverter topology utilizes six unidirectional switches and one bidirectional switch. The proposed inverter structure can be extended to generate any number of voltage levels with the inherent property of producing both positive and negative voltage levels. Various comparisons including the total number of switches, the total number of switch drivers, and the total blocking voltage are done to show the effectiveness of the proposed structure in the reduction of the component counts. In addition, the reliability of the proposed structure is analyzed and comparisons with other counterpart structures are studied. The comparison results show the reliability improvement of the proposed inverter structure. Finally, the simulation results, extracted by MATLAB/Simulink, and the experimental results, obtained from a laboratory prototype, are provided to prove the feasibility of the proposed multilevel inverter (PMI) structure.

This article presents a new digital control system for dual active bridge dc/dc converters. The proposed control system includes a novel compensator with asymmetric half-cycle modulation. The proposed compensator is based on a novel geometric-sequence-control algorithm, which is a model-based predictive current control. The proposed control system provides fast and seamless tracking of the reference current and ensures zero dc current in the transformer windings (prevents transformer saturation). Moreover, it offers high robustness against perturbations and uncertainties in the converter. It also allows symmetric growth of transformer current during transients, thereby eliminating potential temporary saturation issues. Analysis, simulation, and experimental results are provided to demonstrate the superior performance of the proposed control in achieving high precision output regulation, fast and seamless transient response, and high robustness.

Low-pass filters have been used widely in the supervisory energy management controllers (EMC) for electric vehicle applications. However, there has not been a comprehensive methodology for the selection of their key design characteristics, such as the passband, stopband, and attenuation capabilities. In this article, a novel, step-by-step procedure, for the design of the digital low-pass filters (DLPF) is presented for the EMC. Mathematical models for a generalized battery/supercapacitor (SC) structure are derived for the impedance functions of the system. These impedance functions are used to investigate the behavior of the sources and the converter in the frequency domain. Moreover, using the extracted information from the frequency response curves, the guidelines for design of the DLPF are presented. In addition to the DLPF, a fuzzy logic controller is developed to monitor the state-of-charge (SoC) of the SC bank to ensure its operation in a safe region. The controller is designed and tested for the Urban Dynamometer Driving Schedule, using MATLAB/Simulink. Finally, the theory and simulations are validated using a Typhoon hardware-in-loop real-time emulator.

Due to the ever growing global energy demand and pollution levels, clean and renewable alternative energy resources, such as wind, have become indispensable for preserving the planet for future generations. With wind being an unpredictable resource, it is imperative that wind systems extract as much power from the wind as possible while it is available. The conventional maximum power point tracking (MPPT) algorithms that use predetermined mathematical relationships to represent a specific wind system's power/torque characteristics suffer the drawback of deteriorated efficiency over time whereas the perturb and observe algorithms are susceptible to logical errors when subjected to frequent atmospheric variations. In order to solve the aforementioned drawbacks as well as to reduce the cost of the sensing network required to achieve MPPT, this paper proposes a novel sensorless slope-assisted MPPT algorithm that is able to avoid logical errors attributed to wind fluctuations by detecting and identifying atmospheric changes. Atmospheric changes are detected by a state observer by monitoring the generator output power, the ac/dc rectifier output voltage, and the rate of change of the power-voltage ratio without the need for anemometers and any generator speed sensors. The detailed description of the proposed MPPT control logic will be provided in this paper. The functionality of the proposed control method is verified through the simulation results on a 3-kW system, as well as the experimental results on a proof-of-concept 200-W prototype.

This paper presents an adaptive and intelligent power control approach for microgrid systems in the grid-connected operation mode. The proposed critic-based adaptive control system contains a neuro-fuzzy controller and a fuzzy critic agent. The fuzzy critic agent employs a reinforcement learning algorithm based on neuro-dynamic programming. The system feedback is made available to the critic agent's input as the controller's action in the previous state. The evaluation or reinforcement signal produced by the critic agent together with the back-propagation of error is then used for online tuning of the output layer weights of the neuro-fuzzy controller. The proposed controller shows superior results compared with the traditional PI control. The transient response time is significantly reduced, power oscillations are eliminated, and fast convergence is achieved. The simple design and improved dynamic behavior of the proposed controller make it a promising nominee for power control of microgrid systems.

The optimal, resilient and flexible operation of the power system is one of the most important challenges of the power grid. Fast resources as a backup capacity to provide power are one of the ways the power system to be more flexible and resilient. In this paper, a new joint power and reserve scheduling is done considering scheduling based on power instead of scheduling based on energy, the correct management of the thermal units’ ramp, the use of responsive loads includes a collection of commercial customers and plug-in electric vehicles (PEVs) in the secondary (15-minute) and tertiary (30-minute) reserves and discharge management of PEVs. A part of the power demand of these responsive loads is provided as free by renewable resources in times when there are no bad weather conditions. The use of responsive loads, correct management of the ramp of thermal units and a part of the discharge of PEVs can help restore the network quickly. The mixed-integer linear programming (MILP) method has been used to solve the joint power and reserve scheduling problem. The results show that the proposed model can lead to more flexibility and resiliency of the system and reduce the cost of the system.

•A new available efficiency Index (AEI) has been presented.•The hidden revenue from non-production of carbon emission due to the use of renewable energies is considered.•The availability and reliability of a smart grid in the presence of energy storage system are analyzed in different scenarios.•The results show the proposed method can improve the availability, reliability, and total profit of the system.