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The traditional electric power grid is moving toward smart grid, and with the advent of smart grids, a lot of data is generated in high volumes, velocity and variety. This brings several challenges with real time processing to get meaningful information for enhancing the benefits of smart grid. Furthermore, the application of short-term load forecasting poses additional challenges of being highly uncertain and volatile due to different load profiles. This paper conducts a study on the demand side management and load forecasting in electric power grids with help of the historical data obtained from smart grid. Machine learning models are developed using deep learning to ensure significant improvement in forecast accuracy when compared to benchmark Auto-Regressive Integrated Moving Averages ARIMA analysis. The short-term load forecast data has been merged with weather data from Application Program Interface (API). The discussed system uses an autonomous feedback loop to consider the historical load values as features for training and testing. This paper also applies deep learning methods like pooling based recurrent neural networks which could solve the curse of dimensionality that usually exists with increasing layers in traditional neural network methods. The paper proposes an averaging regression ensembles model for short-term load forecast.

In this paper, a data-driven approach has been used to identify and categorize fault in the electrical power system. The proposed methodology involves efficient analysis of the data with feature vectors including the area or zone of the bus. The training is done on machine learning models to classify and identify the location of the fault. Three-phase, line to ground, line-to-line to ground, line-to-line, loss of line with no fault and loss of load at bus faults are simulated to generate labeled data with type of fault and location of fault. Two algorithms have been proposed to choose the measurements selection strategy, and results have been stated. The proposed methodology proves its validity for identification of the fault without necessary measurement of the voltage of each node. The proposed approach works with a minimum number of buses required to be as few as 5-7% of the measured buses. The accuracy, capabilities, and limitations of the proposed algorithm are verified on IEEE 68 bus model. The highest classification accuracy attained on one of the test cases is 91%.

A discrete-time average model-based predictive control (DTA-MPC) is proposed for a quasi-Z-source inverter (qZSI). As a single-stage inverter topology, the qZSI regulates the dc-link voltage and the ac output voltage through the shoot-through (ST) duty cycle and the modulation index. Several feedback strategies have been dedicated to produce these two control variables, among which the most popular are the proportional–integral (PI)-based control and the conventional model-predictive control (MPC). However, in the former, there are tradeoffs between fast response and stability; the latter is robust, but at the cost of high calculation burden and variable switching frequency. Moreover, they require an elaborated design or fine tuning of controller parameters. The proposed DTA-MPC predicts future behaviors of the ST duty cycle and modulation signals, based on the established discrete-time average model of the quasi-Z-source (qZS) inductor current, the qZS capacitor voltage, and load currents. The prediction actions are applied to the qZSI modulator in the next sampling instant, without the need of other controller parameters’ design. A constant switching frequency and significantly reduced computations are achieved with high performance. Transient responses and steady-state accuracy of the qZSI system under the proposed DTA-MPC are investigated and compared with the PI-based control and the conventional MPC. Simulation and experimental results verify the effectiveness of the proposed approach for the qZSI.

This paper proposes a linear feedback structure of sliding mode control for a three-phase rectifier fed by a non-ideal supply voltage. The aim of the proposed technique is to achieve power flow with unity power factor even under distorted and/or unbalanced grid voltage condition. The performance of the proposed sliding mode control strategy is investigated and compared with the traditional PI control technique. Simulation, and implementation studies are conducted to prove that the proposed scheme has better performances than traditional solutions under different operating conditions. The investigation is aimed to show proposed system robustness against grid disturbances.

A quasi-Z-source three-to-single-phase matrix converter is proposed with low-frequency ripple power compensation. The employed impedance network between the source grid and the matrix converter extends the voltage gain; meanwhile, it has filtering function. Therefore, voltage step-up devices and an additional input filter are avoided. In addition, for a conventional three-to-single-phase matrix converter, input current of the source grid contains high harmonic components because of double-line-frequency pulsating power produced in single-phase side. A model predictive control-based ripple power compensation system is proposed in this paper to eliminate the low-order harmonic components from the three-phase input currents and voltages. Thus, the impedance parameters could be small in size and value. Simulation and experimental results verify the analysis and control of the proposed topology.

In this paper, a model predictive control (MPC) strategy for a grid-tied cascaded full-bridge inverter with neutral-point-clamped legs has been developed. Two strings of photovoltaic (PV) cells are interfaced to the grid by the inverter, while the controller ensures the operation at maximum power conditions. It is thus essential for the developed control method to be capable of independently regulating the two dc sources while balancing the dc-link voltages of the capacitors. In addition to these requirements, the proposed controller addresses the critical issue of the common-mode voltage (CMV) effects. By using the redundant switching states of the inverter topology, MPC reduces the high-frequency CMV components and consequently, the flow of the leakage currents from the PV system to earth ground. The developed control strategy is tested by conducting various experiments in an inverter prototype connected to two PV strings. Additionally, the system performance at steady-state conditions, during abrupt reference changes, and with grid voltage variations is compared with the traditional control strategy.

The battery energy-stored quasi-Z-source (BES-qZS)-based photovoltaic (PV) power generation system combines advantages of the qZS inverter and the battery energy storage system. However, the second-harmonic ( ${\text{2}}\omega $ ) power ripple degrades the system's performance and affects the system's design. An accurate model to analyze the ${\text{2}}\omega $ ripple is very important. The existing models did not consider the battery, or assumed a symmetric qZS network with $L_{{1}}= L_{{2}}$ and $C_{{1}}= C_{{2}}$ , which limits the design freedom and causes oversized impedance parameters. This paper proposes a comprehensive model for the single-phase BES-qZS-PV inverter system, where the battery is considered and there is no restriction of $L_{{1}}= L_{{2}}$ and $C_{{1}}= C_{{2}}$ . Based on the built model, a BES-qZS impedance design method is proposed to mitigate the ${\text{2}}\omega $ ripple with asymmetric qZS network. Simulation and experimental results verify the proposed ${\text{2}}\omega $ ripple model and impedance design method.

A battery-energy-stored quasi-Z-source cascaded multilevel inverter (qZS-CMI)-based photovoltaic (PV) power generation system combines advantages of a qZS inverter, a CMI, and a battery energy storage system. However, unbalanced battery state of charge (SOC) between cascaded H-bridge inverter modules will degrade an entire system's performance and shorten battery lifespan. This paper proposes a control method to balance battery SOCs of all modules, no matter the intermittent states of each module's PV power. The method is on the basis of battery SOCs, SOC limits of each module, and the total power injected into the power grid. Simulation and experimental results verify the proposed control method that ensures identical SOCs for the battery-energy-stored qZS-CMI PV system.

In this paper, a predictive speed controller (PSC) based on finite control set model predictive control is developed for electric drives. The large difference between the mechanical and electrical time constants necessitates long prediction horizons for a direct PSC (DPSC) strategy to be implemented. Therefore, the computation burden for online solving of the optimization problem critically increases even for low-complexity topologies, whereas the DPSC implementation becomes impossible for high-complexity inverters. Additionally, due to the absence of a PI controller in DPSC methods, stability issues arise; therefore, special care is mandated for eliminating steady-state errors. By using proper weighting of the speed errors, along with the current errors, in the cost function of the proposed PSC, the use of many prediction steps becomes unessential. For considering the current dynamics, a linear controller is incorporated in the control law of developed PSC offering improved system behavior, whereas the consideration of the speed errors allows achieving fast response characteristics. The proposed strategy is experimentally evaluated through examining reference and disturbance step changes of a PMSM drive with the three-level neutral-point clamped inverter. Finally, the proposed controller operation is experimentally compared with a predictive torque and speed control, by considering several performance indices.

The Crossover Switches Cell (CSC) is a recent Single DC-Source Multilevel Inverter (SDCS-MLI) topology with boosting abilities. In grid-connected PV applications, the CSC should be controlled to inject a sinusoidal current to the grid with low THD% and unity power factor, while balancing the capacitor voltage around its reference. These two objectives can be met through the application of a finite control set model predictive control (FCS-MPC) method. Thus, this paper proposes a design of an optimized FCS-MPC for a 9-level grid-tied CSC inverter. The switching actions are optimized using the redundant switching states. The design is verified through simulations and real-time implementation. The presented results show that the THD% of the grid current is 1.73%, and the capacitor voltage is maintained around its reference with less than 0.5 V mean error. To test the reliability of the control design, different scenarios were applied, including variations in the control reference values as well as the AC grid voltage. The presented results prove the good performance of the designed controller in tracking the reference values and minimizing the steady-state errors.

The pulse-width amplitude modulation (PWAM) method was proposed for the single-phase quasi-Z-source inverter (qZSI)-based photovoltaic (PV) power system to reduce quasi-Z-source (qZS) impedance values while improving efficiency. The method modified sinusoidal pulse-width modulation (SPWM) of the qZSI by combining pulse-amplitude modulation (PAM) and a varied dc-link voltage envelope was produced. The SPWM worked at low dc-link voltage, lowering voltage stress and avoiding shoot-through switching. The PAM worked at the varied dc-link voltage, reducing the number of switching events. As a result, the power dissipation decreased compared to working at the constant dc-link voltage. This study further investigates the PWAM-based single-phase qZS PV inverter system. An improved topology with control strategy is proposed for its grid-connected and standalone operation. Design method of impedance parameters is detailed. The performance in boost and buck operation is discussed when the single-phase qZSI using SPWM and PWAM. Simulation and experimental results verify outstanding features of the PWAM for single-phase qZSI, and the proposed approach for dual-mode operation of the PWAM-based single-phase qZS PV power system.

This paper presents variable- and fixed-switching-frequency-based hysteresis current control (HCC) methods for single-phase grid-connected voltage-source inverters with LCL filter. The main feature of the proposed HCC methods is that the reference inverter current is generated through a proportional-resonant (PR) controller for achieving zero steady-state error in the grid current. The consequence of using the PR controller is eliminating the need for using derivative operations in generating the reference inverter current. Furthermore, the active damping method is employed to damp the LCL resonance. An equation is derived for variable-switching frequency. Fixed-switching frequency operation is achieved by modulating the hysteresis band. The performance of both HCC methods has been validated by simulation and experimentally. It is reported that the proposed HCC methods not only preserve the inherent features of the conventional HCC methods, but also damp the LCL resonance using an active damping method and guarantee zero steady-state error in the grid current.

This study presents a high-efficient maximum power point tracking (MPPT) of photovoltaic (PV) systems by means of model-predictive control (MPC) techniques that is applied to a high-gain DC-DC converter. The high variability and stochastic nature of solar energy requires that the MPPT control continuously adjust the power converter operating point in order to track the changing maximum power point; a concept well known in the literature. The main contribution of this study is a model-predictive-based controller with a fixed step that is combined with the traditional incremental conductance (INC) method. This technique improves the speed at which the controller can track rapid changes in solar insolation and results in an increase in the overall efficiency of the PV system. The controller speeds up convergence since MPC predicts error before the switching signal is applied to the high-gain multilevel DC-DC converter and thus is able to choose the next switch event to minimise error between the commanded and actual converter operation. Comparing the proposed technique to the conventional INC method shows substantial improvement in MPPT effectiveness and PV system performance. The performance of the proposed MPC-MPPT is analysed and validated experimentally.

This paper presents the concept of a capacitorless static synchronous compensator (STATCOM) that uses a matrix converter (MC) and model predictive control (MPC) to compensate lagging power factor (p.f.) loads using inductors instead of electrolytic capacitors (e-caps) for energy storage. Although ubiquitous in power electronic converters, e-caps have well-known failure modes and wear-out mechanisms. In practice, the bus capacitors in a voltage-sourced inverter reactive power compensator may require monitoring and replacement, which can increase the cost of ownership of a traditional reactive power compensation method. The proposed MPC-MC-STATCOM uses a $3\times3$ direct MC, which when properly controlled using finite-set MPC, creates a phase shift of 180° from the input to output current, and thus supplies reactive power to the utility grid using inductors instead of the e-caps. This paper presents the fundamental concept and model derivation. The theoretical analysis is accompanied by simulation and experimental results that verify the intended operation of the controls and circuity in steady state under ideal grid conditions and dynamically to demonstrate robustness of the MPC control under step changes in grid voltage distortion and load characteristics. The conclusion is that the capacitorless STATCOM can provide the reactive power needed to compensate lagging p.f. load.

The quasi-Z-source inverter (qZSI) has attracted much attention for motor drives and renewable energy applications due to its capability to boost or buck in a single converter stage. However, this capability is associated with different challenges related to the closed-loop control of currents, control the dc capacitor voltage, produce three-phase ac output current with high dynamic performance, and obtain continuous and low ripple input current. This paper presents a predictive control strategy for a three-phase qZSI that fulfills these requirements without adding any additional layers of control loops. The proposed controller implements a discrete-time model of the qZSI to predict the future behavior of the circuit variables for each switching state, along with a set of multiobjective control variables all in one cost function. The quasi-impedance network and the ac load are considered together when designing the controller in order to obtain stability of the impedance network with a step change in the output reference. A detailed comparative investigation between the proposed controller and the conventional proportional-integral (PI) controller is presented to prove the superiority of the proposed method over the conventional control method. Simulation and experimental results are presented.

This study presents a decoupled active and reactive power control technique, for a single-phase grid-tied inverter, using model predictive control (MPC). The proposed technique does not use conventional phase-locked loop, pulse-width modulation nor a synchronisation transform, which makes the control algorithm well suited for an all-digital implementation. The proposed controller minimises the number of switching state transitions required to control the grid-side current while simultaneously constraining the harmonics distortions and protecting the inverter from overcurrent condition. In this study, the switching frequency is reduced by using a look-up table to minimise the number of switching state transitions, which helps lowering down the switching losses. The proposed technique uses an adaptive weight factor which gives more priority to commanded power tracking during transient, and minimises the tracking error and switching frequency in steady state while constraining the harmonics distortion. This method improves the tracking performance as well as reduces the switching losses by minimising the switching frequency compared to the MPC with fixed weight factor and conventional decoupled power control. Thus, the outcome of proposed controller is a constraint multi-objective optimisation between the switching frequency reduction and grid-side current harmonics in terms of cost function with weighting factor.

Variability in the solar irradiance level and ambient temperature of photovoltaic (PV) systems necessitates the use of maximum power point tracking (MPPT) of PV systems to ensure continuous harvesting of maximum power. This paper presents a sensorless current (SC) MPPT algorithm using model predictive control (MPC). The main contribution of this paper is the use of model-based predictive control principle to eliminate the current sensor that is usually required for well-known MPPT techniques such as perturb and observe (P&O). By predicting the PV system states in horizon of time, the proposed method becomes an elegant, embedded controller that allows faster response and lower power ripple in steady state than the conventional P&O technique under rapidly changing atmospheric conditions. This becomes possible without requiring expensive sensing and communications equipment and networks for direct measurement of solar irradiation changes. The performance of the proposed SC-MPC-MPPT with reduced load sensitivity is evaluated on the basis of industrial European Efficiency Test, EN 50530, that assesses the performance of PV systems under dynamic environmental conditions. The proposed control technique is implemented experimentally using dSPACE DS1007 platform to verify the simulation results.

The industrial development in recent years has seen a major increase in the use of induction motors, whereby the cost has to be as low as possible and the lifetime as long as possible. To follow up this desire, investigations in this area have become very intense. For that reason, this paper presents a solution for driving an induction motor and simultaneous fault detection with no need for additional sensors. In order to achieve this target, an observer system is implemented and a torque estimation procedure is used for torque detection. An LC filter was installed at the inverter output to provide better THD of the current. The validation of the drive operation was achieved through simulation and experiments. To investigate possible faults, an artificial unbalance was introduced to the test bench, whereby the experiment was validated by a comparison of physical vibrations and estimated torque.

This paper is the continuation of Part I in which a quasi-Z-source modular cascaded converter (qZS-MCC), comprising front-end isolated qZS half-bridge dc–dc converter submodules (SMs), for dc integration of high-power photovoltaic (PV) systems is proposed. The qZS-MCC-based PV system features modular structure, high-voltage dc collection of PV power, simple control with a unified and constant duty cycle for the front-end isolation converter of all SMs, and low qZS impedance due to no double-line-frequency pulsating power. Here, control scheme of the qZS-MCC PV system integrated into the dc collection grid is investigated. Dynamic model of the system is established for controllers design and time-domain transient simulation. Experimental tests are carried out on the downscaled prototype as a proof-of-concept of the proposed control and modeling, demonstrating the validity of the proposed approaches.

A quasi-Z-source modular cascaded converter (qZS-MCC) is proposed for dc integration of high-power photovoltaic (PV) systems. The qZS-MCC comprises series-connected front-end isolated qZS half-bridge (HB) dc–dc converter submodules (SMs). With the front-end isolation, the qZS-MCC achieves high-voltage dc capability, while maintaining modularity and PV panel grounded. The post-stage qZS-HB handles the PV voltage and power flows, dc-link voltage balance, and output-series power integration. Whereas, the front-end isolation converters of all SMs perform a constant duty cycle, lowing the control complexity. There is no double-line-frequency power flowing through the dc-side PV panels, qZS inductors, and qZS capacitors in the qZS-MCC, so small qZS impedance is possible compared to the existing qZS cascaded multilevel inverter. The configuration, operating principle, power loss evaluation, and passive components design of the proposed system are investigated in this part of the paper. The system control, modeling, and corresponding verifications are stated in Part II of this paper.

This paper presents an adaptive observer (AO)-based model predictive control (MPC) for a multilevel flying capacitors inverter (FCI). The proposed system consists of a midpoint dc-link three-cell four-level FCI feeding an RL load. Using the actual load current, the proposed AO estimates accurately the capacitors' voltages, which are fed to the MPC algorithm by means of a hybrid model considering both discrete and continuous variables. For real-time constraints, sufficient conditions are given to guarantee the practical stability of the proposed AO-based MPC. Theoretical analysis and experimental results are given to show that the proposed method is stable for all system configurations and has good performances even during disturbances (load change, input change, and parameters variations). This work was made possible by NPRP-EP Grant # [X-033-2-007] from the Qatar National Research Fund (a member of the Qatar Foundation). The statements made herein are solely the responsibility of the authors. Scopus

Power grids with increasing number of distributed energy resources (DERs) equipped with fleet of smart devices are exposed to malicious attacks. These malicious actions can ultimately cause a large-scale blackout if these subversive activities are not prevented, detected, or promptly addressed. Power grids are being threatened by a category of cyber-physical attacks, which target both the physical and cyber layers of the system. This paper proposes an autonomous detection and corrective control framework consisting of two algorithms to identify anomalies and provide a corrective action on the distribution system using smart inverters. The proposed framework detects the inverter abnormal behaviors and identifies them as cyber-physical attack or internal failure of the inverter. A model predictive control (MPC) scheme is proposed to detect the inverter internal failure. In the case of inverter failure, the proposed MPC scheme adopts corrective actions to restore the inverter operation with a pre-defined power injection set-points. Additionally, this paper proposes a cyber-physical attack detection mechanism, based on measurements from a geographic community of smart devices. The proposed framework continuously assists the supervisory control and data acquisition (SCADA) system to differentiate anomalies on the distribution system and decide the appropriate control actions for the entire grid.

Voltage source inverters in islanded microgrids grant active and reactive power sharing. Droop control is widely used due to its simplicity and lack of need for communication. Loads in droop-based microgrids drive the system frequency and voltage up and down. In this paper, a modified droop control to restore the frequency and voltage for an islanded microgrid is presented. Two new terms are introduced to the droop control to eliminate the frequency and voltage mismatches caused by the loads. Also, power sharing between multiple inverters feeding various loads is studied. To ensure precise active and reactive power sharing between the inverters, tuned droop control is analyzed and implemented. MATLAB/Simulink is used to demonstrate the effectiveness of the proposed technique for a microgrid model.

Nowadays, the electricity grid from the customer side is getting more complex. Number of customers with photovoltaic (PV) generation, plug-in electric vehicles (PEVs), and stationary battery energy storage system (BESS), referred here as Nano-Grid or n-Grid are increasing. With proper economic incentives and control mechanisms, the n-Grid may be used to ensure grid reliability and resilience if engaged in energy exchange with other n-Grids or the main grid. Such energy exchange framework is called transactive energy. The complexity and variety of the component integration and operation make n-Grid involvement in the transactive energy framework challenging. In this paper, a hardware-in-the-loop (HIL) simulation framework is introduced to provide solutions for some of the issues of power system and power electronics co-simulation that represent the backbone for the transactive energy exchange. Since grid decision making process has conspicuously different time constant in comparison with power inverters' switching frequency, including both in a simulation framework is challenging. A simulation framework in which PV generation and BESS are integrated to the n-Grid with power inverters is elaborated in this paper. Finally, a hardware-in-the-loop testbed implementation is discussed.

Recently, there has been an increase in the interest surrounding the integration of solar photovoltaic (PV) systems in the low voltage (LV) distribution network. This is due to many benefits, such as low generation costs, high efficiency, scalability, etc. However, large PV penetration at the distribution network can cause voltage levels to rise beyond the acceptable limits of the grid codes. Large amount of losses can also occur due to the reverse power flow resulting from the high penetration level of distributed PV generation units integrated into the distribution network. In this paper, a novel methodology based on a gradual increase in the PV penetration level is presented to determine the maximum PV penetration level in the LV distribution networks. PV penetration is defined as the ratio of the peak PV active generation to the peak active demand of the load. The IEEE European LV test feeder has been used as a test case to validate the proposed methodology. Real PV and load data, from residential customers in Ausgrid's electricity network, New South Wales (NSW), Australia, has been used to generate seasonal and worst-case PV generation and load profiles. The PV penetration in the network is increased to find the levels at which the voltage violations occur. PV penetration level with the minimum losses throughout the year is considered as the maximum acceptable level. Various analyses of real data have been used to find the optimal maximum level of PV penetration at the distribution network level.

In this paper, a novel and simple controller for seven-level packed U-cell (PUC) grid-connected inverter is presented. The control method is derived based on sliding mode control theory. Making use of the measured grid voltage and computed reference grid current, the reference value of the inverter output voltage is determined. According to the calculated voltage value, the suitable control set is selected (offline) in order to satisfy the reaching conditions of two separate sliding lines. The sliding lines are defined based on the grid current and the auxiliary capacitor voltage errors. Simulation results are presented to show the effectiveness of the proposed simple controller in tracking the desired values.

The cables failures in power systems utilities have been given great attention for reliability, economic aspects and safety of power utility operation. Such failures are caused by electrical, mechanical, and environmental stresses. Power cables might experience some serious damages particularly during the partial discharge activities. Therefore, the early localization of the exact defective cable section has become of extreme importance. The contribution of this study is to analyze electrical parameters behavior and its effects caused by a spheroidal cavity within the high voltage Cross-Linked Polyethylene (XLPE) cables. Also it investigates the correlation between electrical parameters and the size and location of voids inside the dielectric insulator using Finite Elements Analysis (FEA) environment. The results is intended to show that the location of the void inside the XLPE insulated power cables has a higher impact on the electric field and current density distribution than the void size.

Gas insulated switchgears (GIS) have the best insulation performance ensuring least failure incidents and most reliable operation, which justify the higher installation costs. Nevertheless, this popular switchgear also needs partial discharge measurement for insulation diagnosis, as it does detailed modeling and analysis of the insulation is needed. This paper presents a novel computational model of the complex pre-breakdown discharge phenomena that occur due to insulation imperfection in GIS. The paper aims to provide quantifiable parameters modeling equivalent to industrial measured parameters during commissioning of GIS. The proposed model is based on Poisson’s equation along with hydrodynamics equations which are utilized to investigate the influence of defect dimensions, electrical pulse features on pre-breakdown incidents and on the alteration of the charge density, electric stress, and temperature distributions around the insulation imperfection.

Partial discharge diagnostic techniques play an important role in maintaining operation safety and reliability of medium and high voltage apparatus. The rapid development of Ultra-High frequency techniques for partial discharge detection in gas insulated switchgear devices is attributed to the high sensitivity and immunity to interferences. An important challenge facing the RF diagnostic techniques is the complexity of switchgears as a propagating environment for electromagnetic waves. This paper is devoted to present the propagation behavior of electromagnetic waves in such power devices by reporting on the output characteristics of RF waves due to two different discontinuities namely the T-structure and disconnecting switches. The two discontinuities are to be applied simultaneously to analyze their impact together. Finite element method built in COMSOL Multiphysics is used to implement the model.

Model predictive controlled (MPC) power electronics converters (PECs) features numerous benefits including fast transient response, multi-objective control in single-loop, and inclusion of constraints and nonlinearities in a simple manner. However, the control approach requires the accurate knowledge of the model parameters of the system. Potential model parameter mismatches with the actual values will result in performance deterioration of the MPC. Various agents like aging and harsh environmental conditions would yield changes in circuit impedance. This paper proposes an autonomous MPC for PECs subject to the variations and uncertainties in input filter impedance. The proposed controller adaptively tunes the model parameters used in the predictive equations, alleviating mismatch among the predictive model parameters and the actual system. The proposed auto-tuned modeling scheme requires no additional sensors while maintaining the simplicity of the controller. The proposed method is applicable to all types of PECs and filter topologies. The theoretical analysis and results demonstrate that the proposed approach embedded in the MPC makes the control algorithm robust to variations of model parameters of the system.

This paper proposes a Hybrid DC link voltage balancing of a 2-leg 5-level Neutral Point Clamped (NPC) inverter. The scheme uses a combination of active (hardware) based and software (modulation) based techniques to achieve a balancing solution with enhanced power quality performance. The active balancing scheme is implemented using a Fly-back auxiliary circuit that is coupled to the non-adjacent DC bus capacitors. The balancing circuit uses less power electronics components compared to alternative active balancing approaches. The complementary soft balancing is composed of three types of modulations to produce output waveform with improved total harmonic distortion performance. The applicability and proof of merits have been demonstrated by simulation of a Ladder transistor clamped NPC inverter under passive load.

This paper proposes a hierarchical optimal active and reactive power control while minimizing the switching events for three-phase grid-tied cascaded multilevel inverters (CMI) for battery energy storage applications. Model predictive control (MPC) is known as a potential approach for multi-objective control schemes in single-loop manner for power electronics interfaces. However, MPC schemes are suffering from high computational burden. Furthermore, one of the main challenges while designing MPC is tuning of the cost function weight factors in multi-objective control schemes. The weight factors design and tuning directly affect the performance and robustness of the MPC. The proposed high performance hierarchical multi-objective optimal controller doesn’t have the aforementioned limitations of the MPC. The proposed control scheme utilizes a dynamic look-up matrix as an internal optimizer tool. The redundant switching states are cycled to equalize the power drawn from the independent battery energy storage sources while achieving a minimum energy control. The theoretical analysis and case studies verify robustness, fast dynamic response, and computational efficiency of the proposed multi-criteria optimal controller.

This work presents a modified model predictive control (MPC) with open-circuit fault-detection and fault-tolerance capabilities for grid-connected multilevel inverters. The proposed self-healing model predictive control (SMPC) approximates the error in the inverter output voltage, and executes a diagnostic algorithm if this error exceeds a pre-defined tolerance. This diagnostic algorithm determines the switch with an open-circuit failure in a duration less than one fundamental period. After an open-circuit failure is detected, the controller will reduce the set of permissible control actions, allowing the inverter to retain healthy operation. Unlike the existing methods, the proposed SMPC combines fault-detection techniques with the direct application for corrective actions for fast fault clearness. The theoretical analysis and case studies verify the functionality of the proposed self-healing MPC scheme for a grid-tied seven-level cascaded multilevel inverter (CMI).

A novel configurations of a non-isolated Modified SEPIC Converter with two Voltage Lift Switched Inductor (MSCVLSI) modules namely MSCVLSI-XYL, MSCVLSI-LYZ and MSCVLSI-XLZ are presented in the paper. The key features of these configurations are, 1) high voltage conversion ratio, 2) single controlled switch, 3) high-value input inductor to smooth the input current, 4) maximum utilization of input source, 5) continuous input current. With these notable features, proposed configurations are more convenient for high voltage renewable energy applications to boost the low voltage of photovoltaic array/fuel cell. The feasibility of these converter configurations are verified by mathematical analysis and simulation results. MSCVLSI configurations are simulated for 250 W resistive load and at 50 kHz switching frequency. - 2019 IEEE. ACKNOWLEDGMENT This publication was made possible by NPRP grant # [X-033-2-007] from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. Scopus

In this paper, a DC microgrid based on solar PV array and battery storage is simulated and a dual-mode control system is developed for grid-connected and islanded modes. The developed dual-mode control approach is based on model predictive control (MPC). The control system is flexible to allow operating the microgrid under different modes that include islanded and grid-connected modes. The considered microgrid is modeled and simulated using MATLAB/Simulink software and different scenarios have been tested to verify the proposed principle.

In this paper, an effective finite-control-set model predictive controller (FCS-MPC) is proposed for an active dual output rectifier. The topology under study is a 5-level packed U cells (PUC5) rectifier. The optimized cost function is designed based on the capacitors’ voltages and current errors. The Capacitors’ reference voltages and the peak value of the reference grid current are used to normalize the errors within the cost function. The peak value of the current reference is generated by a PI controller using the capacitors’ voltage errors. The presented results show a proper tracking of the rectifier’s dual output voltages while ensuring a unity power factor.

This paper, a model predictive control (MPC) based primary control strategy is proposed for parallel three-phase four-leg inverters in islanded AC microgrids. To regulate the frequency and voltage in the AC microgrid, a cascaded control structure is used. The used structure consists of a droop control loop, a virtual impedance control loop, and the MPC based voltage control loop. Compared to traditional proportional-integral (PI) based cascaded control, the proposed technique offers faster dynamic response and better steady state operation. The performance of the proposed control system is validated by hardware-in-the-loop (HIL) simulation studies.

This paper proposes a novel smart energy management system (EMS) for distributed generations (DGs) in AC microgrid. The considered microgrid consists of two DGs, energy storage system, and loads. The solar PV system and the wind energy conversion system (WECS) are selected as an input power source of DGs. Model predictive control technique is used to regulate each DG’s output current whereas adaptive neuro-fuzzy inference system (ANFIS) based EMS is developed to manage the available energy in AC microgrid. The proposed method is validated analytically and through Hardware-in-the-Loop (HIL) experiments. The carried out HIL experiments prove the merit of the proposed method.

The transient energy margin of large-scale power-electronic-interfaced microgrid is very limited. Typically, this margin is stored in the rotor of synchronous generators which acts as a low pass filter for power system disturbances. In microgrid, the transient frequency ride through (TFRT) capability becomes very limited or marginal. Thus, the system stability is induced under small disturbance conditions, which results in large frequency deviation upon any load change or source on/off switching. This paper proposes a novel method to suppress the frequency variation by controlling the energy stored in multiple dc link capacitors based on the instantaneous energy mismatch between the supply and the demand. The Energy Shaping Process (ESP) proposed here aims to control the magnitude and the insertion time of the released energy from multiple coordinated dc links such that the frequency nadir and the rate of change of frequency (RoCoF) are both minimized. The ESP considers the sign of the energy mismatch, the sign of the frequency variation, and the sign of frequency variation’s derivative. ESP provides flexible virtual inertia. The results show that ESP is very efficient in suppressing the energy mismatch, as well as, the frequency variation during transient events, which leads to stable and reliable microgrid operation.

Recently, the differential buck topology was introduced to compensate the 2nd order power pulsation of singlephase systems. Specifically, the Common-Mode (CM) operation of the differential buck is utilized for active power ripple mitigation, while the Differential-Mode (DM) operation is used as an active power transporting port. Thus, compared to the available active power ripple mitigation methods in the literature; the differential buck topology does not require supplementary gate drives, power semiconductors, and energy storage elements. Besides, the differential buck converter is suitable for non-isolated systems due to its inherent leakage current suppression characteristic. Therefore, this paper proposes an improved active power decoupling scheme for active rectifiers based on the differential buck topology that are tied to distorted power grids. In addition, it will be shown that for a grid that is distorted to nth harmonic with a DC component, the DCbus ripple’s harmonic components are from 1st to 2nth harmonic. The theoretical analyses are validated with a 1 kW rectifier system connected to 120Vrms/50Hz power grid that is distorted by 2nd, 3rd, 4th and 5th order harmonics with a DC component. The results are aimed to show a ripple free DC-bus voltage with just 30 μF capacitor even when the current supplied from the grid is highly distorted.

This paper proposes an effective computing framework for Short-Term Load Forecasting (STLF). The proposed technique copes with the stochastic variations of the load demand using a stacked generalization approach. This approach combines three models, namely, Light Gradient Boosting Machine (LGBM), eXtreme Gradient Boosting machine (XGB), and Multi-Layer Perceptron (MLP). The inner mechanism of Stacked XGB-LGBM-MLP model consists of generating a meta-data from XGB and LGBM models to compute the final predictions using MLP network. The performance of the proposed Stacked XGB-LGBM-MLP model is validated using two datasets from different locations: Malaysia and New England. The main contributions of this paper are: 1) A novel stacking ensemble-based algorithm is proposed; 2) An effective STLF technique is introduced; 3) A critical multi-study analysis for hyperparameter optimization with five techniques is comprehensively performed; 4) A performance comparative study using two datasets and reference models is conducted. Several case studies have been carried out to prove the performance superiority of the proposed model compared to both existing benchmark techniques and hybrid models.

Through coupling the impedance network between the grid and the conventional indirect matrix converter (IMC), the LC -filter-integrated quasi-Z-source (qZS) IMC overcomes the 0.866 voltage gain limitation of the conventional IMC and also avoids the input filter that is required to mitigate current harmonics of the conventional qZS matrix converters. This paper further investigates the voltage boosting and LC filtering function of the LC -filter-integrated qZS IMC. The voltage gain, the filtering function, and qZS network parameters design are presented using a small-signal model and circuit analysis. Simulation and experimental results validate the built model, the voltage gain analysis, and the parameters design of this type of qZS IMC. The input current of the LC -filter-integrated qZS network is compared to the conventional Z-source and qZS IMCs to investigate the integrated LC filtering capability. The experimental results verify that the LC -filter-integrated qZS network provides the necessary filtering function. Thus, the traditional input filter can be eliminated, which reduces the cost, power loss, volume, and weight for the overall system, when compared with the other conventional topologies that require the input filter, even those with impedance-source networks.

Since societies depend on energy and its management, extensive changes in energy-related technologies, such as the Smart Grid (SG), are likely to bring out subsequently enormous forms of social change. Imagine, there are several claims about the risks that lie ahead as conventional energy resources terminated, as populations increase, and as assumption accelerate. Therefore, the future societies will be subject to creative development and wide-ranging transformation to optimize their energy consumption. The SG can integrate an assorted set of electricity resources, containing large power plants as well as distributed renewable energy resources, electric energy storage, demand response, and electric vehicles. In line with many visions for the SG, consumers will play a more ‘active’ role in the future energy systems. Therefore, it is necessary to ensure customers’ acceptance to successfully build a SG. The eventual deployment of the SG depends on the consumers’ acceptance of SG products and services. Yet fully engaging the residential space in the SG remains a challenge. This work aims to provide energy systems researchers and decision makers with proper insight into the underlying drivers of consumer acceptance of the SG and the logical steps for their engagement to promote the SG technology and making it feasible in a timely manner.

This paper presents a finite-control-set model predictive control (FCS-MPC) for grid-tied packed U cells (PUC) multilevel inverter (MLI). The system under study consists of a single-phase 3-cells PUC inverter connected to the grid through filtering inductor. The proposed competitive topology allows the generation of 7-level output voltage with reduction of passive and active components compared to the conventional MLIs. The aim of the proposed FCS-MPC technique is to achieve, under various operating conditions, grid-tied current injection with unity power factor and low total harmonic distortion while balancing the capacitor voltage. Parameters' sensitivity analysis was also conducted. The study is conducted on a low-power case study single-phase 3-cells PUC inverter and with possible extension to higher number of cells. Theoretical analysis, simulation, and experimental results are presented and compared. This work was made possible by NPRP-EP grant # [X-033-2-007] from the Qatar National Research Fund (a member of Qatar Foundation). Scopus

Conventional matrix converters (MCs) have limited voltage gain that is less than 0.866, whether for direct MC (DMC) or indirect MC (IMC). The Z-source MCs (ZSMCs) overcome the voltage gain limitation of the traditional MC and achieve buck and boost operation with reduced switches count, thereby achieving low cost, high efficiency, and reliability, compared to the back-to-back converter. Furthermore, it will leads to more MC industrial applications. This paper presents an up-to-date comprehensive overview of the different ZSMC topologies and their configurations, circuit analyses, modulation schemes, and applications. This study offers a comprehensive and systematic reference for the future development of the ZSMCs.

This paper considers a social maximize welfare problem in a micro grid. Firstly, to enhance capacity ability and the output stability of generators in a micro grid, a novel social welfare optimization problem is modeled using wavelet neural network and flywheel energy storage system. Based on augmented Lagrangian function, a continuous time distributed gradient algorithm is proposed for the novel model. In the framework of nonsmooth analysis and algebraic graph theory, we prove that with the algorithm, the optimal solution can always be found asymptotically. Simulation results on 14-bus and 100-bus systems are presented to substantiate the performance and characteristics of the proposed algorithm.

This paper presents an overview for the Z-Source Converter (ZSC) as an emerging power electronics topology for dc/ac converters in general propose motor drive applications. Different ZSC topologies fed from different renewable and alternative energy sources, different motor types with different number of phases and different control algorithms will be reviewed as a part of the ZSC motor drive system. In addition, various applications of the ZSC in automotive field will be highlighted. The ZSC is very promising power electronics converter topology for motor drive applications as, it provides many advantages compared with the traditional motor drive system configuration, such as: single stage conversion with buck/boost capability, improved drive system reliability, improved efficiency, and extended output voltage range.

The active power filter (APF) that consists of a half-bridge leg and an ac capacitor is integrated in the single-phase quasi- Z -source inverter (qZSI) in this paper to avoid the second harmonic power flowing into the dc side. The capacitor of APF buffers the second harmonic power of the load, and the ac capacitor allows highly pulsating ac voltage, so that the capacitances of both dc and ac sides can be small. A model predictive direct power control (DPC) is further proposed to achieve the purpose of this new topology through predicting the capacitor voltage of APF at each sampling period and ensuring the APF power to track the second harmonic power of single-phase qZSI. Simulation and experimental results verify the model predictive DPC for the APF-integrated single-phase qZSI.

The single-phase quasi-Z source inverter (qZSI) topology has recently attracted attention for single-phase grid-tie photovoltaic (PV) applications. However, due to the inherent second-harmonic power flow in single-phase systems, a large qZS network is required to reduce the second-harmonic component of currents and voltages on the dc side. Minimization of the qZS network remains an open issue. This paper proposes a technique that minimizes the qZS capacitance and inductance of the single-phase qZSI topology by employing dc-side low-frequency current ripple damping control. Through analysis of power flow, a second-harmonic power model is derived and the ripple power is analyzed for minimization of the qZS network. A current ripple damping control is proposed to ensure suppression of second-harmonic power flow through the inductors. Simulation and experimental results verify the theoretical analysis, damping control, and the proposed design minimization of the qZS network for the single-phase topology.