This article presents a cost-based robust charging scheme for plug-in electric vehicle (PEV) integrated with the beneficial collaboration of photovoltaic (PV) system. The uncertainty of load/PV power and electricity price is incorporated into the proposed model. To handle the altering feature of the uncertainty resources and achieve a robust charging strategy, the information gap decision theory (IGDT) is utilized. Since the formulated IGDT-based charging model is inherently a multiobjective optimization problem, the nondominated sorting genetic algorithm type 2 (NSGA-II) is used to create the Pareto optimal solutions. To attain the best compromise solution, a fuzzy-oriented selection method is introduced. Moreover, to elucidate more effective constraints for the robust territories (RTs) associated with the uncertainty resources of the proposed model, an evaluation based on the deterministic and nondeterministic operation costs is discussed. To validate the proposed robust charging strategy, a power hardware-in-the-loop experimental setup is developed using OPAL-RT 5700. Furthermore, the effectiveness of the NSGA-II in terms of both robustness and convergence efficiency is validated through comparison with single-objective particle swarm optimization, multiobjective particle swarm optimization and GUROBI solver.

This paper presents an analysis of revenue increment strategies for Electric Vehicle Charging Stations (EVCS) within a microgrid context. The proposed methodology takes into account the utilization of Photovoltaic (PV) power and Grid Electricity Price (GEP) in the EVCS revenue increment process. To this end, optimization algorithm is used to provide a systematic and mathematical approach for addressing the revenue increment strategies for EVCS. The paper shows the formulation of the objective functions and constraints in a precise and structured manner, enabling the exploration of various scenarios and providing valuable insights into the revenue-maximizing and State of Charge (SOC) management capabilities of the proposed strategies. A multi-objective function is introduced, including PV power generation, energy price, and additionally, a second objective function is formulated to ensure Electric Vehicles (EVs) reach their desired SOC at departure time. An evaluation of our proposed optimization is conducted, comparing how model formulation impacts the revenue and SOC achievement. Simulation results demonstrate the accuracy and verification of the proposed strategies.

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In this paper, a new asymmetric multilevel inverter (MLI) topology proposed to avoid the drawbacks of using numerous DC voltage sources and H-bridge cells in asymmetric MLIs. This structure consists of two modules. The first module is a five-level neutral point clamped (NPC5) and the second module is a nine-level packed E-cell converter (PEC9) containing a few low-cost and low-size devices. These modules are connected to each other, and a hybrid PWM modulation is operated to result in the 41-level asymmetric inverter. The proposed hybrid PWM modulation causes to operate only five low voltage and low power switches at the switching frequency, while the rest of the switches operate at low frequency or at the fundamental frequency, which reduces the size and cost of the proposed 41-level inverter. The presented simulations by MATLAB SIMULINK confirm the suitable performance of the inverter as well as the proposed hybrid modulation method.

This paper presents a grid-integrated multilevel inverter based on Packed E-Cell (PEC) structure for connecting renewable energy sources to the existing power grids. This dual source topology benefits from low number of semiconductor devices, simple robust control strategy, and smooth current of the capacitors. The shunt-capacitors of the converter are charged or discharged simultaneously to a quarter of the input DC source via horizontally extension design of the circuit. Thus, by applying only one voltage sensor and simple phase disposition pulse width modulation approach (PD-PWM), the operation of the inverter to generate 17-levels for the output voltage is ensured. For improving the dynamic performance of the converter, a closed-loop controller is designed and a precise mathematical analysis is presented as well. Accurate performance of the proposed structure is assessed by calculating theoretical analyses and simulating the inverter in MATLAB Environment.

The presented article introduces a versatile multilevel inverter based on Packed E-Cell (PEC) topology. This structure is suitable for conversion of photovoltaic energy generations to supply AC loads and uninterruptible power supplies (UPS). Requiring a reduced number of power switches and capacitors compared to other inverters along its control simplicity are the prominent merits of this converter. Thanks to the horizontally extension of the shunt-capacitors, both of them can be charged or discharged to a quarter if the input source, at the same time. Hence, by applying two isolated input sources and one voltage sensor, the proposed inverter generates 17-levels for the output voltage. Simple level shifted pulse width modulation technique (LS-PWM) is used to control the operation of the proposed inverter. Finally, the accurate performance of the proposed multilevel structure is investigated through MATLAB simulations.

The main challenge in hybrid wind-battery systems is the battery cost including investment and replacement. Thus, numerous studies have been conducted on cost minimization. Previous studies often focused on the battery sizing, while the battery performance has also the significant effect on the battery replacement and in turn battery cost. In this paper, a new approach is proposed to improve the battery performance and lifetime. We proposed an extended two-set battery model with new scenarios and formulation to achieve a balance between batteries and managing their power during prediction error. In this model, shallow charge/discharge cycles are eliminated, and batteries experience complete cycles. Furthermore, the battery availability is increased. The simulation results for a case study are presented and the results show the effectiveness of the proposed approach in comparison of conventional models.

In this paper, an adaptive fuzzy passivity-based control strategy is proposed to provide stable operation for a grid-tied nine-level packed E-Cell (PEC9) converter. Passivity theory is developed in the first step to enable the error dynamics of the PEC9 converter currents to reach a much more effective convergence rate using the proposed damping coefficients. Moreover, various operating margins are achieved for the damping coefficients through PEC9 current errors-based 3D curves. In order to establish online estimation for the damping coefficients, the fuzzy controller and Artificial Neural Network (ANN) are combined. Experimental and simulation results are employed to validate the accuracy of the proposed control technique under load variation, parameter mismatch and DC-link voltage variation.

Smart charging/discharging of Plug-in Electric Vehicles (PEVs) is definitely able to bring a significant cost benefit for both EV station owners and EV owners as well. To this end, this paper develops a Mamdani-based fuzzy strategy with the inputs including the forecasted and real PV generation data, electricity price, and the instantaneous state-of-charging (SOC). Moreover, the output power of PEVs is considered as the output of the proposed strategy. In order to attain further smooth and accurate power sharing for PEVs, varied output rules are assigned commensurate with the rated power of each PEVs. In addition, another fuzzy strategy is developed using the instantaneous SOC error to establish a specified SOC for PEVs at the departure time. While two PV panel profiles are taken into account, Simulation in MATLAB/Simulink environment presents accurate and acceptable results from SOCs of PEVs, PEVs output power, prices and grid power.

This is a fact that the battery life is inversely related to the number of discharge cycles. However, these days, the bidirectional smart charging scenario of plug-in electric vehicles (PEVs) has become a hot trend, using them as a storage source at peak load or price. Therefore, this paper aims to present a simple and novel technique in predictive-based linear programming for limiting the number of discharge cycles of PEV. In this regard, a specified number of cycles is defined by the user such that the predictive algorithm tries to use these cycles in the most optimal way. In this paper, first, the effect of the discharging cycle on the battery life available in the literature is presented. Then, the photovoltaic-assisted charging station configuration and desired optimization algorithm are introduced. Following, the main novelty of this work, i.e. a linear technique for limiting the number of discharging cycles will be described. Finally, the simulation results are provided to validate the performance of the proposed method.

In this paper a novel single dc-source switch-capacitor compact multilevel topology is designed based on Packed E-Cell to have the boosting potency for the 11-level operation and to merit as a reliable AC-DC converter for fault tolerant capability. The proposed single-phase compact converter is reduced the active/passive components counts while the output voltage levels are increased which it includes 6 normal power switches and 3 bidirectional switches as well as 2 dc capacitors as the auxiliary dc sources. While the conventional compact converter is incapable of fault tolerant operation, the proposed topology could emerge as a reliable while it has the boosting ability due to its switched-capacitor feature. Moreover, the dc capacitors are actively balanced thanks to various switching states redundancy. The proposed single-phase switched-capacitor converter is validated by theoretical analyses as well as simulation results obtained by Matlab-Simulink where it shows the accurate dc capacitors voltages balancing and prefect 11-level generation in the AC output terminal.

An accurate reference current detection (RCD) algorithm with the ability of double-frequency oscillation cancellation (DFOC) is designed in this paper to control a nine-level packed E-cell (PEC9) as a single-phase active power filter (SPAPF). The reference current is detected through DFOC-based RCD and subsequently injected by the converter. The detected current contains all unnecessary components and is accurate enough to keep the grid current in sinusoidal form with the THD under the permitted threshold. The proposed PEC9-based SPAPF not only guarantees the power quality at the grid side, but also benefits all advantages of PEC multilevel converter. The effectiveness of the proposed SPAPF is assessed in comparison with conventional one and its performance is investigated via simulation studies by using MATLAB/SIMULINK software.

This article proposes a passivity method synthesized by an adaptive neuro fuzzy inference system (ANFIS) to control a grid-tied nine-level packed E-cell (PEC9) inverter. PEC9 is an optimized components count of single-phase, single-dc-source, compact multilevel converter with an appealing feature of dc capacitors horizontal extension. Indeed, PEC9 forms a single auxiliary dc-bus to actively balance its voltages so as grid-tied controller would not be charge of capacitors voltages balancing. Hence, the proposed intelligent-based passivity control (IPC) is designed using only the dynamical model of the PEC9 inverter current. The zero dynamics of state variable errors are obtained and a damping coefficient matrix is presented to theoretically analyze the convergence rate of PEC9 inverter currents under the proposed control functions. In addition, various operating margins of damping coefficients are inquired. So, using the margins, a trained ANFIS as an online estimator tracks the damping injections. It precisely regulates the damping coefficients in unstable conditions; thus, the excellent PEC9 inverter operation is guaranteed. Experiments and simulations validate high reliable performance of the proposed IPC technique under various grid-tied operational conditions.

In this paper, a simple space vector modulation called 1D-SVM integrated with an active capacitor voltage regulation algorithm is applied to the appealing single-phase single DC source nine-level (PEC9) inverter. The proposed 1D-SVM reduces the switching losses by avoiding the additional switching in the middle of defined switching period and also provides the better capacitor voltage regulation compared to carrier based methods. Additional switching could be imposed when the carrier base methods integrated with the capacitor voltage regulation algorithm in PEC9. But, the proposed modulation technique not only prevents the additional occurrences but also decreases the ripples of the capacitors voltages so it can decrease the size of the capacitors. The 1D-SVM calculates and determines a duty cycle for the whole single-phase multilevel converter in each sampling time. The performance of the proposed 1D-SVM for the PEC9 capacitor voltage regulation has been investigated by simulation tests in Matlab-Simulink environment.

This paper proposes a control strategy for a nine-level Packed E-Cell (PEC9) converter to act as Static Synchronous Compensators (STATCOMs). The controller is aimed to support grid stability through controlling the injection of PEC9 active and reactive power. The controller is designed in such way which second-order responses for the errors of PEC9 power can be reached. By analyzing the responses, a tuning process is presented for the controller coefficients as well. Simulation results in MATLAB/SIMULINK verifies the ability of proposed PEC9-based STATCOM.

Compact Multilevel Converters (CMCs) are type of converter topology where both DC sources and AC loads are clamped by active switches and the load current directly passes though DC sources. The H-bridge has been emerged as the first generation of CMCs, but later H-bridge has been developed as Packed U-Cell (PUC) using auxiliary DC capacitors instead of extra DC sources and optimizing number of components. Recently, an advanced CMC based on the PUC has been introduced so-called as Packed E-Cell (PEC) which is further optimized compared to PUC topology. The main challenge in CMCs including PEC is to balance the auxiliary DC capacitors in a low switching frequency technique. In this paper, DC capacitor voltage balancing of PEC is investigated at a low switching frequency operation using Selective Harmonic Mitigation (SHM) modulation technique. Some theoretical and simulation analyses have been performed to evaluate the performance of PEC under low switching frequency operation.

In this paper, an improved Adaptive Neural Fuzzy Inference System (ANFIS) based controller has been designed to regulate the capacitor voltage and load current of Seven-Level Packed U-Cell (PUC7) inverter. PUC7 is an affordable topology due to the least power switches and DC sources; but, it suffers from unstable adjusting capacitor voltage level. Proportional Integral (PI) as a simple linear control method causes overshoots and undershoots in transient response and conducts the system to unstable mode when some uncertainties are existed in the load. However, the proposed ANFIS control method regulates the load current and balances the capacitor voltage without any overshoot or undershoot and transient response even in presence of nonlinear loads. Simulation results of stand-alone mode of operation of PUC7 obtained by MATLAB software also confirm usability of ANFIS control loop to achieve unity power factor, minimum Total Harmonic Distortion (THD) and minimum capacitor voltage ripple while the PUC7 inverter is connected to an AC dynamic load.

This paper presents a control strategy for a Multi-Terminal MMC-HVDC system to enhance the frequency response of AC grids. Using power sharing of both upper and lower arms of MMC combined with a basic equation of control functions, the proposed upper and lower control functions are extracted. In these proposed control functions, total wasted power in both upper and lower arms along with the power generated by the arm inductances are considered. The proposed control functions are capable of providing accurate performance with fast frequency response for AC grids with the existence of both load variations and DC voltage fluctuations. MATLAB/SIMULINK software is employed to demonstrate the merit of proposed controller.

This paper presents a robust fuzzy-based control strategy for single-phase five-level PUC5 inverter in grid-connected mode that can properly improve the grid power quality. The proposed control technique is able to provide unity power factor between grid voltage and current by accurately injecting the needed load currents in presence of unmolded uncertainties. To provide robust property, the proposed fuzzy-based control strategy for accurate operation of PUC5 in grid-connected conditions has been designed. Simulation results in MATLAB software verify the proposed control technique abilities at achieving very low THD grid current, unity power factor, appropriate output voltage and SPWM reference signal.

A control technique based on dynamic model of stand-alone single-phase voltage-source converter (SPVSC) in dq reference frame and droop curve equation is proposed in this paper to stable the voltage of point of common coupling (PCC) when renewable energy resources (RERs) are linked in a microgrid structure. The proposed control strategy is designed with respect to the aimed state variables of PCC frequency and voltage magnitude as well as the droop curve specifications. Moreover, an evaluation on PCC voltage frequency and voltage magnitude-based curve is presented for further analyzing the proposed controller performance. Simulation results in MATLAB/SIMULINK software prove the abilities of proposed controller in reaching stable operation of PCC voltage in microgrid application under load alteration.