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In this article, we propose a modified finite-set model predictive control (M-FS-MPC) for multilevel switching-mode operation of grid-connected nine-level packed E-cell (PEC9) inverter. With a single-dc source, six power switches, back-to-back-connected switches as bidirectional and two capacitors horizontally extended, PEC9 inverter topology has remarkably reduced the components count. Packed E-cell (PEC) prominent feature has the capability of switching among different multilevel voltages: nine-, seven-, or five-level under faulty switch cases without any structural modification and only if the controller is appropriately designed. M-FS-MPC is proposed to operate the grid-connected PEC with the multilevel switching mode under bidirectional switch fault operation. Switching among five-, seven-, or nine-level voltages is attained by proper dc capacitors’ voltages regulation, whereas the desired current injection with low total harmonic distortion (THD) and requested power factor for addressing grid connectivity applications is guaranteed. The system discrete model is developed and the experimental results verify the performance and robustness of M-FS-MPC in targeting the capability of PEC multilevel switching-mode operation and grid connectivity requirements in both steady and transient states.

Seven-level packed U-cell (PUC7) is known as a cost-effective low-component multilevel inverter. However, PUC7 challenge is the capacitor voltage balancing; so, it conventionally needs an additional voltage control integrated into the current control loop. Because of extra variables, the control problem is further complicated for the grid-connected PUC7. This article proposes an optimized sliding-mode control (OSMC) based on the current dynamical model to track the load current reference and to self-balance the capacitor voltage in both grid-connected and stand-alone operations. By optimizing the OSMC control factor using a visual-based optimization method, PUC7 switching operation is controlled to self-balance the capacitor voltage while any extra voltage controller is needed. An adaptive control law has been also proposed for self-tuning of the PUC7 current reference to track the load and dc source variations. Experimental and simulation results of PUC7 prove the excellent performance of the proposed OSMC in achieving capacitor self-voltage balancing operation.

Power electronic matrix converters are converters carrying out just one solitary transitional stage. AC-AC conversion automatism in matrix converters is attained through the exploitation of bidirectional controllable power switches associated with a structural matrix. The indirect matrix converter is an alternating preference to the direct matrix converter embodied by AC-DC converter and DC-AC inverter. In this paper, an assemblage of Pulse Width Modulation categories is used to control the dual stages of IMC. AC-DC converter is modulated through the well-known space vector algorithm, while DC-AC inverter is modulated through a novel algorithmic conception referred to as the digital scalar algorithm. Comparative analysis between the conventional DSVPWM modulation and the novel proposed modulation technique is escorted demonstrating that the latter is facilely comprehended and simply put into real-time practice. This paper comes forward with digital signal processor real-time enforcement, conceived for indirect matrix converter. Uniting both original approaches into one topological system entrained a significant decrease of 38% in real-time computation assesses. Throughout the paper, it is well proven that the proposed solution results in high-quality input/output waveforms, and averts from servicing supplementary devices that trigger silicon devices' gates. Numerous experimental enquires within the delivered research reveal advantageous aspects of the contemporary approach from overall simplicity to entire effectiveness.

Industrial Customers are dispersed at various levels of the electrical network and fed together with other customers' categories in a distributed environment. Optimizing industrial processes in the presence of other customers' categories supplied by the same infrastructure is a challenging issue. Existing studies have analyzed the effect of different Industrial Demand Response Programs on the distribution network, which also supplies other customers' categories. They show the need for improving the distribution performance although multiple demand response programs have been suggested for this purpose. In this paper, a new approach is presented considering an optimal synchronized process among all consumers' categories. It shows that the balance between generation and demand is maintained, the customer satisfaction is guaranteed, the profit is maximized and the cost is minimized for all customers. Various time constraints set by different industry productions are considered in the optimization process. Fairness problems, multiple pricing schemes and formulation for the same are elaborated. The method is validated through a simulation on Matlab using K-Means Clustering and multi-objective particle swarm optimization (MOPSO) along with data prediction.

Multi-Level Inverters (MLI) have become of great importance for electrical energy supplement to grids due to its modularity, lower Total Harmonic Distortion (THD) and decreased filter needs. However, although multilevel inverters achieve high voltage levels, increased number of power switches are required which make them more prone to breakdowns and faults. Among active devices failures, Open-Circuit (OC) faults are extensively explored in research studies. Hence, this paper presents a deep overview concerning methods based on Artificial Intelligence (AI) algorithms involved in diagnosis and localization of OC failure in different multilevel inverter architectures. Initially, two major classifications of fault diagnosis methods for OC switch failure are listed and clarified briefly. Then, AI algorithms are discussed thoroughly. Further, certain criteria with several standards are formulated to differentiate between strategies investigated in publications. Then, various implemented techniques in literature are widely overviewed and compared in an original table.

Multiple types of Demand Response Programs (DRPs) are offered within the same infrastructure. Multiple objectives of technical, economic and marketing order are targeted. Defining a model with weights for the various objectives and the related Key Performance Indicators (KPIs) is of a high importance. A structured model can be achieved through the assessment of an adequate market design with adequate dynamic pricing schemes to be offered to consumers, coupled with reducing costs at various levels and optimizing the technical indices while using business intelligence and big data. The originality of this paper resides in the simulation of a model combining multiple DRPs with multiple objectives and their assigned weights, hence the elasticity of dynamic parameters and criteria selection to achieve the compromise. It includes the proposal of dynamic pricing schemes for consumers’ detected clusters while optimizing costs and considering technical constraints. The optimal solution is the result of combining an assessment process based on historical data coupled with intensive what if scenarios to serve the planning and optimization phase, thus its application will be guaranteed. The validation is preformed through a simulation on Matlab using multi-objective optimization clustering based with assigned weights.

Stirred photobioreactors (PBR) have been extensively used for microalgae cultivation due to their good mixing and mass transfer conditions. However, it is difficult to study the hydrodynamics behavior with experimental procedures of these PBRs. Computational Fluid Dynamics (CFD) is a common method that has been widely used to simulate the performance of PBRs, reduce the design cost and improve work efficiency. The objective of this study was to evaluate hydrodynamics and mixing conditions of a novel cactus-like PBR. A hydrodynamic study was conducted on ANSYS FLUENT. The simulation results obtained from the VOF turbulence model showed that the fluid flow exhibit similar behavior in most parts of PBR except around the impellers and the bottom of the reactor. The velocity contours showed efficient mixing performance. In addition, the turbulence kinetic energy having a vital influence on mixing characteristics was found between the values of 1.4 × 10−3 and 7.5 × 10−3 m2/s2 and the lowest values were observed at the bottom of the reactor. Moreover, the area-weighted average of air volume fraction was calculated to be 0.0084. The obtained results could be used to re-design PBR configurations considering the sparger type and size, and the impeller placement.

This paper presents a detailed review on different architecture topologies for Electric Vehicle (EV) charging station. The proposed paper enables to have a solid reference on electric transportation charging station topologies on different levels starting from the infrastructure of common bus to types of chargers and power flow uni/bi-directionality. Besides, two detailed comparative analyses on recent proposed EV architecture topologies based multilevel converters as Cascaded H-Bridge (CHB) and Neutral Point Clamped (NPC) converters are elaborated. The presented CHB analysis tackles enhancements’ attempts on charging time, balancing batteries’ State-Of-Charge (SOC), reducing power losses and balancing capacitors’ voltages. However, the presented NPC analysis includes attempts in improving NPC’s limited voltage balance operation, balancing the bipolar DC bus, regulating load disturbances, enhancing power quality and power utilization. The two analyses are summarized in two comparison tables to sum up the aim and the enhancement of each presented attempt.

This paper presents a direct non-linear based predictive control for a single-phase Shunt Active Power Filter nine-level Packed E-Cell inverter (SAPF-PEC9). The proposed control based on a Finite Set Model Predictive Control (FS-MPC) has been designed to compensate the reactive power requested by the nonlinear load at the Point of Common Coupling (PCC). An outer loop consisting of a PI regulator together with a low pass filter is used to regulate the main capacitor voltage and to inject the proper filter reference current. Meanwhile, the overall design is very simple where a very fast and robust controller is achieved. Moreover the nine-level converter operation together with the direct predictive approach allows the reduction of the passive filter at the shunt converter terminals. Hence a microscale filter is obtained. The performance of the proposed hybrid controller in reactive power compensation, harmonics suppression and unity power factor operation is investigated under stiff grid conditions (zero impedance) through both normal and dynamic load-change operation. Simulation results are provided to validate the fast and effective dynamic performance, the very low harmonic content in the mains current as well as the DC capacitors balancing of the PEC inverter.

In this paper, a fixed switching frequency model predictive current controller is designed and implemented on a sensorless five-level packed U-cell (PUC5) inverter interfacing the utility. The predictive control methodology is based on a voltage vector generation technique for the cost function optimization by nullifying its derivative. The aim of the controller is to allow a fixed-frequency operation with no iterations while operating as a utility line current regulator. A pulsewidth modulator based on employing PUC5 redundant switching states fixes the PUC5 auxiliary dc bus capacitor voltage to its desired level with no necessity of a regulator; the overall technique reduces system complexity with less sensors and no loops in the predictive algorithm making it suitable for industrial applications. System discrete model is developed and experimental results verify the performance of the designed controller in making a fast response in regulating the grid current and balancing the capacitor voltage.

Many control techniques for three-phase active filters with the aim of improving the power factor and reducing the current harmonic distortion at the source level exist today and are widely reported in the scientific literature. Almost all of these methods are designed for a perfect sine-wave source and do not perform sinusoidal current when voltages are distorted or unbalanced. The work developed in this paper concerns the active filtering on a perturbed and unbalanced network. First, the proposed control method is described and validated by simulations and experimental results, and then the proposed method is compared to the classical control laws such as the original p-q theory, the modified p-q theory and the p − q − r method. Experimental results are conducted on a three-wire low power distribution network under perturbed voltage and non-linear load using a DSPACE control system. The assessment is performed on the source currents after filtering, and a comparative evaluation in terms of unbalance factor and current Total Harmonic Distortion ( THD i ) is carried out for all methods.

In large photovoltaic plants (PV farms), the partial shading phenomenon due to clouds leads to a decrease in the total power of the installation, and consequently a decrease in profitability. For improving the plant yield although partially shaded, a reconfiguration of the panel's connection is performed. Several reconfiguration algorithms are published, and a switch matrix is controlled providing panels interconnectivity. However, these algorithms are based on measurements made on each panel of the farm providing the solar radiation on it, its output voltage, and current. This conventional method needs a complex and expensive installation of a great number of instruments, it requires also regular maintenance. This research aims to find a low-cost and spacesaving reconfiguration method using the least possible measuring devices. A feed-forward neural network is developed to estimate the shading rate of each PV zone using meteorological data and sun position. It is found that training a regression model responds better to the problem. Also, training a feed-forward neural network with the Levenberg-Marquardt algorithm proves to be efficient in terms of stability, speed, and convergence with a small error.

In this paper a grid-connected three-phase seven-switch boost-type photovoltaic (PV) current source inverter (CSI7) is investigated. The designed CSI7 injects sinusoidal currents into the grid with a peak amplitude ${\hat I_g} = 7.71A$ for a maximum PV input-power ${P_{pv - MPP}} = 3.6kW$ at ${V_{pv - MPP}} = 432.48V$ and ${I_{pv - MPP}} = 8.32A$ . The principle of operation is thoroughly described and the voltage and current stresses on the semiconductor power devices are analytically determined. Calculation formula for the design of the passive components are also provided. These calculations are performed based on the inverter's rated operating conditions and their accuracy is verified by digital computer simulations. Accordingly, proper active and passive components are selected and a 3. 6 kW PV-CSI7 is designed. The performance of the designed inverter are evaluated under ideal operating conditions $\left({{T_a} = 25^\circ C,G = 1000W/{m^2}} \right)$ and under shading conditions. An overall efficiency around 98 % is obtained.

Multilevel inverters have been greatly spread and utilized in industry especially for high power and voltage ranges. However, these inverters have high number of elements which thereby boost the probability for switch failure. Unfortunately, switch faults will affect the system reliability and may lead to system damage completely if not detected and isolated rapidly. Among the failures, Open Circuit (OC) faults are the most critical ones which are widely investigated in literature. Hence, this paper presents a survey about fault detection strategies based on signal processing methods for OC faults in different multilevel inverter topologies. First of all, fault diagnosis approaches for OC switch failure are divided into two categories and explained briefly. Then, signal processing techniques are investigated in details. Further, specific criteria are developed to evaluate proposed methods in literature. Then, broad literature review of applied techniques is compared and summed up into three tables. Finally, a general conclusion is presented.

The integration of distributed renewable energy (DRE) into grid is experiencing significant growth. Due to its intermittent characteristics, DRE have several impacts on system operation. This integration does not only influence the distribution network, but also it affects the transmission network. This paper analyzes the impact of increased penetration of distributed renewable energy specifically the PV generation on static voltage stability of transmission network and helps to find the maximum allowable capacity of DRE penetration. DRE integration with different weather conditions is studied in this paper. Voltage Collapse Proximity Index (VCPI) is used to evaluate the voltage stability of the system. Simulations are carried out on IEEE-39 bus test system using Power system analysis toolbox (PSAT). It can be concluded that the integration of high level of DRE into the grid affects the voltage stability, and it may lead to voltage collapse. The analysis results can be used to provide guidance for the allowable percentage of DRE integration.

This document describes the Model Predictive Control MPC for a three-phase to three-phase direct matrix converter with an L filter at the input and a C filter at the output for networks connection applications and wind turbines. This AC/AC converter allows the generation of sinusoidal output voltages with variable frequency, input currents with low harmonic distortion and a unit power factor at the source. The work begins by developing the equations of the system, designing the predictive control of the system in the DQ rotating frame. The proposed MPC control uses a cost function J to select the switching state to be applied to the next switching. This gives a sinusoidal output voltage and input currents in phase with the input voltage. Simulations using Matlab/Simulink are presented to validate the proposed control scheme.

In recent decades, the microgrid concept emerged as a solution to electrify remote areas and integrate renewable energy sources to mitigate environmental pollution. Owing to the evolution of power electronic devices, the ease of control, and the improved efficiency and reliability, DC microgrids are gaining increased interest. Many kinds of research address the hierarchical control in DC microgrids to accomplish multi-objectives. On the first and second levels, the control targets fast dynamic variables to achieve its objectives. Yet, on a third control level, general management functionalities are executed. Many of these management functionalities target the system variables with a slower dynamic and so, to prove the effectiveness of the proposed hierarchical control, a 24-hour model simulation is required. The wide time-range dynamics of the existing system variables make the 24-hour modeling subject a complicated matter especially, on standard computers with conventional performances. To overcome this problem, this paper proposes a 24-hour DC microgrid model which offers the best tradeoff between model precision, complexity, and simulation speed. The multi-objectives hierarchical control is adopted: on a first and second control level, several averaging techniques are introduced and compared to a detailed reference model in terms of accuracy and calculation step size. DC microgrid's general management strategy is adopted on the third control level. Simulation tests are performed on MATLAB/Simulink software to prove the viability of the proposed 24-hour model.

Assessment and qualification of consumers’ behavior play an important role in the selection of the suitable Demand Response Programs (DRPs) achieving their engagement and satisfaction. Targeting the assessed consumers’ clusters with adequate and elastic pricing schemes ensures their participation. The model offers the full visibility on the dynamicity of pricing and demands for the various simultaneous clusters’ DRPs operating in a synchronized manner. The originality of this paper resides in the classification of consumers’ behaviors according to the criteria and the elasticity of the multiple dynamic offered pricing schemes for the clusters along with their impacts on each other. An optimal solution is reached through assessment, qualification, planning, benefits’ visibility on various proposals and relocation. Intensive what if scenarios assist in the decision making process of the optimal selection in a planned phase. Thus, contracts’ terms and conditions suiting the consumers and the electrical utility are arranged. The method is validated through a simulation on Matlab using clustering and multi-objective optimization.

Transformerless single-stage Current Source Inverter (CSI) is a very promising power electronic converter due to its inherent boost capability and ease of control. This paper investigates the performance of two traditional CSI topologies with different switch count (conventional six-switch CSI and seven-switch CSI7), for grid-connected Photovoltaic (PV) applications. Both topologies are controlled using the Space Vector with Pulse Width Modulation (SVPWM) technique. The performance of the proposed topologies are assessed by means of numerical simulations and the results are compared in terms of Common Mode Voltage (CMV), ground leakage current, and injected grid-current harmonic distortion THD. Furthermore, conduction and switching semiconductor power losses are computed and simulated over a grid period. Simulations are carried-out at different operating points of the converter to evaluate the performance of both topologies for grid-connected PV applications. The obtained results prove that the CSI7 topology strongly reduces the fluctuations of the CMV and, therefore, results in lower ground leakage current. It also allows the injection of high quality currents with lower THD into the power grid and, commonly, reduces power losses in power semiconductors. With respect to conventional CSI, the CSI7 topology offers high performance criterion and increased efficiency at the cost of one additional power switch.

This paper discusses the state of the art of different topologies of Modular Multilevel Converters (MMC) used in Electric Vehicle (EV) power-train. A comparative study of recently proposed MMC used as a propulsion application in EV is elaborated here for the first time in EV research field. First, this paper delivers a general overview on multilevel converters associated with their various types and advancements. Then, it discusses the change from Internal Combustion Engine Vehicle (ICEV) to EV. Finally, it conducts a comparative study on the existed MMC topologies by categorizing them into five sections according to their types and contribution. First section includes the topologies that follow the same MMC architecture of cascaded half bridges. Second section discuses topologies consisting of cascaded H-bridge (CHB) and points any recorded contribution in comparison with conventional topologies. Third section focuses on topologies that reduces switching elements significantly making the whole system more reliable, cost competitive, more efficient and more size compressed. Fourth section tackles topologies with hybridized energy storage system using Ultra-Capacitors (UC) in order to track its impact on power density limitation. Last section adopts hybridized multilevel converters to observe its effect on system's efficiency and switching losses. The contribution of this paper is pointing on the strength and weakness of each topology in terms of fault tolerance, balance control, size, reliability, efficiency, cost, power density, mobility range, switching elements and switching losses.

In this research, double space vector pulse width modulation is used to control the dual stages of the indirect matrix converter. This modulation technique is facilely comprehended and simply put into real-time practice. An experimental prototype of the indirect matrix converter is developed. The modulation algorithm is implemented on a digital signal processor. After establishing the duty ratios and the modulation signals, the gate drive signals are formed and sent to the semiconductor devices. Keen analysis of the overall system and the overall consolidation of topology, modulation, and drive implementation is presented.

In this paper, a bidirectional power electronics converter assisted by Photovoltaic Panels for Electric Vehicle battery charging application is presented. The charger is composed of two conversion stages: an AC/DC converter represented by an active-rectifier, and a DC/DC converter illustrated by a Dual Active Bridge. The solar renewable energy is considered an alternative DC source assisting in charging the battery. The charger is tested using MATLAB/SIMULINK under different charging and discharging scenarios. An Electric Vehicle equipped with a bidirectional battery charging system has the ability to act as source or a load.

Six-Switch current source inverter (CSI) is a promising unidirectional DC-AC power conversion topology deduced from the reversed structure of the very sparse matrix rectifier. This latter is a single-stage boost-type inverter suitable for grid-connected applications as it provides active power injection from renewable energy sources into the AC grid. This paper investigates the performance of three different soft-switching strategies for three-phase six-switch grid-connected CSI. These strategies are analyzed in terms of the number of switching transitions, DC-link current ripple, average global value of the conduction and switching power losses, as well as, the quality of the injected grid-currents. The proposed evaluation is based on both, theoretical analysis and computer simulations. A comparative study is, commonly, established and the optimum modulation strategies are selected.

Prediction on electrical consumption of clients and their selection for appropriate demand response programs (DRPs), are a major challenge for the stability of the distribution network. Prediction accuracy of patterns and their matching with reality plays an important role in DRPs modeling for better consumers’ participation. Existing Approaches studied several aspects of prediction and baselines in DRPs environment. The originality of this work consists in demonstrating a prediction based approach, studying its accuracy and continuously adding new patterns to the training set. The variation versus planning phase is kept minimal and adapted to customers’ variations. It is achieved at the individual and aggregated profiles, thus customers’ classification and engagement are ensured. The approach is validated through a simulation on Matlab. Objectives include the customer prequalification and the effects of prediction accuracy on the balance generation/demand.

Microalgae cultivation for energy production has gained a great interest in the past few decades in view of the increase in Green House Gas (GHG) emission and the global climate changes. The main challenge of producing microalgal based biofuels is to produce sufficient amount of biomass at minimal costs and at high efficiencies. The reason why engineers have examined and developed new technologies for the production of microalgal biomass. In this work, different types of photo-bioreactor systems for microalgae cultivation exploited in literature are classified and evaluated. Moreover, the main design considerations of a photo-bioreactor (surface-to-volume ratio, optimal diameter and length for tubular photobioreactors, mixing process, orientation and inclination, light and CO 2 supply) to provide a controlled environment in order to achieve optimal growth and product formation of microalgae are listed and discussed thoughtfully.

Originally proposed at the beginning of the twenty-first century, as a solution to electrify remote areas and integrate renewable energy sources to mitigate environmental pollution, Microgrids are gaining nowadays an increased interest, especially, DC microgrids. Many merits over AC grids, such as ease of control, higher efficiency and reliability make DC microgrid applications spread worldwide. Several researches address the control hierarchy and strategy in DC microgrids. On a local control level, Droop Control is a commonly used technique that ensures simultaneously DC bus voltage regulation and proper load sharing between operating converters. Yet, this paper investigates DC Microgrids control strategy from a different approach which is convenient, fundamentally, for remote islanded DC Microgrids. In such applications, the existence of the energy storage system (ESS) is substantial for a safe and stable Microgrid operation, especially, due to the intermittency and unpredictability of renewable energy sources (RESs) generated power. Hence, this paper proposes a simple, local control level, technique which is applied to a standard islanded DC Microgrid topology including: RESs, ESS and a back-up Diesel Generator (DG) as a traditional polluting source. The adopted control strategy main goal is to stabilize DC bus voltage, through ESS, and prevent battery excess discharge by connecting, temporarily, a back-up DG to the Microgrid as an additional source. When connected to the common DC bus, the DG takes charge of stabilizing the DC bus voltage. Once the power flow balance equation is reached again, the DG is disconnected instantly in order to reduce Carbone emissions. Finally, simulation tests are conducted in order to prove the viability and robustness of the proposed method.

Integration of the renewable energy sources (RES) in distribution systems is accompanied with a lot of challenges to power system protection, control and operation. This integration can cause reverse power flow that affects the voltage stability of the power system. To avoid the power system instability, the monitoring of the integration of RES is necessary. In this paper a hybrid algorithm is proposed to monitor reverse power flow, and then it was tested on the IEEE-39 and IEEE-118 node test feeders.

In this research, an assemblage of pulse width modulation categories is used to control the dual stages of the indirect matrix converter. The novel modulation technique is facilely comprehended and simply put into real-time practice. An experimental prototype of the indirect matrix converter is developed. The modulation algorithm is implemented on a digital signal processor. After establishing the duty ratios and the modulation signals, the gate drive signals are formed and sent to the semiconductor devices. Keen analysis of the overall system and the overall consolidation of topology, modulation, and drive implementation is presented.

Multilevel, transformer-less inverters are becoming more and more a subject of interest in grid connected photovoltaic system due to their low cost and high efficiency features. However, most of the designed grid tied systems show more than one stage conversion process to inject the amount of power generated to the grid. Mainly, a DC-DC conversion stage is always requested between the Photovoltaic (PV) panel and the inverter. In this paper, a single-stage grid connected design based on seven level packed U-cell inverter controlled by a finite-set model predictive algorithm with a maximum power point tracking capability is presented as a competitive single-stage/phase grid-connected topology. The overall design is less complex compared to existing topologies where a maximum power point operation of the PV system is well achieved without the use of a boost converter. A predictive algorithm takes in action of the inverter control. Simulation results in MATLAB/SIMULINK are presented to validate the proposed design in both constant and variable irradiation conditions.

The growing permeation of green renewable energies into electrical systems has been considerably remarked in industry. Thriving integration of these external sources into the current grid massively depends on allotted power converters and enormously counts on their specifications and control methods. In this scenario, and in relation to what was previously mentioned, this paper reflects a review of three-phase AC/AC power converters derived from the conventional indirect matrix converter

With the proliferation of renewable energy sources and the adoption of several policies to reduce environmental risks caused by traditional polluting sources, the concept of microgrids, especially DC microgrids, is currently gaining interest. In fact, most renewable energy sources (RESs) and loads are inherently DC type. Moreover, DC microgrids offer many merits over AC ones in terms of ease of control and efficiency. While most of researches address the control hierarchy and strategy in DC microgrids, this paper focuses on the modeling and simulation aspect. A typical configuration of an islanded DC microgrid is modeled in MATLAB/Simulink, and a primary-level control strategy is adopted where two approaches of converters modeling are tested: instantaneous and average model. The two approaches of modeling are compared in terms of precision of losses modeling, dynamic response of the system, simulation time, and computational burden. Simulation tests are conducted, and the results show that, despite its accuracy, the instantaneous model can be applied only for short-term simulations due to many limitations, whereas average converter modeling presents a better solution for long-time simulations, since it ensures a tradeoff between model accuracy and simulation time, which makes the application of the three levels of hierarchical control in DC Microgrids valid in one simulation model.