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This article proposes a control strategy for a three-phase Z-source inverter (ZSI) using a modified discontinuous space vector modulation. The main advantages of the proposed control strategy are the enhanced output power quality and the compromise in the reduction between the conduction and switching losses. Furthermore, the reduced switching losses are achieved by the elimination of one switching transition in each half sector with a proper selection of the shoot-through (ST) state distribution. In addition, the reduced conduction losses are achieved by dividing all sectors equally into 30°. The MATLAB/SIMULINK simulation is carried out to verify the effectiveness of the proposed control strategy and to compare it with the existing space vector modulation techniques that utilize distributions of four and six ST vectors. PLECS software is used for the calculation of the conduction and switching losses. Compared to the other modulation techniques, the key features of the proposed control strategy are the improved boosting capability of the output voltage, the low total harmonic distortion, the reduced conduction and switching losses, and the reduced inductance current ripple. An experimental test bench that comprises a three-phase ZSI feeding an $R$ load, controlled by a dSPACE MicroLabBOX, is used to verify experimentally the effectiveness of the proposed control strategy. It is envisaged that the proposed control strategy can be very useful for electrical drive applications integrating a three-phase ZSI due to its capability to improve the output waveform and reduce the harmonic distortions, switching, and conduction losses.

Aiming to take full advantage of Electric Vehicles' (EVs) batteries despite unpredictability in their arrival and departure time, in this paper, a two-level hierarchical model predictive controller coupled with an innovative charging-discharging scheduler for EVs in building microgrids is proposed. Besides providing a complete framework for its design, this paper also analyses different scenarios of EVs' batteries exploitation that would be beneficial for both building microgrids and EVs' owners. The simulation results conducted in MATLAB Simulink demonstrated that the proposed hierarchical controller could assure that most EVs are completely charged before their departure time while enabling building microgrids to increase their annual photovoltaic self-consumption rate by about 3 percent point compared to the uncontrolled strategy.

This paper discusses a renewable energy system connected to a dual-function power grid through a parallel active power filter for simultaneously improving the power quality and injecting photovoltaic energy to the power grid in the presence of non-linear load. The rejection of disturbances affecting the electrical network supplying the non-linear load in the presence of the photovoltaic system is provided by the proposed direct power control (DPC) command. The combination of a fractional order PID controller for the regulation of the DC bus voltage with an intelligent method of tracking the maximum power point articulated on the fuzzy logic, reserved to solve the problem of quickly changing weather conditions, are proposed for the DPC strategy. The quality of energy offered by the improved DPC resides in the elimination of the undesirable harmonics of the source currents, thus operating the studied system under a power factor very close to the unit with a satisfactory rate of harmonic distortion, in agreement with the international standard IEEE-519. The overall control of the presented system has been the object of an assessment under different states of the power source behavior: balanced, unbalanced and distorted by simulation using MATLAB/Simulink software. The obtained simulations results demonstrate the performance, robustness and feasibility of proposed methods compared to the existing techniques in the literature. Key words: active power filter; direct power control; disturbance rejection; fractional order PID regulator; fuzzy logic MPPT controller.

This paper deals with a shunt active power filter (SAPF) integrated in a photovoltaic (PV) system, which is interfaced to the grid via a double-stage configuration, for simultaneously improving the power quality in the existence of non-linear loads and injecting the PV harvested power to the power grid. The direct power control (DPC) based on the conventional Proportional-integral (PI) suffers from some shortcomings in the transient state, such as large overshoots and undershoots in the voltage. Long response time is another disadvantage when using such a controller. To overcome this situation, the proposed control method is equipped by an anti windup fractional order proportional-integral differentiator (AW-FOPID) regulator, replacing the standard PI or PID regulators to maintain the DC link voltage at its desired value with small overshoots and undershoots in the voltage, while maintaining a short response time. The AW-FOPID controller, however, has five parameters, which makes it troublesome to tune. Accordingly, to adjust this AW-FOPID parameters, the Particle Swarm Optimization (PSO) algorithm is employed by minimizing the Integral Time Absolute Error (ITAE). Furthermore, an intelligent algorithm for tracking the maximum power point (MPPT) based on fuzzy logic has been applied to eventually resolve the drawback of the rapidly changing weather conditions. The overall control scheme is examined by simulation using MATLAB/Simulink software. The obtained simulation results and comparative study demonstrate the feasibility and performance of this control strategy.

International audience; Energy storage systems are key elements for enabling the design of MicroGrids in buildings, specially to deal with stochastic renewable energy resources and to promote peak shifting. However, inaccuracies in the batteries' mathematical models due to temperature and ageing effects can reduce the performance of a MicroGrid system. To tackle these uncertainties, this article presents a two-level hierarchical model predictive controller empowered with a data-driven algorithm for real-time model identification of Lithium-ion batteries. The objective is to enhance their state of charge estimation and to make their maximum use without damaging them. The results demonstrate that it improves up to three times the accuracy of state-of-charge estimation and increases about 3% the annual building MicroGrid selfconsumption rate. Furthermore, the division of the building MicroGrid energy management system into two hierarchical levels soften the drawbacks arise from the inaccuracies of day-ahead data prediction while reducing the computational cost. The proposed architecture guarantees higher energetic autonomy indexes than a conventional rule-based controller in all scenarios under study.

The work on this paper aims to improve the efficiency of a photovoltaic energy system. Reducing the losses in the adaptation stage allows to improve this efficiency. For that, in this paper we will work on the adaptation stage between the solar panels and the loads to reduce the losses. As a first step, we will present a comparison between a conventional DC-DC boost converter usually used in solar system and a quadratic boost with a single switch. This comparison aims to show the advantage of using quadratic converters with high gain in solar systems. The results show that the quadratic converter has a higher efficiency compared to the conventional one, it allows also to reach higher values of gain for a practically acceptable values of duty cycle. This comparison justifies the choice of the quadratic converter. Then, a new dual-mode variable step-size maximum power point tracking (MPPT) algorithm is proposed. The proposed algorithm is used to control the quadratic converter. The proposed algorithm is based on the perturb and observe (P&O) algorithm. The P&O is one of the most known and used MPPT methods, its drawbacks appear during fast solar irradiance variation. The proposed control method is a double mode algorithm. The first mode is active when the operating point is near of the MPP. This mode allows to stabilize the operating point to reduce the steady-state oscillations that occur using the P&O. The second mode is activated when the operating point moves away from the MPP. This mode is a P&O with a large step size that allows tracking the MPP quickly which also reduces the losses. The proposed algorithm is tested through simulations using Simulink/MATLAB. Simulations results prove the efficiency of the proposed algorithm and its advantage compared to the P&O.

International audience; Building microgrids have emerged as an advantageous alternative for tackling environmental issues while enhancing the electricity distribution system. However, uncertainties in power generation, electricity prices and power consumption, along with stringent requirements concerning power quality restrain the wider development of building microgrids. This is due to the complexity of designing a reliable and robust energy management system. Within this context, hierarchical control has proved suitable for handling different requirements simultaneously so that it can satisfactorily adapt to building environments. In this paper, a comprehensive literature review of the main hierarchical control algorithms for building microgrids is discussed and compared, emphasising their most important strengths and weaknesses. Accordingly, a detailed explanation of the primary, secondary and tertiary levels is presented, highlighting the role of each control layer in adapting building microgrids to current and future electrical grid structures. Finally, some insights for forthcoming building prosumers are outlined, identifying certain barriers when dealing with building microgrid communities.

This paper proposes a predictive direct power control for shunt active power filters. The main goal of the proposed active filtering system is to eliminate the unwanted harmonics and compensate fundamental reactive power drawn from the non-linear loads. The proposed control is characterized by a high transient dynamic, which makes it an interesting alternative for classic direct power control. In order to improve the efficiency of the proposed control, different simulation and experimental tests were carried out with real time implementation on dSPACE 1104 card in steady and transient states. The obtained results indicate closeness between simulation and experimental tests, which prove and verify the effectiveness of the proposed control strategy.

This paper presents supervision and control power system for photovoltaic generators with battery storage. The system consists of a photovoltaic (PV) generators and a battery bank supplying kept a load. Two applications are presented throughout this paper. In the first one, the load is made variable while in the second it is considered constant in a case of water pumping. The maximum power point tracking (MPPT) algorithm is applied to reach the maximum power of PV panels. In this work, two algorithms have been used. A supervision unit is also provided to allow maximum power production for the PV generator, protect the batteries against overcharge and deep discharge and satisfies the energy needs. The simulation results under Matlab/Simulink for the two applications show that the proposed supervisor makes the autonomous photovoltaic system capable of working normally by charging and discharging batteries no matter what the meteorological conditions are. This fact guarantees the effectiveness of the proposed applications.

This study deals with a three-phase double-stage multifunctional grid-connected inverter interfaced with a photovoltaic system. The studied system consists of a photovoltaic array, a dc-dc boost converter and a three-phase voltage source inverter connected to the utility at the point of common coupling. To ensure the multifunctional feature, we propose a predictive current control which uses a discrete-time model of the system to predict the future value of the filter current for different voltage vectors. Selection of the optimal voltage vector aims to minimize the error between reference and predicted current by using a cost function. Then, perturb and observe Maximum Power Point Tracking is applied to the dc-dc boost converter to extract maximum power from the photovoltaic array. The main benefits of the proposed system are: harmonic and reactive current elimination, reactive power compensation and feeding photovoltaic power into the utility. The proposed control algorithm is performed on a Matlab ⧹ Simulink™ environment, simulation and experimental results confirm the effectiveness of the proposed control method in term of total harmonic distortion and power factor correction. The performance of the proposed control has been compared with hysteresis and direct power control strategies. Dynamic state results show that the proposed method provides a better performance and more stability under fast environmental conditions changing than hysteresis current control.

In order to overcome the disadvantages of conventional DPC control, this paper proposes a combination of direct power control with space vector modulation used in shunt active power filter. For this reason, from the beginning, every efforts will be directed towards developing a control strategy that achieves the best results by reducing current THD and power ripple. The approach is based on the replacement of switching table and hysteresis controllers by a vector modulator and PI controllers to ensure operation at a constant switching frequency. A series of simulations under Matlab / Simulink environment, followed by a practical implementation using a Dspace 1104 are demonstrated.

International audience; Renewable energy sources are increasingly deployed as distributed generators, restructuring the traditional electrical grid toward smart grids. Their intermittent power generation makes difficult the development of a complete carbon-free MicroGrid. Hence, aiming to keep the safe operation of a building MicroGrid (BMG) under stochastic variations in the power imbalance while respecting the requirements imposed by grid regulation to maximise self-consumption, a three-level energy management system was designed. The BMG main grid interaction aspects are assured by the two upper control level throughout a hierarchical model predictive control, whereas the power sharing among all electric vehicles is ensured via a deterministic state machine. The entire hierarchical control structure was tested through simulation in MATLAB under different scenarios. Results prove that the proposed control allows the BMG to keep its self-consumption index within expected boundaries despite environmental disturbances.

Predictive direct power control (P-DPC) has been suggested as an effective alternative to the conventional direct power control (DPC) applied to PWM converter such as active power filter (APF) and PWM rectifier. It is characterized by a high transient dynamic, which makes it an interesting alternative for conventional direct power control (DPC). Furthermore, in the existence of a non-linear load, the source currents would become highly distorted under perturbed and unbalanced voltage grid conditions. In order to resolve the problems mentioned above, the present paper proposes an improved P-DPC control for APF based on disturbance rejection principle, which is able to operate under balanced, unbalanced and distorted grid voltages conditions and can attain sinusoidal source currents with a respectable total harmonic distortion (THD) meets with IEEE-519 standard. Simulation results and comparative study are presented to confirm the efficiency of the proposed approaches.

This paper addresses the design of a robust Maximum Power Point Tracking (MPPT) controller for a small wind energy conversion system fed by a Permanent Magnet Synchronous Generator (PMSG). The proposed MPPT controls the generator rectified voltage instead of the rotational speed avoiding the need for a mechanical sensor. Traditionally, this control problem is performed using a Proportional Integrator (PI) controller optimised at a specific operating point. However, the PI controller does not guarantee the promising transient performance under changing operating conditions. In this work, the Quantitative Feedback Theory (QFT) has been applied to synthesis a robust DC-voltage controller to ensure a robust stability and tracking specifications for all operating points. The performance of the designed controller has been compared with the classical PI controller experimentally on laboratory benchmark. The experimental results prove that the proposed controller outperforms the conventional PI controller reducing the overshoot between 26.67% and 82.53% and the response time between 36.36% and 71.33%, reducing by the way the mechanical stress on the PMSG under a turbulent wind speed profile. In addition, the extracted electrical energy using the proposed controller over 90 s of a typical wind speed profile is 1.7015% higher.

Most maximum power point tracking (MPPT) techniques based on sliding-mode control (SMC) use another method such as perturb and observe or incremental conductance (IncCond) to provide current or voltage reference which makes the system more complex. To reduce the complexity and to increase the photovoltaic (PV) array efficiency, a direct control high-performance MPPT based on improved SMC has been investigated in this study. Using two different step sizes can follow the PV peak power at different operating conditions with rapid convergence and greater accuracy. The new SMC-based MPPT designed for boost-type DC/DC converters is compared with a conventional and modified IncCond method, and to a classical SMC method which is very similar to that applied by Chu et al. The proposed PV-MPPT system is tested during a stringent profile of sunshine variation as recommended by the European Norm 50530, by simulation within MATLAB/Simulink TM tools and verified by implementation using a test bench based on DS1104 R&D controller board. The obtained results are satisfactory and demonstrate that the new SMC can track the MPP quickly within 0.003 s and with good accuracy close to 99%.

This article deals with shunt active power filtering for power quality improvement with hysteresis current controllers by two methods of implementation assessed under unfavorable non-linear load and source conditions. Fully digital and simple hybrid hysteresis control strategies are tested based on a numerical integrator proportional DC bus controller combined with phase-locked loop outputs to generate current references. In two cases, reference mains currents are generated to ensure three-phase sinusoidal synchronized waveforms of the mains currents. The experimental evaluation of the robustness control in these two implementation methods is verified using a 10-kVA shunt active power filter in steady state for transitional conditions (step load, switch-on of shunt active power filter) and in the worst case of unbalanced loads (break phase) and source voltages. Several experimental results are presented and discussed to prove the robustness and excellent performance of the proposed simple hybrid t...

The real implementation of sliding mode controllers SMCs to a DC-DC boost converter is a challenge due to the nonminimum phase behavior of these kinds of converters and the SMCs chattering problem. In this paper, new integral sliding mode control laws with linear and proposed nonlinear sliding surfaces are developed to overcome these problems. An experimental comparative study between these SMCs and the classical SMC applied for a DC-DC boost converter is presented.

In this work, nonlinear control of a three-phase shunt active power filter (SAPF) has been studied and compared to classical control based on proportional integral regulator. The control strategy is based on the direct current method using sliding mode control (SMC), where the aim is to regulate the average voltage across the dc bus of the inverter. Details are given for the control algorithm; the controller is comprised of a current loop which utilizes a hysteresis controller to generate the gating signals for the switching devices, and a nonlinear controller based on SMC law which is different from classical laws based on error between reference and measured output voltage of the inverter. Sliding surface applied in this work contains the whole of state variables, in order to ensure full control of the system behavior in the presence of disturbances that affect the supply source, the load parameters or the reference value. The designed controller offers advantage that it can gives the improvement of dynamic and static performances in cases of large disturbances. A comparison of the effects of PI control and SMC on the APF response in steady stat, under line variations, load variations, and different component variations is performed.

In this paper, a new maximum power point tracking MPPT algorithm is proposed to track the global maximum point (GMPP) under partial shading conditions (PSC). The proposed algorithm can track the real GMPP under any PSC patterns and under any weather conditions with improving the tracking speed and reducing the PV output power oscillations at the steady state. The proposed algorithm is simple and easy to implement, because additional sensors or electrical switches are not required to identify the GMPP. The idea of the proposed method is based mainly on the scanning of the PV curve with a variable step of the duty cycle from zero to one. The scan step will be small when the operating point is near the MPP, otherwise, the scan step will be large to skip the regions that do not need to be scanned on the PV curve. Therefore, the scan time will be reduced and the MPPs are accurately detected. Furthermore, the algorithm stores only one MPP during the scanning process, stores only the data position of the greatest maximum power of the PV curve in each sample time T s . Therefore, the execution of the embedded program in the calculator is optimized. In order to maintain the operating point at the GMPP after the scanning is finished a simple proposed sub-program will be used. In this work, a controlled Cuk DC–DC converter was used and connected to a Kyocera KC50T PV panel to verify the performance of the proposed method. Matlab/Simulink™ was used for the simulation studies.

Maximum Power Point Tracking (MPPT) methods are used in photovoltaic (PV) systems to continually maximize the PV array output power, which strongly depends on both solar radiation and cell temperature. The PV power oscillations around the maximum power point (MPP) resulting from the conventional methods and complexity of the non-conventional ones are convincing reasons to look for novel MPPT methods. This paper deals with simple Genetic Algorithms (GAs) based MPPT method in order to improve the convergence, rapidity, and accuracy of the PV system. The proposed method can also efficiently track the global MPP, which is very useful for partial shading. At first, a review of the algorithm is given, followed with many test examples; then, a comparison by means Matlab/Simulink© (R2009b) is conducted between the proposed MPPT and, the popular Perturb and Observe (PO) and Incremental Conductance (IC) techniques. The results show clearly the superiority of the proposed controller. Indeed, with the proposed algorithm, oscillations around the MPP are dramatically minimized, a better stability is observed and increase in the output power efficiency is obtained. All these results are experimentally validated by a test bench developed at LIAS laboratory (Poitiers University, Poitiers, France) using real PV panels and a PV emulator which allows one to define a profile insolation model. In addition, the proposed method permits one to perform the test of linearity between the optimal current I mp (current at maximum power) and the short-circuit current I sc , and between the optimal voltage V mp and open-circuit voltage V oc , so the current and voltage factors can be easily obtained with our algorithm.