This page has only limited features, please log in for full access.
Photovoltaic (PV) power systems are integrated with high penetration levels into the grid. This in turn encourages several modifications for grid codes to sustain grid stability and resilience. Recently, constant power management and regulation is a very common approach, which is used to limit the PV power production. Thus, this article proposes dual-mode power generation algorithm for grid-connected PV systems. The developed system considers the two-stage PV configuration for implementation, where the dual-mode power generation technique is executed within the DC–DC conversion (boost) stage. Most of the techniques adopted for dual-mode power operation employ the conventional perturb and observe method, which is known with unsatisfactory performance at fast-changing atmospheric conditions. Considering this issue, this study suggests a modified maximum power point tracker for power extraction. Furthermore, a new adaptive DC-link controller is developed to improve the DC-link voltage profile at different operating conditions. The adaptive DC-link controller is compared with the traditional PI controller for voltage regulation. The inverter control is accomplished using finite-set model predictive control with two control objectives, namely reference current tracking and switching frequency minimization. The overall control methodology is evaluated at different atmospheric and operating conditions using MATLAB/Simulink software.
Mostafa Ahmed; Ibrahim Harbi; Ralph Kennel; Mohamed Abdelrahem. Dual-Mode Power Operation for Grid-Connected PV Systems with Adaptive DC-link Controller. Arabian Journal for Science and Engineering 2021, 1 -15.
AMA StyleMostafa Ahmed, Ibrahim Harbi, Ralph Kennel, Mohamed Abdelrahem. Dual-Mode Power Operation for Grid-Connected PV Systems with Adaptive DC-link Controller. Arabian Journal for Science and Engineering. 2021; ():1-15.
Chicago/Turabian StyleMostafa Ahmed; Ibrahim Harbi; Ralph Kennel; Mohamed Abdelrahem. 2021. "Dual-Mode Power Operation for Grid-Connected PV Systems with Adaptive DC-link Controller." Arabian Journal for Science and Engineering , no. : 1-15.
Sensorless strategies become very popular in modern control techniques because they increase the system reliability. Besides, they can be used as back-up control in case of sensor failure. In this paper, a DC-link sensorless control approach is developed, which is suited for grid-connected PV systems. The studied system is a two-stage PV scheme, where the DC–DC stage (boost converter) is controlled using an adaptive step-size perturb and observe (P&O) method. Further, the inverter control is accomplished by voltage oriented control (VOC). Generally, the VOC is implemented with two cascaded control loops, namely an outer voltage loop and an inner current loop. However, in this work, the outer loop is avoided and the reference current is generated using a losses model for the system. The losses model accounts for the most significant losses in the PV system. Moreover, particle swarm optimization (PSO) is utilized to compensate for the unmodeled losses. The PSO is executed offline for the purpose of calculation burden reduction. The proposed approach simplifies the cascaded VOC strategy and eliminates the DC-link voltage sensor, which in turn decreases the cost of the system. Finally, the proposed technique is compared with the conventional one at different atmospheric conditions and validated using MATLAB simulation results.
Mostafa Ahmed; Mohamed Abdelrahem; Ahmed Farhan; Ibrahim Harbi; Ralph Kennel. DC-link sensorless control strategy for grid-connected PV systems. Electrical Engineering 2021, 1 -11.
AMA StyleMostafa Ahmed, Mohamed Abdelrahem, Ahmed Farhan, Ibrahim Harbi, Ralph Kennel. DC-link sensorless control strategy for grid-connected PV systems. Electrical Engineering. 2021; ():1-11.
Chicago/Turabian StyleMostafa Ahmed; Mohamed Abdelrahem; Ahmed Farhan; Ibrahim Harbi; Ralph Kennel. 2021. "DC-link sensorless control strategy for grid-connected PV systems." Electrical Engineering , no. : 1-11.
In this article, a modified control structure for a single-stage three phase grid-connected photovoltaic (PV) system is presented. In the proposed system, the maximum power point tracking (MPPT) function is developed using a new adaptive model-based technique, in which the maximum power point (MPP) voltage can be precisely located based on the characteristics of the PV source. By doing so, the drift problem associated with the traditional perturb and observe (P&O) technique can be easily solved. Moreover, the inverter control is accomplished using a predictive dead-beat function, which directly estimates the required reference voltages from the commanded reference currents. Then, the reference voltages are applied to a space vector pulse width modulator (SVPWM) for switching state generation. Furthermore, the proposed inverter control avoids the conventional and known cascaded loop structure of the voltage oriented control (VOC) method by elimination of the outer PI controller, and hence the overall control strategy is simplified. The proposed system is compared with different MPPT techniques, including the conventional P&O method and other techniques intended for drift avoidance. The evaluation of the suggested control methodology depends on various radiation profiles created in MATLAB. The proposed technique succeeds at capturing the maximum available power from the PV source with no drift in comparison with other methods.
Mostafa Ahmed; Mohamed Abdelrahem; Ibrahim Harbi; Ralph Kennel. An Adaptive Model-Based MPPT Technique with Drift-Avoidance for Grid-Connected PV Systems. Energies 2020, 13, 6656 .
AMA StyleMostafa Ahmed, Mohamed Abdelrahem, Ibrahim Harbi, Ralph Kennel. An Adaptive Model-Based MPPT Technique with Drift-Avoidance for Grid-Connected PV Systems. Energies. 2020; 13 (24):6656.
Chicago/Turabian StyleMostafa Ahmed; Mohamed Abdelrahem; Ibrahim Harbi; Ralph Kennel. 2020. "An Adaptive Model-Based MPPT Technique with Drift-Avoidance for Grid-Connected PV Systems." Energies 13, no. 24: 6656.
This paper proposes a finite control set model predictive control (FCS-MPC) with a reduced computational burden for a single-phase grid-connected modified packed U-cell multilevel inverter (MPUC-MLI) with two control objectives: reference current tracking and switching frequency minimization. The considered competitive topology consists of two units with six active switches and two DC sources in each unit, allowing the generation of 49 levels in the output voltage, which is considered a significant reduction in the active and passive components compared to the conventional and recently developed topologies of multilevel inverters (MLIs). This topology has 49 different switching states, which means that 49 predictions of the future current and 49 calculations of the cost function are required for each evaluation of the conventional FCS-MPC. Accordingly, the computational load is heavy. Thus, this paper presents two reduced-complexity FCS-MPC methods to reduce the calculation burden. The first technique reduces the computational load almost to half by computing the reference voltage and dividing the states of the MLI into two sets. Based on the reference voltage polarity, one set is defined and evaluated to specify the optimal state, which has a minimal cost function. However, in the second proposed method, only three states of the 49 states are evaluated each iteration, achieving a significant reduction in the execution time and superior control performance compared to the conventional FCS-MPC. A mathematical analysis is conducted based on the reference voltage value to locate the three vectors under evaluation. In the second part of the paper, the sensitivity to parameter variations for the proposed simplified FCS-MPC is investigated and tackled by employing an extended Kalman filter (EKF). In addition, noise related to variable measurement is filtered in the proposed system with the EKF. The simulation investigation was performed using MATLAB/Simulink to validate the system under different operating conditions.
Ibrahim Harbi; Mohamed Abdelrahem; Mostafa Ahmed; Ralph Kennel. Reduced-Complexity Model Predictive Control with Online Parameter Assessment for a Grid-Connected Single-Phase Multilevel Inverter. Sustainability 2020, 12, 7997 .
AMA StyleIbrahim Harbi, Mohamed Abdelrahem, Mostafa Ahmed, Ralph Kennel. Reduced-Complexity Model Predictive Control with Online Parameter Assessment for a Grid-Connected Single-Phase Multilevel Inverter. Sustainability. 2020; 12 (19):7997.
Chicago/Turabian StyleIbrahim Harbi; Mohamed Abdelrahem; Mostafa Ahmed; Ralph Kennel. 2020. "Reduced-Complexity Model Predictive Control with Online Parameter Assessment for a Grid-Connected Single-Phase Multilevel Inverter." Sustainability 12, no. 19: 7997.
Renewable energy sources, especially photovoltaic (PV) ones, are gaining more and more interest due to the predicted lack of conventional sources over the coming years. That shortage is not the only concern, as environmental issues add to this concern also. Thus, this study proposes two-stage PV grid connected system, which is supported with extended Kalman filter (EKF) for parameter estimation. In the first stage, maximum power point tracking (MPPT) for the boost converter is accomplished using new MPPT method in which the switching state of the converter is directly generated after the measurement stage, so it is called direct switching MPPT technique. This technique is compared with the conventional finite control set model predictive control (FCS-MPC) method, where the design of the cost function is based on minimizing the error between the reference and the actual current. The reference current is obtained by employing perturb and observe (P&O) method. In the second stage, the two-level inverter is controlled by means of model predictive control (MPC) with reduced computation burden. Further, to overcome the parameter variations, which is a very common problem in MPC applications, an extended Kalman filter is utilized to eliminate the control algorithm’s dependency on the parameters by providing an efficient estimation. After the inverter, an RL filter is inserted to guarantee the quality of the currents injected into the grid. Finally, the system is validated using Matlab under different operating conditions of atmospheric variation and parameter changes.
Mostafa Ahmed; Mohamed Abdelrahem; Ralph Kennel. Highly Efficient and Robust Grid Connected Photovoltaic System Based Model Predictive Control with Kalman Filtering Capability. Sustainability 2020, 12, 4542 .
AMA StyleMostafa Ahmed, Mohamed Abdelrahem, Ralph Kennel. Highly Efficient and Robust Grid Connected Photovoltaic System Based Model Predictive Control with Kalman Filtering Capability. Sustainability. 2020; 12 (11):4542.
Chicago/Turabian StyleMostafa Ahmed; Mohamed Abdelrahem; Ralph Kennel. 2020. "Highly Efficient and Robust Grid Connected Photovoltaic System Based Model Predictive Control with Kalman Filtering Capability." Sustainability 12, no. 11: 4542.