Mostafa Ahmed - Academia.edu (original) (raw)

Papers by Mostafa Ahmed

Research paper thumbnail of Sensorless Predictive Direct Power Control with On-line Inductance Estimation for Grid-connected PV Applications

In this study, predictive direct power control technique is adopted for two-stage grid-connected ... more In this study, predictive direct power control technique is adopted for two-stage grid-connected PV systems. The system consists of a photovoltaic (PV) source, boost converter, two-level inverter, and filter for the grid connection. The proposed control strategy eliminates all the grid voltage sensors by employing an extended Kalman filter (EKF). To enhance the robustness of the system against parameters variation, the system's inductance is included in the estimation process. Furthermore, the calculation burden associated with the conventional predictive direct power control technique is reduced using a simplified control methodology. The maximum power point tracking (MPPT) operation is accomplished using the perturb and observe (P&O) method. The proposed control algorithm is validated via simulation results under different atmospheric and operating conditions.

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Research paper thumbnail of Predictive Model-based Maximum Power Point Tracking Technique for PV Applications with Reduced Sensor Count

Maximum power point tracking (MPPT) is an essential control for any photovoltaic (PV) system. Thi... more Maximum power point tracking (MPPT) is an essential control for any photovoltaic (PV) system. This paper develops a new predictive technique to extract the maximum power from the PV source. The system under study is composed of a PV source followed by a boost DC-DC converter to interface the resistive load. The proposed MPPT strategy combines the idea of the well-known model predictive control (MPC) with the model of the PV source. By doing so, the switching state can be directly generated without the need of the discrete-time model's derivation as the case in the conventional finite set model predictive control (FS-MPC). Furthermore, the developed scheme decreases the number of required sensors for MPPT. Finally, the superiority of the proposed technique is confirmed, in comparison with the conventional MPC, via simulation results conducted in Matlab platform.

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Research paper thumbnail of Dual-Mode Power Operation for Grid-Connected PV Systems with Adaptive DC-link Controller

Photovoltaic (PV) power systems are integrated with high penetration levels into the grid. This i... more 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.

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Research paper thumbnail of Highly Efficient and Robust Grid Connected Photovoltaic System Based Model Predictive Control with Kalman Filtering Capability

Sustainability

Renewable energy sources, especially photovoltaic (PV) ones, are gaining more and more interest d... more 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 ...

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Research paper thumbnail of Direct Switching Maximum Power Point Tracking Technique for PV Applications

Maximum power point tracking (MPPT) control technique is a necessity in any photovoltaic (PV) sys... more Maximum power point tracking (MPPT) control technique is a necessity in any photovoltaic (PV) system because of the low energy efficiency of the PV panels. This maximizes the harnessed energy from the PV source at various atmospheric conditions. Further, it guarantees to extract the maximum available power during the variable profile of the atmosphere. This paper focuses on MPPT and proposes a new technique, which is inspired from the model predictive control (MPC) principle. In the conventional MPC method, the switching state is obtained based on the error between the predicted control parameter and its reference value coming from an outer loop. The outer loop is normally perturb and observe (P&O) or incremental conductance method (INC). However, in the proposed method, the switching state is obtained directly from the measured values of current and voltage. The proposed methodology is validated using Matlab/Simulink platform and compared with the conventional MPC algorithm at different operating conditions.

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Research paper thumbnail of Evaluation of Predictive Direct Current and Direct Power Control for Grid-connected PV Systems

Predictive control provides many advantages over conventional control techniques. Thus, in this p... more Predictive control provides many advantages over conventional control techniques. Thus, in this paper, a comparative study between the predictive direct current control (PDCC) and predictive direct power control (PDPC) is investigated. The study focuses on applying these control strategies with renewable energy systems (RESs), especially photovoltaic (PV) ones. RESs are integrated with high penetration into the grid, and they must satisfy certain regulations to sustain the grid stability. The studied system consists of a PV array and boost converter followed by two-level inverter to enable the grid connection, where the maximum power point tracking (MPPT) function is accomplished by an adaptive step-size method. The adopted technique here is perturb and observe (P&O) method. The control of active and reactive power is performed using PDPC and PDCC for the purpose of evaluation in terms of power quality, total harmonic distortion (THD), average switching frequency, implementation, calculation burden, etc. The system is validated by simulation results via Matlab platform under various operating conditions.

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Research paper thumbnail of A Robust Maximum Power Point Tracking Based Model Predictive Control and Extended Kalman Filter for PV Systems

Maximum power point tracking (MPPT) is a very important issue in any photovoltaic (PV) system. Th... more Maximum power point tracking (MPPT) is a very important issue in any photovoltaic (PV) system. This paper presents an MPPT using finite control set model predictive control (FCS-MPC), where the system under study is composed of a PV module, boost converter, and resistive load. The proposed MPPT technique not only reduces the required sensors by one but also eliminates the dependency of the control system on the load by using an extended Kalman filter (EKF), which greatly enhances the robustness and reliability of the MPPT based FCS-MPC. Finally, the proposed MPPT technique is validated by simulation results under different radiation conditions and load variation.

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Research paper thumbnail of Maximum Power Point Tracking Based Model Predictive Control and Extended Kalman Filter Using Single Voltage Sensor for PV Systems

The variability of photovoltaic (PV) energy because of atmospheric conditions dependency necessit... more The variability of photovoltaic (PV) energy because of atmospheric conditions dependency necessitates employing a maximum power point tracking (MPPT) technique in the installed PV systems. So in this paper, finite control set model predictive control (FCS-MPC) is used to extract the maximum power from the PV source using a boost converter as interfacing circuit. The proposed technique combines FCS-MPC with an extended Kalman filter (EKF) to reduce the number of required sensors. The EKF is used to estimate both of the PV current and the capacitor voltage. This eliminates two sensors circuits from the PV system, which decreases the system cost. The proposed technique is validated by simulation results under different operating conditions.

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Research paper thumbnail of An Enhanced Maximum Power Point Tracking Based Finite-Control-Set Model Predictive Control for PV Systems

This paper presents an enhanced maximum power point tracking (MPPT) technique based on the finite... more This paper presents an enhanced maximum power point tracking (MPPT) technique based on the finite-control-set model predictive control (FCS-MPC) for photovoltaic (PV) applications. The system under study is composed of a PV source and resistive load, while a boost converter is used as an interfacing circuit between the PV generator and the resistive load. To control the converter, a current-based cost function is applied to get the optimal switching state. Further, the previous switching state is included in the cost function design to enhance the MPPT performance. For investigation, the proposed algorithm is compared with perturb and observe (P&O) method. Additionally, comparison between the proposed technique and the conventional FCS-MPC is performed at different atmospheric conditions.

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Research paper thumbnail of DC-link sensorless control strategy for grid-connected PV systems

Sensorless strategies become very popular in modern control techniques because they increase the ... more Sensorless strategies become very popular in modern control techniques because they increase the system reliability. Besides, they can be used as backup 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.

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Research paper thumbnail of An Adaptive Model-Based MPPT Technique with Drift-Avoidance for Grid-Connected PV Systems

In this article, a modified control structure for a single-stage three phase grid-connected photo... more 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.

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Research paper thumbnail of Highly Efficient and Robust Grid Connected Photovoltaic System Based Model Predictive Control with Kalman Filtering Capability

Renewable energy sources, especially photovoltaic (PV) ones, are gaining more and more interest d... more 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.

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Research paper thumbnail of Performance of Photovoltaic Water Pumping System Under Different MPPT Algorithms

This paper proposes an accurate model for DC photovoltaic pumping system. The system model begins... more This paper proposes an accurate model for DC photovoltaic pumping system. The system model begins with the photovoltaic module (PVM).The boost converter is used as an interfacing circuitry between the PVM and the motor. The DC motor is a permanent magnet (PM) type which coupled with a centrifugal pump. The boost converter is controlled using three different maximum power point tracking (MPPT) algorithms to extract the available power under changing conditions of radiation. Optimal duty cycle required to drive the boost converter is obtained using graphical steady state analysis. Further the system is built using Matlab/Simulink and tested with different atmospheric conditions. Index term-PV, pumping system, dc-dc boost converter and MPPT.

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Research paper thumbnail of Optimal Photovoltaic Water Pumping System Performance under different Operating conditions

This paper presents dc photovoltaic pumping system. The system consists of photovoltaic (PV) gene... more This paper presents dc photovoltaic pumping system. The system consists of photovoltaic (PV) generator, boost converter and permanent magnet (PM) dc motor-pump set. Each part of the system is modelled. Photovoltaic generator parameters are extracted based on data-sheet parameters. Boost converter is designed to operate in continuous conduction mode (CCM) and controlled using incremental conductance (IC) algorithm for maximum power point tracking (MPPT).The system is simulated using Matlab/Simulink .The proposed system is studied under direct coupling and maximum power point tracking conditions. The results show a very good performance MPPT compared with direct coupling. The system is tested under varying conditions of temperature and radiation.

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Research paper thumbnail of Modeling and Maximum Power Point Tracking with Ripple control of Photovoltaic System

This paper presents parameters determination of photovoltaic (PV) module based on data-sheet para... more This paper presents parameters determination of photovoltaic (PV) module based on data-sheet parameters using Newton-Raphson iterative method. The characteristic of photovoltaic module are drawn based on the extracted parameters. Simulation and maximum power point tracking (MPPT) are developed using Matlab/Simulink. Incremental conductance (INC) method for MPPT is used to control a dc-dc boost converter with resistive load. Parameters of boost converter are designed to operate in continuous conduction mode .State-space averaging technique is used to control stand-alone PV module and obtain inductance value for certain amount of ripple in boost inductor current at different temperature and irradiance conditions. Index term-photovoltaic module, MPPT, INC algorithm and state-space averaging

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Research paper thumbnail of Sensorless Predictive Direct Power Control with On-line Inductance Estimation for Grid-connected PV Applications

In this study, predictive direct power control technique is adopted for two-stage grid-connected ... more In this study, predictive direct power control technique is adopted for two-stage grid-connected PV systems. The system consists of a photovoltaic (PV) source, boost converter, two-level inverter, and filter for the grid connection. The proposed control strategy eliminates all the grid voltage sensors by employing an extended Kalman filter (EKF). To enhance the robustness of the system against parameters variation, the system's inductance is included in the estimation process. Furthermore, the calculation burden associated with the conventional predictive direct power control technique is reduced using a simplified control methodology. The maximum power point tracking (MPPT) operation is accomplished using the perturb and observe (P&O) method. The proposed control algorithm is validated via simulation results under different atmospheric and operating conditions.

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Research paper thumbnail of Predictive Model-based Maximum Power Point Tracking Technique for PV Applications with Reduced Sensor Count

Maximum power point tracking (MPPT) is an essential control for any photovoltaic (PV) system. Thi... more Maximum power point tracking (MPPT) is an essential control for any photovoltaic (PV) system. This paper develops a new predictive technique to extract the maximum power from the PV source. The system under study is composed of a PV source followed by a boost DC-DC converter to interface the resistive load. The proposed MPPT strategy combines the idea of the well-known model predictive control (MPC) with the model of the PV source. By doing so, the switching state can be directly generated without the need of the discrete-time model's derivation as the case in the conventional finite set model predictive control (FS-MPC). Furthermore, the developed scheme decreases the number of required sensors for MPPT. Finally, the superiority of the proposed technique is confirmed, in comparison with the conventional MPC, via simulation results conducted in Matlab platform.

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Research paper thumbnail of Dual-Mode Power Operation for Grid-Connected PV Systems with Adaptive DC-link Controller

Photovoltaic (PV) power systems are integrated with high penetration levels into the grid. This i... more 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.

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Research paper thumbnail of Highly Efficient and Robust Grid Connected Photovoltaic System Based Model Predictive Control with Kalman Filtering Capability

Sustainability

Renewable energy sources, especially photovoltaic (PV) ones, are gaining more and more interest d... more 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 ...

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Research paper thumbnail of Direct Switching Maximum Power Point Tracking Technique for PV Applications

Maximum power point tracking (MPPT) control technique is a necessity in any photovoltaic (PV) sys... more Maximum power point tracking (MPPT) control technique is a necessity in any photovoltaic (PV) system because of the low energy efficiency of the PV panels. This maximizes the harnessed energy from the PV source at various atmospheric conditions. Further, it guarantees to extract the maximum available power during the variable profile of the atmosphere. This paper focuses on MPPT and proposes a new technique, which is inspired from the model predictive control (MPC) principle. In the conventional MPC method, the switching state is obtained based on the error between the predicted control parameter and its reference value coming from an outer loop. The outer loop is normally perturb and observe (P&O) or incremental conductance method (INC). However, in the proposed method, the switching state is obtained directly from the measured values of current and voltage. The proposed methodology is validated using Matlab/Simulink platform and compared with the conventional MPC algorithm at different operating conditions.

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Research paper thumbnail of Evaluation of Predictive Direct Current and Direct Power Control for Grid-connected PV Systems

Predictive control provides many advantages over conventional control techniques. Thus, in this p... more Predictive control provides many advantages over conventional control techniques. Thus, in this paper, a comparative study between the predictive direct current control (PDCC) and predictive direct power control (PDPC) is investigated. The study focuses on applying these control strategies with renewable energy systems (RESs), especially photovoltaic (PV) ones. RESs are integrated with high penetration into the grid, and they must satisfy certain regulations to sustain the grid stability. The studied system consists of a PV array and boost converter followed by two-level inverter to enable the grid connection, where the maximum power point tracking (MPPT) function is accomplished by an adaptive step-size method. The adopted technique here is perturb and observe (P&O) method. The control of active and reactive power is performed using PDPC and PDCC for the purpose of evaluation in terms of power quality, total harmonic distortion (THD), average switching frequency, implementation, calculation burden, etc. The system is validated by simulation results via Matlab platform under various operating conditions.

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Research paper thumbnail of A Robust Maximum Power Point Tracking Based Model Predictive Control and Extended Kalman Filter for PV Systems

Maximum power point tracking (MPPT) is a very important issue in any photovoltaic (PV) system. Th... more Maximum power point tracking (MPPT) is a very important issue in any photovoltaic (PV) system. This paper presents an MPPT using finite control set model predictive control (FCS-MPC), where the system under study is composed of a PV module, boost converter, and resistive load. The proposed MPPT technique not only reduces the required sensors by one but also eliminates the dependency of the control system on the load by using an extended Kalman filter (EKF), which greatly enhances the robustness and reliability of the MPPT based FCS-MPC. Finally, the proposed MPPT technique is validated by simulation results under different radiation conditions and load variation.

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Research paper thumbnail of Maximum Power Point Tracking Based Model Predictive Control and Extended Kalman Filter Using Single Voltage Sensor for PV Systems

The variability of photovoltaic (PV) energy because of atmospheric conditions dependency necessit... more The variability of photovoltaic (PV) energy because of atmospheric conditions dependency necessitates employing a maximum power point tracking (MPPT) technique in the installed PV systems. So in this paper, finite control set model predictive control (FCS-MPC) is used to extract the maximum power from the PV source using a boost converter as interfacing circuit. The proposed technique combines FCS-MPC with an extended Kalman filter (EKF) to reduce the number of required sensors. The EKF is used to estimate both of the PV current and the capacitor voltage. This eliminates two sensors circuits from the PV system, which decreases the system cost. The proposed technique is validated by simulation results under different operating conditions.

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Research paper thumbnail of An Enhanced Maximum Power Point Tracking Based Finite-Control-Set Model Predictive Control for PV Systems

This paper presents an enhanced maximum power point tracking (MPPT) technique based on the finite... more This paper presents an enhanced maximum power point tracking (MPPT) technique based on the finite-control-set model predictive control (FCS-MPC) for photovoltaic (PV) applications. The system under study is composed of a PV source and resistive load, while a boost converter is used as an interfacing circuit between the PV generator and the resistive load. To control the converter, a current-based cost function is applied to get the optimal switching state. Further, the previous switching state is included in the cost function design to enhance the MPPT performance. For investigation, the proposed algorithm is compared with perturb and observe (P&O) method. Additionally, comparison between the proposed technique and the conventional FCS-MPC is performed at different atmospheric conditions.

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Research paper thumbnail of DC-link sensorless control strategy for grid-connected PV systems

Sensorless strategies become very popular in modern control techniques because they increase the ... more Sensorless strategies become very popular in modern control techniques because they increase the system reliability. Besides, they can be used as backup 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.

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Research paper thumbnail of An Adaptive Model-Based MPPT Technique with Drift-Avoidance for Grid-Connected PV Systems

In this article, a modified control structure for a single-stage three phase grid-connected photo... more 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.

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Research paper thumbnail of Highly Efficient and Robust Grid Connected Photovoltaic System Based Model Predictive Control with Kalman Filtering Capability

Renewable energy sources, especially photovoltaic (PV) ones, are gaining more and more interest d... more 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.

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Research paper thumbnail of Performance of Photovoltaic Water Pumping System Under Different MPPT Algorithms

This paper proposes an accurate model for DC photovoltaic pumping system. The system model begins... more This paper proposes an accurate model for DC photovoltaic pumping system. The system model begins with the photovoltaic module (PVM).The boost converter is used as an interfacing circuitry between the PVM and the motor. The DC motor is a permanent magnet (PM) type which coupled with a centrifugal pump. The boost converter is controlled using three different maximum power point tracking (MPPT) algorithms to extract the available power under changing conditions of radiation. Optimal duty cycle required to drive the boost converter is obtained using graphical steady state analysis. Further the system is built using Matlab/Simulink and tested with different atmospheric conditions. Index term-PV, pumping system, dc-dc boost converter and MPPT.

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Research paper thumbnail of Optimal Photovoltaic Water Pumping System Performance under different Operating conditions

This paper presents dc photovoltaic pumping system. The system consists of photovoltaic (PV) gene... more This paper presents dc photovoltaic pumping system. The system consists of photovoltaic (PV) generator, boost converter and permanent magnet (PM) dc motor-pump set. Each part of the system is modelled. Photovoltaic generator parameters are extracted based on data-sheet parameters. Boost converter is designed to operate in continuous conduction mode (CCM) and controlled using incremental conductance (IC) algorithm for maximum power point tracking (MPPT).The system is simulated using Matlab/Simulink .The proposed system is studied under direct coupling and maximum power point tracking conditions. The results show a very good performance MPPT compared with direct coupling. The system is tested under varying conditions of temperature and radiation.

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Research paper thumbnail of Modeling and Maximum Power Point Tracking with Ripple control of Photovoltaic System

This paper presents parameters determination of photovoltaic (PV) module based on data-sheet para... more This paper presents parameters determination of photovoltaic (PV) module based on data-sheet parameters using Newton-Raphson iterative method. The characteristic of photovoltaic module are drawn based on the extracted parameters. Simulation and maximum power point tracking (MPPT) are developed using Matlab/Simulink. Incremental conductance (INC) method for MPPT is used to control a dc-dc boost converter with resistive load. Parameters of boost converter are designed to operate in continuous conduction mode .State-space averaging technique is used to control stand-alone PV module and obtain inductance value for certain amount of ripple in boost inductor current at different temperature and irradiance conditions. Index term-photovoltaic module, MPPT, INC algorithm and state-space averaging

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