Abderezak Lashab | Aalborg University (original) (raw)

Papers by Abderezak Lashab

Research paper thumbnail of Model-Free Predictive Control for Improved Performance and Robustness of Three-Phase Quasi Z-Source Inverters

IEEE Access, 2024

This paper suggests a novel Model-Free Predictive Control (MFPC) approach for three-phase quasi Z... more This paper suggests a novel Model-Free Predictive Control (MFPC) approach for three-phase quasi Z-source inverters (qZSI). While Model Predictive Control (MPC) is popular for qZSI due to its ease of use and performance, it suffers from sensitivity to parameter mismatch. The proposed MFPC overcomes this limitation by relying on an ultra-local model (ULM), eliminating the need for precise parameter matching. This approach establishes a comprehensive mathematical model for key qZSI control variables, including load current, inductor current, and capacitor voltage. Additionally, a unique method seamlessly integrates shoot-through status into the MFPC framework without compromising qZSI operation. Simulation results across various operating conditions demonstrate how much better the suggested MFPC is than the traditional MPC, especially under parameter mismatch scenarios. Notably, the MFPC achieves a significant improvement, exceeding a 37% reduction in total harmonic distortion (THD). Furthermore, the practicality of the proposed MFPC strategy is validated through hardware-in-the-loop (HIL) testing using a C2000TM microcontroller. INDEX TERMS Ultra-local model, model-free control, model predictive control, parametric uncertainties, quasi Z-source inverter, total harmonic distortion.

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Research paper thumbnail of An Improved ω-φ Droop Control for Cascaded PV-ES System in Islanded Mode

IEEE Transactions on Sustainable Energy, 2024

The cascaded H-bridge structure has raised more and more attention in the field of photovoltaic (... more The cascaded H-bridge structure has raised more and more attention in the field of photovoltaic (PV) power generation. This paper presents an improved ω-φ droop control method for the islanded cascaded photovoltaic-energy storage (PVES) system. The PV units mainly focus on outputting active power with unity power factor characteristic while the ES unit is responsible for the total output voltage regulation, frequency restoration, and power fluctuation suppression. With the proposed method, the string voltage can be regulated by the ES unit. Further, both the frequency synchronization with no steady state error and the cooperation between ES and PVs are realized automatically with only ES control requires PCC information. Therefore, the communication dependence is reduced which improves the system reliability. In addition, stability analysis and simulation results are provided to verify the effectiveness of the proposed controller.

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Research paper thumbnail of Topologies and Control in Photovoltaic Systems with and without Storage

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Research paper thumbnail of Lunar Habitat Wastewater Subsystem Power and Water Management

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Research paper thumbnail of On Improved PSO and Neural Network P&O Methods for PV System under Shading and Various Atmospheric Conditions

Energies, Oct 17, 2022

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Research paper thumbnail of A Deep GMDH Neural-Network-Based Robust Fault Detection Method for Active Distribution Networks

Energies

The increasing penetration of distributed generation (DG) to power distribution networks mainly i... more The increasing penetration of distributed generation (DG) to power distribution networks mainly induces weaknesses in the sensitivity and selectivity of protection systems. In this manner, conventional protection systems often fail to protect active distribution networks (ADN) in the case of short-circuit faults. To overcome these challenges, the accurate detection of faults in a reasonable fraction of time appears as a critical issue in distribution networks. Machine learning techniques are capable of generating efficient analytical expressions that can be strong candidates in terms of reliable and robust fault detection for several operating scenarios of ADNs. This paper proposes a deep group method of data handling (GMDH) neural network based on a non-pilot protection method for the protection of an ADN. The developed method is independent of the DG capacity and achieves accurate fault detection under load variations, disturbances, and different high-impedance faults (HIFs). To v...

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Research paper thumbnail of Nonlinear adaptive controller design to stabilize constant power loads connected-DC microgrid using disturbance accommodation technique

Electrical Engineering

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Research paper thumbnail of Optimized Modulation Scheme for Four-Leg Quasi Z-Source Inverter: Reducing Power Loss and Improving Output Quality

IEEE Access

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Research paper thumbnail of A Data-Driven Approach for Generator Load Prediction in Shipboard Microgrid: The Chemical Tanker Case Study

Energies

Energy efficiency and operational safety practices on ships have gained more importance due to th... more Energy efficiency and operational safety practices on ships have gained more importance due to the rules set by the International Maritime Organization in recent years. While approximately 70% of the fuel consumed on a commercial ship is utilized for the propulsion load, a significant portion of the remaining fuel is consumed by the auxiliary generators responsible for the ship’s onboard load. It is crucial to comprehend the impact of the electrical load on the ship’s generators, as it significantly assists maritime operators in strategic energy planning to minimize the chance of unexpected electrical breakdowns during operation. However, an appropriate handling mechanism is required when there are massive datasets and varied input data involved. Thus, this study implements data-driven approaches to estimate the load of a chemical tanker ship’s generator using a 1000-day real dataset. Two case studies were performed, namely, single load prediction for each generator and total load p...

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Research paper thumbnail of Low Computational Burden Predictive Direct Power Control of Quasi Z-Source Inverter for Grid-Tied PV Applications

Sustainability

This paper proposes a simplified predictive direct power control for the grid-tied quasi Z-source... more This paper proposes a simplified predictive direct power control for the grid-tied quasi Z-source inverter. The proposed control implements a model predictive control structure to achieve the maximum obtainable power from the collected PV source. The power delivered to the grid is managed to compensate for the reactive power and, as needed, to ensure the grid’s stability. A predictive power model for a quasi Z-source inverter is developed in which the proposed control can operate with a fixed switching frequency without a weighting factor. The simplified space vector modulation uses the three appropriate switching vectors that are selected and applied using precalculated switching times during each switching period, in which the required switching vectors are determined only from one sector in the space vector diagram, taking all of the information of the other sectors, which leads to reducing the computational burden. Simulation results and comparative study are used to confirm the...

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Research paper thumbnail of Nonlinear Adaptive Controller Design to Stabilize Constant Power Loads connected-DC Microgrid using Disturbance Accommodation Technique

The DC microgrid is comprised of a considerable number of electronically regulated power electron... more The DC microgrid is comprised of a considerable number of electronically regulated power electronic loads that act as constant power loads (CPLs). These power electronic devices have a high bandwidth regulation capability as well as a high-power conversion efficiency. Specifically, the high bandwidth control for the output of the converter load, when paired with the system's filtering components, results in negatively damped oscillations. These features, even if needed, may cause system instability and, finally, system failure if not avoided. To achieve effective power flow control in a DC microgrid, it is crucial to eliminate the undesired behaviour of the CPLs. The control objective requires the assessment of the power for uncertain loads, which vary with time. This paper proposes an adaptive controller linked to a cubature Kalman filter(CKF) for a DC microgrid with time-varying non-ideal CPLs. The controller utilises the neuro-fuzzy inference system(ANFIS) to make the design ...

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Research paper thumbnail of A Comparative Study of MPPTs for Nano-Satellite Microgrid Applications under Spinning Flight Scenarios

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society

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Research paper thumbnail of Novel V2G regulation scheme using Dual-PSS for PV islanded microgrid

Applied Energy

The incorporation of electric vehicles (EVs) into residential/industrial microgrids (MGs) present... more The incorporation of electric vehicles (EVs) into residential/industrial microgrids (MGs) presents some limitations such as fluctuations in voltage, frequency, and lack of power supply. According to the literature, the control methods for vehicle-to-grid (V2G) in MGs are insufficiently coordinated for charging and regulation, limited by narrow charging control constraints, complex, and computationally demanding. Moreover, the power system stabilizer (PSS) is employed only in the generation side. To this regard, a PSS is proposed in this paper along with the proportional integral-derivative (PID) controller, which is tuned adaptively using Harris hawks optimizer (HHO) for frequency, voltage, and power-sharing regulations through the parked EVs. The considered islanded MG is consisting of a diesel generator as a backup generation source, dealing with the intermittent nature of the solar photovoltaic (PV) plant and residential load. It also includes an EV aggregator. In case of partial shading of the solar PV farm and triggering the load demand, the proposed control strategy provides a complementary signal to promote short response time during transients, boost the transient stability performance, and offer damping characteristics adequate for V2G regulation with the islanded residential MG. To examine the efficacy of the proposed scheme, a detailed simulation model using Matlab/Simulink was built. The final findings show that the proposed direct adaptive PID-PSS controller gives significantly enhanced voltage and frequency with spinning reserve compared to the conventional PI-controller both considering the inclusion of V2G on the MG regulation side and conventional controller without V2G and PSS on the regulation side. Also, it can provide power flow in a bi-directional way during the partial shading contingency that the residential MG may expe-rience within 24 hr.

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Research paper thumbnail of A Decentralized Master-slave Method for Three-Phase Cascaded H-bridge System

IEEE Journal of Emerging and Selected Topics in Industrial Electronics, 2023

For the cascaded H-bridge system, the existing decentralized methods are mainly focused on single... more For the cascaded H-bridge system, the existing decentralized methods are mainly focused on single-phase systems. Designing a decentralized method for the three-phase cascaded H-bridge system is more challenging, particularly, for achieving phase-to-phase frequency synchronization and three-phase voltage balance without real-time communication among each distributed generation (DG). To achieve this, this paper proposes a decentralized master-slave method for three-phase cascaded H-bridge systems, where no communication is required for each local control unit of DGs. The overall control is divided into two parts. One part is for the master DG to realize phase synchronization among Phase-A, B, and C, which is designed by modifying the power factor angle through droop control. The other part is for slave DGs to achieve frequency synchronization of the modules in each phase, which adopts the power factor angle droop control. Small signal stability analysis based on fast and slow time scale separation is carried out for the proposed method. Last, the Control-hardware-in-loop (CHIL) tests and experimental results prove the effectiveness of the proposed method.

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Research paper thumbnail of Optimized Modulation Scheme for Four-Leg Quasi Z-Source Inverter: Reducing Power Loss and Improving Output Quality

IEEE Access, 2023

This study introduces a new three-dimensional space vector modulation technique for a four-leg qu... more This study introduces a new three-dimensional space vector modulation technique for a four-leg quasi Z-source inverter (4L-qZSI) integrating a qZSN and a two-level four-leg inverter. The proposed method encompasses three variants, namely 3DZSVM2, 3DZSVM4, and 3DZSVM8, designed to enhance steady-state operations and harmonic distortions for 4L-qZSI. One of the main contributions of this research is the establishment of a new modulation technique for the 4L-qZSI. The proposed method amalgamates the benefits of SVMs in both abc and αβγ coordinates. The design processes of the 3DZSVM algorithm are carried out in the newly proposed ρσ τ coordinates, while the space vector diagram (SVD) of the 4L-qZSI is utilized in the αβγ location. The proposed algorithm is applied in a single sector, optimizing time interval calculations and pulse creation without requiring trigonometric functions. Extensive simulation studies were conducted to validate the performance of the introduced modulation scheme for the 4L-qZSI. The simulation results show excellent steady-state performance and benefit over the conventional space vector modulation with zero sequences (CZPWM), including a power loss reduction of 50% and a 50% decrease in the THD of the output voltage. In addition, applying this technique results in enhanced output current quality, reduced power loss by 40%, and decreased inductive current ripple by 50% under unbalanced load conditions. Furthermore, the proposed 3DZSVM control strategy for 4L-qZSI is experimentally verified using the TMS320F28379D kit based on the Hardware-in-the-Loop (HIL) simulator. This demonstrates the practicality and effective performance of the suggested control strategy under unbalanced load conditions.

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Research paper thumbnail of A Deep GMDH Neural-Network-Based Robust Fault Detection Method for Active Distribution Networks

Energies, 2023

The increasing penetration of distributed generation (DG) to power distribution networks mainly i... more The increasing penetration of distributed generation (DG) to power distribution networks mainly induces weaknesses in the sensitivity and selectivity of protection systems. In this manner, conventional protection systems often fail to protect active distribution networks (ADN) in the case of short-circuit faults. To overcome these challenges, the accurate detection of faults in a reasonable fraction of time appears as a critical issue in distribution networks. Machine learning techniques are capable of generating efficient analytical expressions that can be strong candidates in terms of reliable and robust fault detection for several operating scenarios of ADNs. This paper proposes a deep group method of data handling (GMDH) neural network based on a non-pilot protection method for the protection of an ADN. The developed method is independent of the DG capacity and achieves accurate fault detection under load variations, disturbances, and different high-impedance faults (HIFs). To verify the improvements, a test system based on a real distribution network that includes three generators with a capacity of 6 MW is utilized. The extensive simulations of the power network are performed using DIgSILENT Power Factory and MATLAB software. The obtained results reveal that a mean absolute percentage error (MAPE) of 3.51% for the GMDH-network-based protection system is accomplished thanks to formulation via optimized algorithms, without requiring the utilization of any feature selection techniques. The proposed method has a high-speed operation of around 20 ms for the detection of faults, while the conventional OC relay performance is in the blinding mode in the worst situations for faults with HIFs.

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Research paper thumbnail of A Data-Driven Approach for Generator Load Prediction in Shipboard Microgrid: The Chemical Tanker Case Study

Energies, 2023

Energy efficiency and operational safety practices on ships have gained more importance due to th... more Energy efficiency and operational safety practices on ships have gained more importance due to the rules set by the International Maritime Organization in recent years. While approximately 70% of the fuel consumed on a commercial ship is utilized for the propulsion load, a significant portion of the remaining fuel is consumed by the auxiliary generators responsible for the ship’s onboard load. It is crucial to comprehend the impact of the electrical load on the ship’s generators, as it significantly assists maritime operators in strategic energy planning to minimize the chance of unexpected electrical breakdowns during operation. However, an appropriate handling mechanism is required when there are massive datasets and varied input data involved. Thus, this study implements data-driven approaches to estimate the load of a chemical tanker ship’s generator using a 1000-day real dataset. Two case studies were performed, namely, single load prediction for each generator and total load prediction for all generators. The prediction results show that for the single generator load prediction of DG1, DG2, and DG3, the decision tree model encountered the least errors for MAE (0.2364, 0.1306, and 0.1532), RMSE (0.2455, 0.2069, and 0.2182), and MAPE (17.493, 5.1139, and 7.7481). In contrast, the deep neural network outperforms all other prediction models in the case of total generation prediction, with values of 1.0866, 2.6049, and 14.728 for MAE, RMSE, and MAPE, respectively.

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Research paper thumbnail of Optimal Sizing and Siting of PV and Battery Based Space Microgrids Near the Moon’s Shackleton Crater

IEEE Access

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Research paper thumbnail of Low Computational Burden Predictive Direct Power Control of Quasi Z-Source Inverter for Grid-Tied PV Applications

Sustainability, 2023

This paper proposes a simplified predictive direct power control for the grid-tied quasi Z-source... more This paper proposes a simplified predictive direct power control for the grid-tied quasi Z-source inverter. The proposed control implements a model predictive control structure to achieve the maximum obtainable power from the collected PV source. The power delivered to the grid is managed to compensate for the reactive power and, as needed, to ensure the grid’s stability. A predictive power model for a quasi Z-source inverter is developed in which the proposed control can operate with a fixed switching frequency without a weighting factor. The simplified space vector modulation uses the three appropriate switching vectors that are selected and applied using precalculated switching times during each switching period, in which the required switching vectors are determined only from one sector in the space vector diagram, taking all of the information of the other sectors, which leads to reducing the computational burden. Simulation results and comparative study are used to confirm the proposed control performance for the grid-tied quasi Z-source inverter capable of tracking and generating the maximum power from PV with fast-tracking dynamics, ensuring the ac voltage desired, and better tracking of the active and reactive power reference with the lowest power ripple. The grid current harmonics were tested and conformed to the IEEE-519 standard. Additionally, the proposed simplified PDPC is experimentally validated using the Hardware-in-the-Loop emulator and the C2000TM-microcontroller-LaunchPadXL TMS320F28379D kit, establishing the usability and good result of our proposed control approach in terms of requirements.

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Research paper thumbnail of Optimal Sizing and Siting of PV and Battery based Space Microgrids near the Moon's Shackleton Crater

IEEE Access, 2023

Space mission cost and feasibility depend mainly on the size and mass of the payload. This paper ... more Space mission cost and feasibility depend mainly on the size and mass of the payload. This paper investigates the optimal photovoltaic (PV) array and battery size and mass for an islanded PV-battery powered space microgrid (MG) at the lunar south pole. The PV arrays are considered to be installed on top of towers to increase solar energy harvesting. Considering the dependency of the generated power from PV arrays on the tower height, different tower heights of 10, 50, and 100 m are investigated. The paper presents the methodology to estimate the available power from the PV system using the information of illumination time-series at the location of potential sites with different tower heights. Besides, considering the power demand of several power-consuming units at different operating states, the power demand profile of the lunar base is generated. The optimal sizing of the PV and battery system for a 1-year horizon, without considering battery degradation, results in a total mass of approximately 1.5 × 10 5 kg to 3.5 × 10 5 kg with a tower height of 10 m depending on the solar illumination profiles at different sites. For a 5-year optimization horizon of the same sites with 10 m tower height and considering the battery yearly capacity degradation, total system mass ranges approximately from 2 × 10 5 kg to 5.5 × 10 5 kg. Although increasing the tower height may considerably reduce the total size and mass of the battery and PV system, the mass of the PV tower will increase. Thus, a satisfactory trade-off in selecting the site location and tower height is required. In this regard, 15 highly illuminated sites at different locations and with different PV tower heights are assessed in this paper. To improve the reliability and flexibility of the power system, the multi-microgrid (MMG) concept is deployed to distribute the power-consuming units of the base among different MGs having their local energy production and storage systems. Finally, based on the total power demand served at a candidate site and the corresponding total system mass, a criterion, mass-per-unit-load (MPUL), is used to identify the sites that serve the highest power demand with less total system mass.

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Research paper thumbnail of Model-Free Predictive Control for Improved Performance and Robustness of Three-Phase Quasi Z-Source Inverters

IEEE Access, 2024

This paper suggests a novel Model-Free Predictive Control (MFPC) approach for three-phase quasi Z... more This paper suggests a novel Model-Free Predictive Control (MFPC) approach for three-phase quasi Z-source inverters (qZSI). While Model Predictive Control (MPC) is popular for qZSI due to its ease of use and performance, it suffers from sensitivity to parameter mismatch. The proposed MFPC overcomes this limitation by relying on an ultra-local model (ULM), eliminating the need for precise parameter matching. This approach establishes a comprehensive mathematical model for key qZSI control variables, including load current, inductor current, and capacitor voltage. Additionally, a unique method seamlessly integrates shoot-through status into the MFPC framework without compromising qZSI operation. Simulation results across various operating conditions demonstrate how much better the suggested MFPC is than the traditional MPC, especially under parameter mismatch scenarios. Notably, the MFPC achieves a significant improvement, exceeding a 37% reduction in total harmonic distortion (THD). Furthermore, the practicality of the proposed MFPC strategy is validated through hardware-in-the-loop (HIL) testing using a C2000TM microcontroller. INDEX TERMS Ultra-local model, model-free control, model predictive control, parametric uncertainties, quasi Z-source inverter, total harmonic distortion.

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Research paper thumbnail of An Improved ω-φ Droop Control for Cascaded PV-ES System in Islanded Mode

IEEE Transactions on Sustainable Energy, 2024

The cascaded H-bridge structure has raised more and more attention in the field of photovoltaic (... more The cascaded H-bridge structure has raised more and more attention in the field of photovoltaic (PV) power generation. This paper presents an improved ω-φ droop control method for the islanded cascaded photovoltaic-energy storage (PVES) system. The PV units mainly focus on outputting active power with unity power factor characteristic while the ES unit is responsible for the total output voltage regulation, frequency restoration, and power fluctuation suppression. With the proposed method, the string voltage can be regulated by the ES unit. Further, both the frequency synchronization with no steady state error and the cooperation between ES and PVs are realized automatically with only ES control requires PCC information. Therefore, the communication dependence is reduced which improves the system reliability. In addition, stability analysis and simulation results are provided to verify the effectiveness of the proposed controller.

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Research paper thumbnail of Topologies and Control in Photovoltaic Systems with and without Storage

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Research paper thumbnail of Lunar Habitat Wastewater Subsystem Power and Water Management

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Research paper thumbnail of On Improved PSO and Neural Network P&O Methods for PV System under Shading and Various Atmospheric Conditions

Energies, Oct 17, 2022

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Research paper thumbnail of A Deep GMDH Neural-Network-Based Robust Fault Detection Method for Active Distribution Networks

Energies

The increasing penetration of distributed generation (DG) to power distribution networks mainly i... more The increasing penetration of distributed generation (DG) to power distribution networks mainly induces weaknesses in the sensitivity and selectivity of protection systems. In this manner, conventional protection systems often fail to protect active distribution networks (ADN) in the case of short-circuit faults. To overcome these challenges, the accurate detection of faults in a reasonable fraction of time appears as a critical issue in distribution networks. Machine learning techniques are capable of generating efficient analytical expressions that can be strong candidates in terms of reliable and robust fault detection for several operating scenarios of ADNs. This paper proposes a deep group method of data handling (GMDH) neural network based on a non-pilot protection method for the protection of an ADN. The developed method is independent of the DG capacity and achieves accurate fault detection under load variations, disturbances, and different high-impedance faults (HIFs). To v...

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Research paper thumbnail of Nonlinear adaptive controller design to stabilize constant power loads connected-DC microgrid using disturbance accommodation technique

Electrical Engineering

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Research paper thumbnail of Optimized Modulation Scheme for Four-Leg Quasi Z-Source Inverter: Reducing Power Loss and Improving Output Quality

IEEE Access

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Research paper thumbnail of A Data-Driven Approach for Generator Load Prediction in Shipboard Microgrid: The Chemical Tanker Case Study

Energies

Energy efficiency and operational safety practices on ships have gained more importance due to th... more Energy efficiency and operational safety practices on ships have gained more importance due to the rules set by the International Maritime Organization in recent years. While approximately 70% of the fuel consumed on a commercial ship is utilized for the propulsion load, a significant portion of the remaining fuel is consumed by the auxiliary generators responsible for the ship’s onboard load. It is crucial to comprehend the impact of the electrical load on the ship’s generators, as it significantly assists maritime operators in strategic energy planning to minimize the chance of unexpected electrical breakdowns during operation. However, an appropriate handling mechanism is required when there are massive datasets and varied input data involved. Thus, this study implements data-driven approaches to estimate the load of a chemical tanker ship’s generator using a 1000-day real dataset. Two case studies were performed, namely, single load prediction for each generator and total load p...

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Research paper thumbnail of Low Computational Burden Predictive Direct Power Control of Quasi Z-Source Inverter for Grid-Tied PV Applications

Sustainability

This paper proposes a simplified predictive direct power control for the grid-tied quasi Z-source... more This paper proposes a simplified predictive direct power control for the grid-tied quasi Z-source inverter. The proposed control implements a model predictive control structure to achieve the maximum obtainable power from the collected PV source. The power delivered to the grid is managed to compensate for the reactive power and, as needed, to ensure the grid’s stability. A predictive power model for a quasi Z-source inverter is developed in which the proposed control can operate with a fixed switching frequency without a weighting factor. The simplified space vector modulation uses the three appropriate switching vectors that are selected and applied using precalculated switching times during each switching period, in which the required switching vectors are determined only from one sector in the space vector diagram, taking all of the information of the other sectors, which leads to reducing the computational burden. Simulation results and comparative study are used to confirm the...

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Research paper thumbnail of Nonlinear Adaptive Controller Design to Stabilize Constant Power Loads connected-DC Microgrid using Disturbance Accommodation Technique

The DC microgrid is comprised of a considerable number of electronically regulated power electron... more The DC microgrid is comprised of a considerable number of electronically regulated power electronic loads that act as constant power loads (CPLs). These power electronic devices have a high bandwidth regulation capability as well as a high-power conversion efficiency. Specifically, the high bandwidth control for the output of the converter load, when paired with the system's filtering components, results in negatively damped oscillations. These features, even if needed, may cause system instability and, finally, system failure if not avoided. To achieve effective power flow control in a DC microgrid, it is crucial to eliminate the undesired behaviour of the CPLs. The control objective requires the assessment of the power for uncertain loads, which vary with time. This paper proposes an adaptive controller linked to a cubature Kalman filter(CKF) for a DC microgrid with time-varying non-ideal CPLs. The controller utilises the neuro-fuzzy inference system(ANFIS) to make the design ...

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Research paper thumbnail of A Comparative Study of MPPTs for Nano-Satellite Microgrid Applications under Spinning Flight Scenarios

IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society

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Research paper thumbnail of Novel V2G regulation scheme using Dual-PSS for PV islanded microgrid

Applied Energy

The incorporation of electric vehicles (EVs) into residential/industrial microgrids (MGs) present... more The incorporation of electric vehicles (EVs) into residential/industrial microgrids (MGs) presents some limitations such as fluctuations in voltage, frequency, and lack of power supply. According to the literature, the control methods for vehicle-to-grid (V2G) in MGs are insufficiently coordinated for charging and regulation, limited by narrow charging control constraints, complex, and computationally demanding. Moreover, the power system stabilizer (PSS) is employed only in the generation side. To this regard, a PSS is proposed in this paper along with the proportional integral-derivative (PID) controller, which is tuned adaptively using Harris hawks optimizer (HHO) for frequency, voltage, and power-sharing regulations through the parked EVs. The considered islanded MG is consisting of a diesel generator as a backup generation source, dealing with the intermittent nature of the solar photovoltaic (PV) plant and residential load. It also includes an EV aggregator. In case of partial shading of the solar PV farm and triggering the load demand, the proposed control strategy provides a complementary signal to promote short response time during transients, boost the transient stability performance, and offer damping characteristics adequate for V2G regulation with the islanded residential MG. To examine the efficacy of the proposed scheme, a detailed simulation model using Matlab/Simulink was built. The final findings show that the proposed direct adaptive PID-PSS controller gives significantly enhanced voltage and frequency with spinning reserve compared to the conventional PI-controller both considering the inclusion of V2G on the MG regulation side and conventional controller without V2G and PSS on the regulation side. Also, it can provide power flow in a bi-directional way during the partial shading contingency that the residential MG may expe-rience within 24 hr.

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Research paper thumbnail of A Decentralized Master-slave Method for Three-Phase Cascaded H-bridge System

IEEE Journal of Emerging and Selected Topics in Industrial Electronics, 2023

For the cascaded H-bridge system, the existing decentralized methods are mainly focused on single... more For the cascaded H-bridge system, the existing decentralized methods are mainly focused on single-phase systems. Designing a decentralized method for the three-phase cascaded H-bridge system is more challenging, particularly, for achieving phase-to-phase frequency synchronization and three-phase voltage balance without real-time communication among each distributed generation (DG). To achieve this, this paper proposes a decentralized master-slave method for three-phase cascaded H-bridge systems, where no communication is required for each local control unit of DGs. The overall control is divided into two parts. One part is for the master DG to realize phase synchronization among Phase-A, B, and C, which is designed by modifying the power factor angle through droop control. The other part is for slave DGs to achieve frequency synchronization of the modules in each phase, which adopts the power factor angle droop control. Small signal stability analysis based on fast and slow time scale separation is carried out for the proposed method. Last, the Control-hardware-in-loop (CHIL) tests and experimental results prove the effectiveness of the proposed method.

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Research paper thumbnail of Optimized Modulation Scheme for Four-Leg Quasi Z-Source Inverter: Reducing Power Loss and Improving Output Quality

IEEE Access, 2023

This study introduces a new three-dimensional space vector modulation technique for a four-leg qu... more This study introduces a new three-dimensional space vector modulation technique for a four-leg quasi Z-source inverter (4L-qZSI) integrating a qZSN and a two-level four-leg inverter. The proposed method encompasses three variants, namely 3DZSVM2, 3DZSVM4, and 3DZSVM8, designed to enhance steady-state operations and harmonic distortions for 4L-qZSI. One of the main contributions of this research is the establishment of a new modulation technique for the 4L-qZSI. The proposed method amalgamates the benefits of SVMs in both abc and αβγ coordinates. The design processes of the 3DZSVM algorithm are carried out in the newly proposed ρσ τ coordinates, while the space vector diagram (SVD) of the 4L-qZSI is utilized in the αβγ location. The proposed algorithm is applied in a single sector, optimizing time interval calculations and pulse creation without requiring trigonometric functions. Extensive simulation studies were conducted to validate the performance of the introduced modulation scheme for the 4L-qZSI. The simulation results show excellent steady-state performance and benefit over the conventional space vector modulation with zero sequences (CZPWM), including a power loss reduction of 50% and a 50% decrease in the THD of the output voltage. In addition, applying this technique results in enhanced output current quality, reduced power loss by 40%, and decreased inductive current ripple by 50% under unbalanced load conditions. Furthermore, the proposed 3DZSVM control strategy for 4L-qZSI is experimentally verified using the TMS320F28379D kit based on the Hardware-in-the-Loop (HIL) simulator. This demonstrates the practicality and effective performance of the suggested control strategy under unbalanced load conditions.

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Research paper thumbnail of A Deep GMDH Neural-Network-Based Robust Fault Detection Method for Active Distribution Networks

Energies, 2023

The increasing penetration of distributed generation (DG) to power distribution networks mainly i... more The increasing penetration of distributed generation (DG) to power distribution networks mainly induces weaknesses in the sensitivity and selectivity of protection systems. In this manner, conventional protection systems often fail to protect active distribution networks (ADN) in the case of short-circuit faults. To overcome these challenges, the accurate detection of faults in a reasonable fraction of time appears as a critical issue in distribution networks. Machine learning techniques are capable of generating efficient analytical expressions that can be strong candidates in terms of reliable and robust fault detection for several operating scenarios of ADNs. This paper proposes a deep group method of data handling (GMDH) neural network based on a non-pilot protection method for the protection of an ADN. The developed method is independent of the DG capacity and achieves accurate fault detection under load variations, disturbances, and different high-impedance faults (HIFs). To verify the improvements, a test system based on a real distribution network that includes three generators with a capacity of 6 MW is utilized. The extensive simulations of the power network are performed using DIgSILENT Power Factory and MATLAB software. The obtained results reveal that a mean absolute percentage error (MAPE) of 3.51% for the GMDH-network-based protection system is accomplished thanks to formulation via optimized algorithms, without requiring the utilization of any feature selection techniques. The proposed method has a high-speed operation of around 20 ms for the detection of faults, while the conventional OC relay performance is in the blinding mode in the worst situations for faults with HIFs.

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Research paper thumbnail of A Data-Driven Approach for Generator Load Prediction in Shipboard Microgrid: The Chemical Tanker Case Study

Energies, 2023

Energy efficiency and operational safety practices on ships have gained more importance due to th... more Energy efficiency and operational safety practices on ships have gained more importance due to the rules set by the International Maritime Organization in recent years. While approximately 70% of the fuel consumed on a commercial ship is utilized for the propulsion load, a significant portion of the remaining fuel is consumed by the auxiliary generators responsible for the ship’s onboard load. It is crucial to comprehend the impact of the electrical load on the ship’s generators, as it significantly assists maritime operators in strategic energy planning to minimize the chance of unexpected electrical breakdowns during operation. However, an appropriate handling mechanism is required when there are massive datasets and varied input data involved. Thus, this study implements data-driven approaches to estimate the load of a chemical tanker ship’s generator using a 1000-day real dataset. Two case studies were performed, namely, single load prediction for each generator and total load prediction for all generators. The prediction results show that for the single generator load prediction of DG1, DG2, and DG3, the decision tree model encountered the least errors for MAE (0.2364, 0.1306, and 0.1532), RMSE (0.2455, 0.2069, and 0.2182), and MAPE (17.493, 5.1139, and 7.7481). In contrast, the deep neural network outperforms all other prediction models in the case of total generation prediction, with values of 1.0866, 2.6049, and 14.728 for MAE, RMSE, and MAPE, respectively.

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Research paper thumbnail of Optimal Sizing and Siting of PV and Battery Based Space Microgrids Near the Moon’s Shackleton Crater

IEEE Access

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Research paper thumbnail of Low Computational Burden Predictive Direct Power Control of Quasi Z-Source Inverter for Grid-Tied PV Applications

Sustainability, 2023

This paper proposes a simplified predictive direct power control for the grid-tied quasi Z-source... more This paper proposes a simplified predictive direct power control for the grid-tied quasi Z-source inverter. The proposed control implements a model predictive control structure to achieve the maximum obtainable power from the collected PV source. The power delivered to the grid is managed to compensate for the reactive power and, as needed, to ensure the grid’s stability. A predictive power model for a quasi Z-source inverter is developed in which the proposed control can operate with a fixed switching frequency without a weighting factor. The simplified space vector modulation uses the three appropriate switching vectors that are selected and applied using precalculated switching times during each switching period, in which the required switching vectors are determined only from one sector in the space vector diagram, taking all of the information of the other sectors, which leads to reducing the computational burden. Simulation results and comparative study are used to confirm the proposed control performance for the grid-tied quasi Z-source inverter capable of tracking and generating the maximum power from PV with fast-tracking dynamics, ensuring the ac voltage desired, and better tracking of the active and reactive power reference with the lowest power ripple. The grid current harmonics were tested and conformed to the IEEE-519 standard. Additionally, the proposed simplified PDPC is experimentally validated using the Hardware-in-the-Loop emulator and the C2000TM-microcontroller-LaunchPadXL TMS320F28379D kit, establishing the usability and good result of our proposed control approach in terms of requirements.

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Research paper thumbnail of Optimal Sizing and Siting of PV and Battery based Space Microgrids near the Moon's Shackleton Crater

IEEE Access, 2023

Space mission cost and feasibility depend mainly on the size and mass of the payload. This paper ... more Space mission cost and feasibility depend mainly on the size and mass of the payload. This paper investigates the optimal photovoltaic (PV) array and battery size and mass for an islanded PV-battery powered space microgrid (MG) at the lunar south pole. The PV arrays are considered to be installed on top of towers to increase solar energy harvesting. Considering the dependency of the generated power from PV arrays on the tower height, different tower heights of 10, 50, and 100 m are investigated. The paper presents the methodology to estimate the available power from the PV system using the information of illumination time-series at the location of potential sites with different tower heights. Besides, considering the power demand of several power-consuming units at different operating states, the power demand profile of the lunar base is generated. The optimal sizing of the PV and battery system for a 1-year horizon, without considering battery degradation, results in a total mass of approximately 1.5 × 10 5 kg to 3.5 × 10 5 kg with a tower height of 10 m depending on the solar illumination profiles at different sites. For a 5-year optimization horizon of the same sites with 10 m tower height and considering the battery yearly capacity degradation, total system mass ranges approximately from 2 × 10 5 kg to 5.5 × 10 5 kg. Although increasing the tower height may considerably reduce the total size and mass of the battery and PV system, the mass of the PV tower will increase. Thus, a satisfactory trade-off in selecting the site location and tower height is required. In this regard, 15 highly illuminated sites at different locations and with different PV tower heights are assessed in this paper. To improve the reliability and flexibility of the power system, the multi-microgrid (MMG) concept is deployed to distribute the power-consuming units of the base among different MGs having their local energy production and storage systems. Finally, based on the total power demand served at a candidate site and the corresponding total system mass, a criterion, mass-per-unit-load (MPUL), is used to identify the sites that serve the highest power demand with less total system mass.

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