Article
Computer Science, Information Systems
Song-Pei Ye, Yi-Hua Liu, Chun-Yu Liu, Kun-Che Ho, Yi-Feng Luo
Summary: A neural network assisted variable step size incremental conductance MPPT method is proposed in this paper for photovoltaic systems. By adopting a proper scaling factor, the performance of this method can be improved under rapidly changing irradiance conditions.
Article
Computer Science, Artificial Intelligence
Hamza Bahri, Abdelghani Harrag
Summary: PEMFC fuel cell is characterized by low operating temperature, high efficiency, and long lifetime, but faces challenges such as dependency of output power on operating conditions. The development of a golden section search-based maximum power point tracking controller can improve operation and optimize power extraction.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Isaac Owusu-Nyarko, Mohamed A. Elgenedy, Ibrahim Abdelsalam, Khaled H. Ahmed
Summary: The newly proposed modified variable step-size INC algorithm addresses the two main drawbacks of traditional techniques by continuously adjusting step-size through an autonomous scaling factor and slope angle variation algorithm, thereby mitigating the impact of PV voltage change to improve MPPT efficiency.
Article
Engineering, Electrical & Electronic
Muhammad Omer Bin Saeed, Syed Ahmed Pasha, Azzedine Zerguine
Summary: This paper presents a different variable step-size incremental least mean square strategy that provides excellent performance at low SNR values. The proposed algorithm has been theoretically analyzed and validated through simulations for different scenarios. Various variable step algorithms for high SNR values exist in the literature.
Article
Chemistry, Multidisciplinary
Sergio Andre, Fernando Silva, Sonia Pinto, Pedro Miguens
Summary: Research on renewable energy and power electronic converters is increasing due to environmental concerns. This study proposes a novel MPPT technique based on integral feedback conductance and incremental conductance error, considering the current dynamics of the boost converter. The efficiency, performance, and computational needs of this MPPT algorithm are evaluated and compared to other widely used techniques in the literature.
APPLIED SCIENCES-BASEL
(2023)
Article
Multidisciplinary Sciences
Ibrahim AL-Wesabi, Fang Zhijian, Hassan M. Hussein Farh, Abdullrahman A. Al-Shammaa, Hanlin Dong, Abdullah M. Al-Shaalan, Tarek Kandil
Summary: This study addresses the issues caused by low ripples and variations in the DC-Bus voltage in single-phase Photovoltaic/Battery Energy Storage (PV/BES) grid-connected systems. By using the modified incremental conductance (MIC) technique and a novel d-q current regulation technique, the ripples and fluctuations are successfully eliminated. Furthermore, the use of Battery Energy Storage (BES) improves the dynamic performance of the system.
SCIENTIFIC REPORTS
(2022)
Article
Automation & Control Systems
Zhihong Yan, Ying Huang, Siew-Chong Tan, Chuyang Y. Tang, Shu Yuen Hui
Summary: In this article, a self-adaptive-step-size incremental-resistance MPPT technique is proposed to extract maximum power from RED stacks. It is simple and easy to implement, and realizes a balance between fast dynamic responses and small oscillations at a steady state. Various tests are conducted to validate the effectiveness of the proposed MPPT technique.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Syed Safi Uddin Qadri, Muhammad Arif, Muhammad Omer Bin Saeed
Summary: This study proposes a variable step-size strategy for distributed network estimation using the incremental scheme. The algorithm utilizes the ratio of filtered squared instantaneous error to the squared instantaneous error in a windowed format, reducing dependency on error power in low signal-to-noise power ratio situations. Theoretical analysis yields closed-form solutions for mean squared error, excess mean squared error, and mean squared deviation, which are verified through simulation results. Extensive testing demonstrates the superiority of the proposed algorithm compared to other algorithms.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Engineering, Multidisciplinary
Shaik Rafi Kiran, Ch Hussaian Basha, Abhishek Kumbhar, Nikita Patil
Summary: This article investigates the maximum power point tracking controller and boost converter for fuel cell systems. The peak power of the fuel cell system is achieved using the modified MPPT controller, and an efficient boost-up device is proposed in this study.
SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES
(2022)
Article
Computer Science, Information Systems
Mahmoud N. Ali, Karar Mahmoud, Matti Lehtonen, Mohamed M. F. Darwish
Summary: This paper proposes a novel design of a fuzzy logic based algorithm for varying the step size of the incremental conductance (INC) maximum power point tracking (MPPT) method for photovoltaic (PV) generation units. The method introduces five effective regions around the point of maximum PV power, and uses a fuzzy logic system to adjust the step size of the duty cycle. By enhancing the coordination between the fuzzy logic based algorithm and the INC method, the MPPT efficiency is improved, as demonstrated in simulations of a grid-connected PV system model.
Article
Automation & Control Systems
Jinlong Lei, Peng Yi, Jie Chen, Yiguang Hong
Summary: In this article, the authors investigate the problem of distributed stochastic optimization over randomly switching networks. They propose a distributed stochastic gradient tracking algorithm that incorporates a variance reduction scheme. They provide convergence guarantees and complexity analysis under certain conditions.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Computer Science, Artificial Intelligence
Tao Hai, Jasni Mohamad Zain, Kengo Muranaka
Summary: This study proposes the utilization of the modified fluid search optimization (MFSO) algorithm to regulate the incremental conductance (INC) controller for maximum power tracking. A MATLAB/Simulink model is constructed to evaluate the performance of the proposed approach and has been tested across various weather conditions. The simulation results demonstrate the effectiveness of the suggested approach in monitoring the maximum power point under different environmental circumstances, achieving a performance rate exceeding 99.3%.
Article
Computer Science, Information Systems
Mohammad Haziq Ibrahim, Swee Peng Ang, Muhammad Norfauzi Dani, Mohammad Ishlah Rahman, Rafidah Petra, Sheik Mohammed Sulthan
Summary: This paper introduces a hybrid MPPT algorithm using particle swarm optimization to optimize the maximum PV output power. The algorithm adjusts the step size according to solar irradiance. The results show that the hybrid algorithm outperforms the conventional methods.
Article
Mathematics, Applied
Dan Yang, Xiangmei Wang
Summary: This paper investigates the use of dynamic step sizes in the incremental subgradient algorithm for minimizing the sum of a large number of convex functions. Two modified dynamic step size rules are proposed and their convergence and complexity properties are analyzed. Experimental results show that these two algorithms converge faster and more stably than the previous ones, especially for solving large separable convex optimization problems.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2023)
Article
Automation & Control Systems
Sandeep Sahoo, Shailendra Kumar, Bhim Singh
Summary: This article introduces the Wiener variable step size with variance smoothening (WVSSV) technique for the utility supportive solar photovoltaic (PV) system. The WVSSV technique controls the dc-ac converter to perform power factor correction, compensation of nonactive component, and reduction of total harmonics distortion (THD) from the utility grid. It presents robustness and good adaptation in highly adverse nonlinear load conditions.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Computer Science, Artificial Intelligence
Mustapha Habib, Ahmed Amine Ladjici, Abdelghani Harrag
NEURAL COMPUTING & APPLICATIONS
(2020)
Article
Computer Science, Artificial Intelligence
Hamza Bahri, Abdelghani Harrag
Summary: PEMFC fuel cell is characterized by low operating temperature, high efficiency, and long lifetime, but faces challenges such as dependency of output power on operating conditions. The development of a golden section search-based maximum power point tracking controller can improve operation and optimize power extraction.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Abdelghani Harrag, Hegazy Rezk
Summary: A new hybrid MPPT approach combining perturb & observe and type-2 fuzzy logic is proposed to improve the power output of a PEMFC system. Comparative simulation results demonstrate significant improvements in dynamic response time and steady-state oscillations compared to traditional methods.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Electrochemistry
Abdelghani Harrag
Summary: This study introduces a novel neural network single sensor maximum power point tracking algorithm to optimize the output power of proton exchange membrane fuel cells. Comparative simulation results demonstrate the superiority of the proposed neural network controller over traditional single sensor methods in terms of transit response reduction and overall energy losses. Moreover, the implementation of the neural network controller with only one sensor reduces complexity and cost in PEM fuel cell power systems.
JOURNAL OF NEW MATERIALS FOR ELECTROCHEMICAL SYSTEMS
(2021)
Article
Thermodynamics
Assam Boudia, Sabir Messalti, Abdelghani Harrag, Moussa Boukhnifer
Summary: A new control strategy for photovoltaic system based on superconducting magnetic energy storage (SMES) has been proposed and investigated, showing significant improvements in extracting maximum power point and controlling energy storage. The comparative study between PID classic controller and PID-fuzzy controller has demonstrated that the latter provides superior accuracy and reduced power oscillation in PV-SMES system.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Energy & Fuels
Hegazy Rezk, Abdelghani Harrag
Summary: A robust type-2 fuzzy logic-based MPPT approach is proposed in this work to enhance the energy efficiency of thermoelectric generators. By adaptively adjusting the step size of incremental resistance MPPT, the method achieves stable extraction of the maximum power point of TEG under varying operational conditions.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Electrochemistry
Hamza Bahri, Abdelghani Harrag
Summary: Due to the increasing global energy consumption, renewable energy technology is necessary to address environmental problems. Hydrogen is a promising alternative fuel for the future, produced through water electrolysis using renewable energy to provide direct electric current.
JOURNAL OF NEW MATERIALS FOR ELECTROCHEMICAL SYSTEMS
(2021)
Review
Energy & Fuels
S. Mohanty, P. K. Patra, A. Mohanty, A. Harrag, Hegazy Rezk
Summary: The measurement and forecasting of solar radiation is a challenging task that requires intelligent modeling techniques. This study focuses on the use of an ANFIS model to accurately predict solar radiation based on selected input parameters. A comprehensive literature survey was conducted to review various studies in this field.
FRONTIERS IN ENERGY RESEARCH
(2022)
Article
Electrochemistry
Hamza Bahri, Abdelghani Harrag, Hegazy Rezk
Summary: This study presents a renewable energy-based hybrid system for powering a cell tower in Algeria, with the lowest total net present cost and levelized cost of energy, environmentally friendly and emission-free. The operational strategy ensures the hybrid system generally meets the load requirements.
JOURNAL OF NEW MATERIALS FOR ELECTROCHEMICAL SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Mustapha Habib, Annika Gram, Abdelghani Harrag, Qian Wang
Summary: This paper presents a methodology for analyzing and simulating the effect of operating large photovoltaic plants as static synchronous compensators, with the goal of improving voltage profiles and reducing power losses in transmission lines. The proposed approach takes into account the varying reactive power capacity in PV inverters and uses an optimization algorithm to find the optimal reactive power setpoint for each plant in real time.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Abdelghani Harrag, Mustapha Hatti
Summary: This paper discusses the development of stateflow P&O and IC MPPT controllers for a PV power system, which includes a PV module BP-SX150S powering a resistive load via a dc-dc boost converter controlled using the proposed stateflow models. Simulation and experimental testing confirmed the effectiveness of the stateflow P&O and IC MPPT models in tracking maximum output power, with variable step size versions showing the best performance.
REVUE ROUMAINE DES SCIENCES TECHNIQUES-SERIE ELECTROTECHNIQUE ET ENERGETIQUE
(2022)
Article
Engineering, Electrical & Electronic
Yacine Daili, Abdelghani Harrag
Summary: The VSG concept is a promising solution for integrating renewable DG into microgrids. However, traditional VSG control suffers from nonlinear and strongly coupled active and reactive powers, leading to poor dynamic performance. The proposed decoupled VSG control effectively improves stability and dynamic performance by introducing additional control signals and utilizing a small signal approach. Simulation results demonstrate significant improvements in overshoot and setting time, confirming the effectiveness of the proposed VSG control.
REVUE ROUMAINE DES SCIENCES TECHNIQUES-SERIE ELECTROTECHNIQUE ET ENERGETIQUE
(2021)
Article
Electrochemistry
Boudia Assam, Messalti Sabir, Harrag Abdelghani
JOURNAL OF NEW MATERIALS FOR ELECTROCHEMICAL SYSTEMS
(2020)
Proceedings Paper
Automation & Control Systems
Nassir Harrag, Abdelghani Harrag
2019 6TH INTERNATIONAL CONFERENCE ON CONTROL, DECISION AND INFORMATION TECHNOLOGIES (CODIT 2019)
(2019)
Proceedings Paper
Computer Science, Theory & Methods
Abdelghani Harrag, Sabir Messalti
RENEWABLE ENERGY FOR SMART AND SUSTAINABLE CITIES: ARTIFICIAL INTELLIGENCE IN RENEWABLE ENERGETIC SYSTEMS
(2019)
