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Performance Evaluation of perturb and observe algorithm for MPPT with Buck-Boost Charge Controller in Photovoltaic Systems

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JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS 2021年第6期32卷 1652-1662页

作者： Bhan, Veer Shaikh, Shoaib Ahmed Khand, Zahid Hussain Ahmed, Tofique Khan, Liaquat Ali Chachar, Faheem Akhtar Shaikh, Abdul Majeed Sukkur IBA Univ Dept Elect Engn Sukkur Sindh Pakistan

The ecological and economical concerns have given rise to the application of solar photovoltaic (PV) system in the community to meet the increased load demands on its own. Owing to the varying output of solar PV modules depending on the weather conditions, the efficiency of system is degraded and thus requires using maximum power point (MPP) tracking technique for utmost power extraction. The MPP methods can be realized both mechanically or electrically using suitable converter topology and appropriate tracking algorithm. However, the mechanical tracker in contrast to electrical circuit is immoderate and inefficient and conversely necessitates to exercise effective and promising power tracking algorithm. This research proposes to implement the perturb and observe (P and O) algorithm for MPPT in charge controller using buck-boost converter to attain desired and optimized results. The use of buck-boost DC-DC converter helps in stepping up/down the voltage level as per requirements under the control of P and O algorithm. Having optimized tracker designed, its performance has been tested at different levels of irradiance and temperature principally with load and battery. Further, the results obtained from simulated scenarios are compared with real-time experiments, which confirm the robustness and effectiveness of proposed MPPT method in solar PV system using P and O algorithm and buck-boost converter.

关键词： PV module perturb and observe algorithm Maximum power point tracking Buck-boost converter

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Enhancing the Maximum Power Extraction in Partially Shaded PV Arrays Using Hybrid Salp Swarm perturb and observe algorithm

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INTERNATIONAL JOURNAL OF RENEWABLE ENERGY RESEARCH 2020年第2期10卷 898-911页

作者： Balaji, V Fathima, A. Peer Vellore Inst Technol Sch Elect Engn Chennai 600127 Tamil Nadu India

Partial shading is a common problem faced by photovoltaic (PV) modules installed in residential areas. During shaded conditions, the power voltage (P-V) characteristics of the PV array consist of many local power peaks and a global power peak. Out of the many maximum power tracking algorithms, the perturb and observe (PO) is considered as the simplest algorithm. However, PO fails in tracking maximum power during shaded conditions, as it can track only a single power peak. In this proposed work, additional modification to PO algorithm is given by combining it to a metaheuristic Salp Swarm (SS) algorithm. Thus, a hybrid Salp Swarm perturb and observe (SSPO) algorithm is proposed in this paper, wherein the SS algorithm is used to locate the approximate global peak, and PO is utilized to find the exact global power. The proposed algorithm can track the exact power during uniform and partial shaded conditions. The SSPO is tested under steady state and dynamic conditions using MATLAB/Simulink The obtained results are compared with the Salp swarm and conventional PO algorithm and it shows that SSPO can track the maximum power in all the conditions with 99 % efficiency and faster tracking time.

关键词： Salp swarm algorithm Partial shading Maximum power point tracking perturb and observe algorithm Stand alone PV system

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Framework of Maximum Power Extraction From Solar PV Panel Using Self Predictive perturb and observe algorithm

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IEEE TRANSACTIONS ON SUSTAINABLE ENERGY 2018年第2期9卷 895-903页

作者： Kumar, Nishant Hussain, Ikhlaq Singh, Bhim Panigrahi, Bijaya Ketan Indian Inst Technol Delhi Dept Elect Engn New Delhi 110016 India

This paper deals with a new version of perturb and observe tracking algorithm for maximum power extraction from the solar photovoltaic panel, which has self-predictive and decision taking ability. The working principle of self-predictive perturb and observe (SPP&O) algorithm is based on three consecutive operating points on the power-voltage characteristic. Out of three points, first two points very smartly detects the dynamic condition, as well as in normal condition, quickly searches the maximum power point (MPP) region. Moreover, by using a circular analogy, all points decide the optimal operating position for next iteration, which is responsible for quick MPP tracking as well as improved dynamic performance. Here, in every new iteration, the step-size is reduced by 90% from the previous step-size, which provides an oscillation-free steady-state performance. The effectiveness of the proposed technique is validated by MATLAB simulation as well as tested on hardware prototype. Moreover, comparison between SPP&O algorithm and state of art methods is made. Its satisfactory dynamic and steady-state behaviors with low algorithm complexity as well as the low computational burden of the SPP&O algorithm show the superiority over state of the art methods.

关键词： Solar PV MPPT self predictive perturb and observe algorithm spherical analogy SPP&O

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Improvement of Maximum Power Point Tracking perturb and observe algorithm for a Standalone Solar Photovoltaic System

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MEHRAN UNIVERSITY RESEARCH JOURNAL OF ENGINEERING AND TECHNOLOGY 2017年第3期36卷 501-510页

作者： Awan, Muhammad Mateen Afzal Awan, Fahim Gohar Univ Engn & Technol Ctr Energy Res & Dev Lahore Pakistan Univ Engn & Technol Dept Elect Engn Lahore Pakistan

Extraction of maximum power from PV (Photovoltaic) cell is necessary to make the PV system efficient. Maximum power can be achieved by operating the system at MPP (Maximum Power Point) (taking the operating point of PV panel to MPP) and for this purpose MPPT (Maximum Power Point Trackers) are used. There are many tracking algorithms/methods used by these trackers which includes incremental conductance, constant voltage method, constant current method, short circuit current method, PAO (perturb and observe) method, and open circuit voltage method but PAO is the mostly used algorithm because it is simple and easy to implement. PAO algorithm has some drawbacks, one is low tracking speed under rapid changing weather conditions and second is oscillations of PV systems operating point around MPP. Little improvement is achieved in past papers regarding these issues. In this paper, a new method named "Decrease and Fix" method is successfully introduced as improvement in PAO algorithm to overcome these issues of tracking speed and oscillations. Decrease and fix method is the first successful attempt with PAO algorithm for stability achievement and speeding up of tracking process in photovoltaic system. Complete standalone photovoltaic system's model with improved perturb and observe algorithm is simulated in MATLAB Simulink.

关键词： Photovoltaic Cell Maximum Power Point Tracking perturb and observe algorithm Decrease and Fix Method

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Development of a hybrid genetic algorithm/perturb and observe algorithm for maximum power point tracking in photovoltaic systems under non-uniform insolation

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IET RENEWABLE POWER GENERATION 2015年第7期9卷 757-765页

作者： Sundareswaran, Kinattingal Vigneshkumar, Vethanayagam Palani, Sankaran Natl Inst Technol Dept Elect & Elect Engn Tiruchirappalli 620015 Tamil Nadu India Sudharsan Engn Coll Dept Elect & Commun Engn Pudukkottai Tamil Nadu India

The power-voltage characteristic curve of photovoltaic systems under partially shaded conditions exhibits multiple peaks and renders conventional maximum power point tracking techniques ineffective. This study proposes a hybrid optimisation algorithm incorporating genetic algorithm (GA) in the initial stages of tracking followed by traditional perturb and observe (P&O) algorithm. Although GA and P&O methods do not guarantee convergence to global maximum power point when employed separately, the fusion of the two methods leads to confirmed global convergences with least time. The excellent performance of the combined method is illustrated through extensive simulation and experimental results.

关键词： genetic algorithms maximum power point trackers hybrid power systems convergence solar cells hybrid genetic algorithm photovoltaic system nonuniform insolation power-voltage characteristic curve partially shaded conditions maximum power point tracking technique hybrid GA optimisation algorithm perturb and observe algorithm P& O algorithm global convergence

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A new MPPT design using variable step size perturb and observe method for PV system under partially shaded conditions by modified shuffled frog leaping algorithm- SMC controller

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SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS 2021年 45卷 101056-101056页

作者： Mohammadinodoushan, Mohammad Abbassi, Rabeh Jerbi, Houssem Ahmed, Faraedoon Waly Ahmed, Halkawt Abdalqadir kh Rezvani, Alireza No Arizona Univ Sch Informat Comp & Cyber Syst Flagstaff AZ 86011 USA Univ Hail Coll Engn Dept Elect Engn Hail 1234 Saudi Arabia Univ Hail Coll Engn Dept Ind Engn Hail 1234 Saudi Arabia Univ Halabja Dept Phys Coll Sci Halabja Iraq Sulaimani Polytech Univ Chamchamal Tech Inst Dept Elect Installat Sulaymaniyah Iraq Duy Tan Univ Inst Res & Dev Da Nang 550000 Vietnam Duy Tan Univ Fac Elect Elect Engn Da Nang 550000 Vietnam

Renewable energies, particularly solar photovoltaic (PV) panels have been largely integrated into power systems, mainly due to the fact that this technology is environmentally friendly and available almost everywhere. However, these systems have some challenges regarding their efficiency. They should always follow the maximum power point (MPP) to deliver the highest power. To this end, maximum power point tracking methods, known as MPPT algorithms, have already been proposed to overcome this problem. The MPPT techniques, commonly used, take into consideration unchanged climate conditions. In this respect, a novel framework is developed in this paper for the MPPT algorithm based on a sliding mode controller (SMC) applicable to PV panels with partial shading conditions (PSC) and uniform conditions. This model employs the modified shuffled frog leaping algorithm (MSFLA) to derive the desired values of the parameters of the controller that utilizes the variable step-size perturb and observe (P&O). The performance of the developed framework is based on using the desired values of the SMC for the variable step-size P&O of the MPPT when the system operates in the grid-connected state. The presented framework is abbreviated MSFLA-SMC. This system shows precise tracking under changing weather conditions and it performs better compared to conventional techniques. The developed control system is associated with desired dynamic response and power flow between the PV system and the grid.

关键词： Partial shading condition Uniform condition PV Sliding mode controller Energy efficiency Grid connected perturb and observe algorithm

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MPPT Reactive Control algorithm for Heaving Wave Energy Converters With Power Setpoint Capabilities

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IEEE ACCESS 2024年 12卷 176779-176798页

作者： Elamin, Abdin Y. Wahyudie, Addy Hashfi, Tuanku Badzlin Shareef, Hussain Errouissi, Rachid Laghari, Mohammad Shakeel Mubin, Marizan Binti Mekhilef, Saad United Arab Emirates Univ UAE U Dept Elect & Commun Engn Al Ain U Arab Emirates United Arab Emirates Univ UAE U Natl Water & Energy Ctr Al Ain U Arab Emirates Delft Univ Technol Dept Elect Sustainable Energy NL-2628 CD Delft Netherlands Univ Malaya Dept Elect Engn Kuala Lumpur 50603 Malaysia Swinburne Univ Technol Sch Sci Comp & Engn Technol Melbourne Vic 3122 Australia

Reactive control is a popular method for maximizing wave energy absorption in wave energy converters (WECs). This technique involves adjusting the damping and stiffness coefficients of the WEC to align its natural frequency with the frequency of incoming waves. Unfortunately, wave variability and complex hydrodynamics have posed challenges in accurately determining these coefficients. This paper proposes a model-independent approach for reactive control based on a variable step size maximum power point tracking (MPPT) algorithm. The MPPT algorithm tunes the WEC's damping and stiffness coefficients toward maximum generated power. Furthermore, a power curtailment control (PCC) strategy is integrated, based on a proportional-integral (PI) controller that modifies the MPPT control force to follow power generation references below its maximum generation capacity. This capability is essential for grid integration, where power generation must match demand. Finally, a hardware-in-the-loop experimental setup was constructed to evaluate the proposed control strategies under monochromatic and polychromatic wave conditions. An analysis comparing MPPT and damping control under various polychromatic wave conditions revealed that MPPT achieves substantially higher electrical power, outperforming damping control by 55.4% to 70.6%. The experimental results demonstrated the efficacy of the PCC strategy in reducing the WEC power output to track specific power setpoints.

关键词： Wave energy conversion Mathematical models Force Damping Maximum power point trackers Absorption Hydrodynamics Tuning Prediction algorithms Power systems Complex conjugate control hardware-in-the-loop maximum power point tracking permanent magnet linear generator perturb and observe algorithm power curtailment control wave energy converter

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Investigation and simulation of a solar water pumping system with a speed-controlled DC motor 12

Investigation and simulation of a solar water pumping system...

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12th International Conference on Smart Grid (ICSmartGrid)

作者： Benabida, Farid Aissa, Oualid Talhaoui, Hicham Babes, Badreddine Colak, Ilhami Univ Mohamed El Bachir El Ibrahimi Bordj Bou Arre LPMRN Lab Fac Sci & Technol El Anceur Algeria Res Ctr Ind Technol CRTI Algiers Algeria Istinye Univ Fac Engn & Nat Sci Dept Elect & Elect Engn Istanbul Turkiye

ISBN: (纸本)9798350361612;9798350361629

An investigation on a photovoltaic (PV) water pumping system (PVWPS) based on a DC motor, under an imposed rotation speed and changeable weather conditions, has been done in this research work. Thus, to extract the maximum power point of the studied system, the perturb and observe (P&O) algorithm and Incremental Conductance (IC) strategy are applied. The investigation is conducted on a centrifugal pump driven by a DC motor with speed control by using the MATLAB/Simulink software. The simulation results from the designed PVWPS demonstrate that the IC strategy outperforms the P&O algorithm in convergence speed, while the P&O offers superior steady-state oscillation performance under high irradiation levels.

关键词： Solar Pumping System Incremental Conductance strategy perturb and observe algorithm DC motor Speed Control

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Deep Reinforcement Learning Based MPPT Control for Grid Connected PV System 7

Deep Reinforcement Learning Based MPPT Control for Grid Conn...

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IEEE 7th International Conference on Industrial Cyber-Physical Systems (ICPS)

作者： Vora, Kunal Liu, Shichao Dhulipati, Himavarsha Carleton Univ Dept Elect Ottawa ON Canada

ISBN: (纸本)9798350363029;9798350363012

Maximum power point tracking (MPPT) helps in generating maximum power from PV system at a specified irradiance levels irrespective of changes in the sun's position and cloud cover conditions. From previous studies, it is observed that, conventional methods for MPPT suffers from oscillations around maximum power point and does not adapt to changing environmental conditions of irradiance and temperature. Therefore, new techniques like reinforcement learning is implemented in PV system to overcome aforementioned limitations. In this paper, integration of deep learning and reinforcement learning named deep Q-learning (DQN) is implemented in grid connected PV system. DQN solves the problem of varying environmental conditions by discretizing the state spaces. The proposed method is implemented in MATLAB/ SIMULINK environment. Based on the simulation results, it can be proposed that proposed method is efficient in handling ever changing environmental conditions.

关键词： Deep Reinforcement Learning Photovoltaic System Maximum power point tracking perturb and observe algorithm Energy Storage Sustainable Energy

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Neural-Gradient Maximum Power Point Tracking Method for Solar Panel

Neural-Gradient Maximum Power Point Tracking Method for Sola...

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2023 IEEE International Conference on Electrical, Computer and Energy Technologies, ICECET 2023

作者： Wacira, Joseph M. Vargas, Alessandro N. Bah, Bubacarr Sampaio, Leonardo P. African Institute for Mathematical Sciences Stellenbosch University Cape Town South Africa Universidade Technológica Federal Do Paraná Department of Electrical Engineering Paraná Brazil London School of Hygiene and Tropical Medicine Medical Research Council Unit the Gambia Bakau Gambia

ISBN: (纸本)9798350327816

A popular method used to maximize the power output of solar panels is Maximum Power Point Tracking (MPPT). This work attempted to improve MPPT by utilizing an artificial neural network (ANN) algorithm and gradient perturbation of the duty cycle, dubbed the Neural-Gradient MPPT method. The ANN takes in as input, irradiance, and temperature, whereas its outputs are the power and current at the MPP. We compared our proposed algorithm to the popular traditional MPPT algorithm, perturb and observe (P&O). Our proposed MPPT technique has a faster response to abrupt changes in solar irradiance and temperature and less steady-state error than the baseline P&O algorithm. © 2023 IEEE.

关键词： artificial neural network Maximum Power Point Tracking perturb and observe algorithm

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