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Journal articles on the topic 'Contrôle MPPT'

Author: Grafiati

Published: 4 June 2021

Last updated: 10 February 2022

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1

Confessor, Sâmya Lorena Medeiros, and Dorgival Albertino Da Silva Júnior. "MODELAGEM DE UM MÓDULO FOTOVOLTAICO PARA CONTROLE MPPT (MODELING OF A PHOTOVOLTAIC MODULE MPPT CONTROL." Engevista 18, no. 1 (July 27, 2016): 250. http://dx.doi.org/10.22409/engevista.v18i1.724.

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O presente artigo têm como objetivo apresentar a modelagem e simulação de um módulo fotovoltaico. Para isso, utilizou-se o modelo de um diodo, também conhecido como modelo ideal. A partir da modelagem, criou-se blocos através do MATLAB/Simulink® para implementação e simulação do módulo em estudo, o KC85T do fabricante Kyocera. Os resultados obtidos comprovaram e validaram o modelo desenvolvido, uma vez que as curvas características V-I e V-P obtidas coincidem com as fornecidas pelo fabricante do módulo PV. A partir do modelo, pode-se utilizá-lo em um sistema de geração fotovoltaica conectado a um conversor em que será realizado o controle do MPPT (Maximum Power Point Tracking) do módulo PV.

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2

Hinokuma, Tatsuya, Hooman Farzaneh, and Ayas Shaqour. "Techno-Economic Analysis of a Fuzzy Logic Control Based Hybrid Renewable Energy System to Power a University Campus in Japan." Energies 14, no. 7 (April 1, 2021): 1960. http://dx.doi.org/10.3390/en14071960.

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In order to reduce the load demand of buildings in Japan, this study proposes a grid-tied hybrid solar–wind–hydrogen system that is equipped with a maximum power point tracking (MPPT) system, using a fuzzy logic control (FLC) algorithm. Compared with the existing MPPTs, the proposed MPPT provides rapid power control with small oscillations. The dynamic simulation of the proposed hybrid renewable energy system (HRES) was performed in MATLAB-Simulink, and the model results were validated using an experimental setup installed in the Chikushi campus, Kyushu University, Japan. The techno-economic analysis (TEA) of the proposed system was performed to estimate the optimal configuration of the proposed HRES, subject to satisfying the required annual load in the Chikushi campus. The results revealed a potential of 2% surplus power generation from the proposed HRES, using the FLC-based MPPT system, which can guarantee a lower levelized cost of electricity (LOCE) for the HRES and significant savings of 2.17 million yen per year. The TEA results show that reducing the cost of the solar system market will lead to a reduction in LCOE of the HRES in 2030.

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3

Hua, Chih-Chiang, and Yu-Jun Zhan. "A Hybrid Maximum Power Point Tracking Method without Oscillations in Steady-State for Photovoltaic Energy Systems." Energies 14, no. 18 (September 7, 2021): 5590. http://dx.doi.org/10.3390/en14185590.

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This paper proposes a hybrid maximum power point tracking (MPPT) method with zero oscillation in steady-state by combining genetic algorithm (GA) and perturbation and observation (P&O) method. The proposed MPPT can track the global maximum power point (GMPP) fast for a photovoltaic (PV) system even under partial shaded conditions (PSC). The oscillations around the GMPP are eliminated and the power loss can be reduced significantly. In addition, the proposed MPPT can make the PV system operate at the highest efficiencies under various atmospheric conditions. During the MPP tracking, the system will oscillate around the MPPs, resulting in unnecessary power loss. To solve the problem, the artificial intelligence (AI) algorithms, such as PSO, Bee Colony optimization, GA, etc., were developed to deal with this issue. However, the problem with the AI algorithm is that the time for convergence may be too long if the range of the MPP search space is large. In addition, if the atmospheric conditions change fast, the PV system may operate at or close to the local maximum power points (LMPPs) for a long time. In this paper, a method combining the P&O’s fast tracking and GA’s GMPP tracking ability is proposed. The proposed system can stop the oscillations as soon as the GMPP is found, thus minimizing the power loss due to oscillations. The proposed MPPT can achieve superior performance while maintaining the simplicity of implementation. Finally, the simulation and experimental results are presented to demonstrate the feasibility of the proposed system.

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Casaro, Marcio Mendes, and Denizar Cruz Martins. "Processamento eletrônico da energia solar fotovoltaica em sistemas conectados à rede elétrica." Sba: Controle & Automação Sociedade Brasileira de Automatica 21, no. 2 (April 2010): 159–72. http://dx.doi.org/10.1590/s0103-17592010000200005.

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Este artigo apresenta um sistema fotovoltaico conectado à rede elétrica comercial em configuração centralizada e construído com um inversor trifásico de dois estágios capaz de extrair a máxima potência do arranjo de painéis fotovoltaicos. O algoritmo P&O é adotado como técnica de MPPT. O isolamento é realizado por um transformador de alta frequência. O conversor que compõe o estágio CC-CC dispensa a estrutura de controle, pois funciona com razão cíclica e frequência constantes ao longo de toda a faixa de operação. Isto viabiliza o uso de conversores CC-CC ressonantes, cujo rendimento é elevado em altas frequências, favorecendo a compactação da estrutura de potência. Assim, o conversor trifásico série ressonante é escolhido para compor este estágio. O MPPT é transferido para o estágio CC-CA, que, invariavelmente, possui um controlador para a corrente injetada na rede elétrica. O inversor trifásico PWM alimentado em tensão, que compõe o estágio CC-CA, é controlado e modulado vetorialmente. O controle vetorial impõe a transformação de Park as correntes de linha, de onde resulta a corrente de eixo direto. O MPPT utiliza as mesmas variáveis do controlador de corrente e maximiza a corrente de eixo direto, a qual reflete a potência extraída do arranjo fotovoltaico. Assim, nenhuma medição específica para o MPPT é realizada, resultando em economia de sensores.

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5

C. C. dos Santos, Cássia, Jean Patric da Costa, Carlos Marcelo de Oliveira Stein, Emerson Giovani Carati, Rafael Cardoso, and L. I. Nadal. "CONTROL STRATEGY FOR PHOTOVOLTAIC BOOST CONVERTER OPERATING IN MPPT AND LPPT MODES." Eletrônica de Potência 25, no. 3 (September 15, 2020): 326–36. http://dx.doi.org/10.18618/rep.2020.3.0006.

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6

Mara Vital Barros, Camila, Wellington Santos Mota, Péricles Rezende Barros, and Luciano Sales Barros. "Mppt Of Wind Energy Conversion Systems Based On Pmsg Through Predictive Control." Eletrônica de Potência 20, no. 4 (November 1, 2015): 364–72. http://dx.doi.org/10.18618/rep.2015.4.2553.

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7

Chao, Kuei-Hsiang, and Muhammad Nursyam Rizal. "A Hybrid MPPT Controller Based on the Genetic Algorithm and Ant Colony Optimization for Photovoltaic Systems under Partially Shaded Conditions." Energies 14, no. 10 (May 18, 2021): 2902. http://dx.doi.org/10.3390/en14102902.

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A maximum power point tracking (MPPT) controller was used to make the photovoltaic (PV) module operate at its maximum power point (MPP) under changing temperature and sunlight irradiance. Under partially shaded conditions, the characteristic power–voltage (P–V) curve of the PV modules will have more than one maximum power point, at least one local maximum power point and a global maximum power point. Conventional MPPT controllers may control the PV module array at the local maximum power point rather than the global maximum power point. MPPT control can be also implemented by using soft computing methods (SCM), which can handle the partial shade problem. However, to improve the robustness and speed of the MPPT controller, a hybrid MPPT controller has been proposed that combines two SCMs, the Genetic Algorithm (GA) and Ant Colony Optimization (ACO). Matlab was used in a simulation of a GA-ACO MPPT controller where four SunPower SPR-305NE-WHT-D PV modules with a maximum power of 305.226 W connected in series were used under conditions of partial shade to investigate the performance of the proposed MPPT controller. The results obtained were analyzed and compared with others obtained under perturb and observe (P&O) MPPT and conventional ACO MPPT controllers were observed.

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Al Gizi, Abdullah J. H. "PLC Fuzzy PID Controller of MPPT of Solar Energy Converter." WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL 16 (January 7, 2021): 1–20. http://dx.doi.org/10.37394/23203.2021.16.1.

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Development of the Maximum-Power-Point-Tracking (MPPT) scheme for solar mounts and rectifiers leftovers interesting. We design of high-sensitive fuzzy (HSF) Proportional-Integral-Derivative (PIDC) controller by means of Matlab and Programmable-Logic-Controllers (PLCs) for an adjusted of the MPPT scheme. This proposal is founded on a synergistic mixture of the Radial-Basis-Function-Neural Network (RBF-NN), Genetic Algorithm (GA), and Sugeno-Fuzzy-Logic (SFL) systems. The finest limits of PIDC and MPPT are strong-minded through optimization, wherever RBF-NN is adjusted by means of GA to reach the best key. Also, RBF-NN is rummage-sale to improve the PID limits (got from GA) for scheming HSFL-PIDC of the MPPT scheme. The HSFL-PIDC controller is extra planned to transfer in PLCs (STEP 75.5) for implementing the photovoltaic (PV) scheme. The all-inclusive scheme is extra tuned by solar limits under numerous operational circumstances to advance the solar recital in terms of accusing and correcting. The recital of the planned analog employed MPPT controller is assessed by interfacing it with a hardware prototype of dual photovoltaic (PV) scheme. The mixture controller configured the regulator signal founded on the interaction and in that way reduces the voltage mistake and the oscillation in the voltage regulator process. The achieved scheme is established to be well-organized and robust in refining solar charging and rectifying capability .

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9

González-Castaño, Catalina, Leandro L. Lorente-Leyva, Javier Muñoz, Carlos Restrepo, and Diego H. Peluffo-Ordóñez. "An MPPT Strategy Based on a Surface-Based Polynomial Fitting for Solar Photovoltaic Systems Using Real-Time Hardware." Electronics 10, no. 2 (January 17, 2021): 206. http://dx.doi.org/10.3390/electronics10020206.

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This paper presents an optimal design of a surface-based polynomial fitting for tracking the maximum power point (MPPT) of a photovoltaic (PV) system, here named surface-based polynomial fitting (MPPT-SPF). The procedure of the proposed MPPT-SPF strategy is based on a polynomial model to characterize data from the PV module with a global fit. The advantage of using polynomials is that they provide a good fit within a predefined data range even though they can diverge greatly from that range. The MPPT-SPF strategy is integrated with a DC-DC boost converter to verify its performance and its interaction with different control loops. Therefore, the MPPT strategy is applied to the reference outer PI control loop, which in turn provides the current reference to the inner current loop based on a discrete-time sliding current control. A real-time and high-speed simulator (PLECS RT Box 1) and a digital signal controller (DSC) are used to implement the hardware-in-the-loop system to obtain the results. The proposed strategy does not have a high computational cost and can be implemented in a commercial low-cost DSC (TI 28069M). The proposed MPPT strategy is compared with a conventional perturb and observe method to prove its effectiveness under demanding tests.

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10

Toriki, Mohammad Berel, Muhammad Khamim Asy’ari, and Ali Musyafa’. "Enhanced Performance of PMSG in WECS Using MPPT - Fuzzy Sliding Mode Control." Journal Européen des Systèmes Automatisés 54, no. 1 (February 28, 2021): 85–96. http://dx.doi.org/10.18280/jesa.540110.

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The wind turbine is a tool used to convert wind energy into electrical energy. This research applies the maximum power point tracking (MPPT) algorithm combined with the fuzzy sliding mode control (FSMC) to produce maximum power in the wind turbine. Addition of fuzzy logic algorithm to sliding mode control to reduce the chattering phenomenon caused by the high switching frequency of the MOSFET in the boost converter. The permanent magnet synchronous generator (PMSG) type of generator with a capacity of 600 watts is used to convert the mechanical energy of the turbine into electrical energy. Tracing the maximum power value of the generator with the MPPT-FSMC algorithm in this study based on the value of the generator output voltage, generator output current, and converter output voltage obtained through simulations on MATLAB / SIMULINK. Comparison of wind turbine performance using MPPT-FSMC and without MPPT is shown as validation of improved wind turbine performance when using intelligent control algorithm.

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11

Ammaiyappan, A. Bharathi Sankar, and R. Seyezhai. "Implementation of Fuzzy logic control based MPPT for Photovoltaic system with Silicon Carbide (SiC) boost DC-DC converter." WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL 16 (April 20, 2021): 198–215. http://dx.doi.org/10.37394/23203.2021.16.17.

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In recent days, photovoltaic (PV) system is the most promising renewable energy technologies and the PV cell has to operate at the optimum operating point to deliver maximum power. In order to obtain maximum power from PV, a maximum power point controller is required. This paper presents the simulation and hardware implementation of fuzzy logic (FL) maximum power point (MPPT) controller with FPGA technology for photovoltaic system. The MPPT algorithm is implemented for a Silicon carbide (SiC) MOSFET based boost DC-DC converter which provides fast switching, low losses and high voltage gain. The proposed MPPT algorithm is implemented on a SPARTAN/FPGA board platform based on the model developed and executed in MATLAB/SIMULINK. The entire system designed and implemented to hardware was successfully tested on a laboratory prototype PV array. The experimental results show the effectiveness and feasibility of the proposed controller and the results were satisfactory.

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12

Marhraoui, Saloua. "Fuzzy Sliding Mode Hybrid Control MPPT Strategy and PI Control as a Controller for a Battery Integrated with PV System." Journal of Advanced Research in Dynamical and Control Systems 12, no. 01-Special Issue (February 13, 2020): 415–28. http://dx.doi.org/10.5373/jardcs/v12sp1/20201089.

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13

Chang, En-Chih. "High-Performance Pure Sine Wave Inverter with Robust Intelligent Sliding Mode Maximum Power Point Tracking for Photovoltaic Applications." Micromachines 11, no. 6 (June 11, 2020): 585. http://dx.doi.org/10.3390/mi11060585.

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Photovoltaic (PV) power generation has been extensively used as a result of the limited petrochemical resources and the rise of environmental awareness. Nevertheless, PV arrays have a widespread range of voltage changes in a variety of solar radiation, load, and temperature circumstances, so a maximum power point tracking (MPPT) method must be applied to get maximum power from PV systems. Sliding mode control (SMC) is effectively used in PV power generation due to its robustness, design simplicity, and superior interference suppression. When the PV array is subject to large parameter changes/highly uncertain conditions, the SMC leads to degraded steady-state performance, poor transient tracking speed, and unwanted flutter. Therefore, this paper proposes a robust intelligent sliding mode MPPT-based high-performance pure sine wave inverter for PV applications. The robust SMC is designed through fast sliding regime, which provides fixed time convergence and a non-singularity that allows better response in steady-state and transience. To avoid the flutter caused by system unmodeled dynamics, an enhanced cuckoo optimization algorithm (ECOA) with automatically adjustable step factor and detection probability is used to search control parameters of the robust sliding mode, thus finding global optimal solutions. The coalescence of both robust SMC and ECOA can control the converter to obtain MPPT with faster convergence rate and without untimely trapping at local optimal solutions. Then the pure sine wave inverter with robust intelligent sliding mode MPPT of the PV system delivers a high-quality and stable sinusoidal wave voltage to the load. The efficacy of the proposed method is validated on a MPPT pure sine wave inverter system by using numerical simulations and experiments. The results show that the output of the proposed PV system can improve steady-state performance and transient tracking speed.

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Gil-Velasco, Alfredo, and Carlos Aguilar-Castillo. "A Modification of the Perturb and Observe Method to Improve the Energy Harvesting of PV Systems under Partial Shading Conditions." Energies 14, no. 9 (April 28, 2021): 2521. http://dx.doi.org/10.3390/en14092521.

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There are multiples conditions that lead to partial shading conditions (PSC) in photovoltaic systems (PV). Under these conditions, the harvested energy decreases in the PV system. The maximum power point tracking (MPPT) controller aims to harvest the greatest amount of energy even under partial shading conditions. The simplest available MPPT algorithms fail on PSC, whereas the complex ones are effective but require high computational resources and experience in this type of systems. This paper presents a new MPPT algorithm that is simple but effective in tracking the global maximum power point even in PSC. The simulation and experimental results show excellent performance of the proposed algorithm. Additionally, a comparison with a previously proposed algorithm is presented. The comparison shows that the proposal in this paper is faster in tracking the maximum power point than complex algorithms.

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15

Brito, Moacyr A. G. de, Victor A. Prado, Edson A. Batista, Marcos G. Alves, and Carlos A. Canesin. "Design Procedure to Convert a Maximum Power Point Tracking Algorithm into a Loop Control System." Energies 14, no. 15 (July 27, 2021): 4550. http://dx.doi.org/10.3390/en14154550.

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This paper presents a novel complete design procedure to convert a maximum power point tracking (MPPT) algorithm into a control system. The MPPT algorithm can be tuned by employing any control system design. In this paper, we adopted Bode diagrams using the criteria of module and phase as the power electronics specialists are habituated with such concepts. The MPPT control transfer functions were derived using the average state equations and small-signal analysis. The control loops were derived for power and voltage control loops. The design procedure was applied to the well-known perturb and observe (P&O) and incremental conductance (IC) algorithms, returning the P&O based on PI and IC based on PI algorithms. Such algorithms were evaluated through simulation and experimental results. Additionally, we showed that the proposed design methodology can optimize energy harvesting, allowing algorithms to have outstanding tracking factors (above 99%) and adaptability characteristics.

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Angadi, Sachin, Udaykumar R. Yaragatti, Yellasiri Suresh, and A. B. Raju. "System Parameter Based Performance Optimization of Solar PV Systems with Perturbation Based MPPT Algorithms." Energies 14, no. 7 (April 5, 2021): 2007. http://dx.doi.org/10.3390/en14072007.

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Maximum power point tracking (MPPT) algorithms are invariably employed to utilize solar photovoltaic (PV) systems effectively. Perturbation based MPPT algorithms are popular due to their simplicity and reasonable efficiency. While novel MPPT algorithms claim increased energy utilization over classic perturbation techniques, their performance is governed by the choice of optimal algorithm parameters. Existing guidelines for parameter optimization are mathematically laborious and are not generic. Hence, this paper aims to provide simple and comprehensive guidelines to ensure optimal performance from the perturbation based MPPT technique. For an illustration of proposed claims, a solar PV fed boost converter is investigated to examine the effect of input capacitor, digital filter cut-off frequency, system time constant and sampling time on implementing a classic Perturb and Observe (P and O) algorithm. The readers will be presented with two simple step tests (to determine the effective system time constant) and proposed guidelines to choose the optimal performance sampling time. Necessary laboratory experiments show that an appropriate choice of sampling time could increase efficiency and ensure system stability. This investigation’s learnings can be easily extended to any power electronics converter, loads and all perturbation-based algorithms used in solar PV systems. The results of appropriate tests on the system’s mathematical model and the laboratory prototype are presented in detail to support this research’s claims.

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Beck, Y., and N. Sober. "Experimental Verification and Comparative Study of Various MPPT Algorithms." Automatika 57, no. 2 (January 2016): 343–53. http://dx.doi.org/10.7305/automatika.2016.10.1101.

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18

Paz, Francisco, and Martin Ordonez. "Zero Oscillation and Irradiance Slope Tracking for Photovoltaic MPPT." IEEE Transactions on Industrial Electronics 61, no. 11 (November 2014): 6138–47. http://dx.doi.org/10.1109/tie.2014.2311414.

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19

Cortés, Baldwin, Roberto Tapia, and Juan J. Flores. "System-Independent Irradiance Sensorless ANN-Based MPPT for Photovoltaic Systems in Electric Vehicles." Energies 14, no. 16 (August 7, 2021): 4820. http://dx.doi.org/10.3390/en14164820.

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The integration of photovoltaic systems (PVS) in electric vehicles (EV) increases the vehicle’s autonomy by providing an additional energy source other than the battery. However, current solar cell technology generates around 200 W for a 1.4 m2 panel (to be installed on the roof of the EV) at stable irradiance conditions. This limitation in production and the sudden changes in irradiance produced by shadows of clouds, buildings, and other structures make developing a fast and efficient maximum power point tracking (MPPT) technique in this area necessary. This article proposes an artificial neural network (ANN)-based MPPT, called DS-ANN, that uses manufacturer datasheet parameters as inputs to the network to address this problem. The Bayesian backpropagation-regularization performs the training, ensuring that the MPPT technique operates satisfactorily on different PVS without retraining. We simulated the response of 20 commercial modules against actual irradiance data to validate the proposed method. The results show that our method achieves an average tracking efficiency of 99.66%, improving by 1.21% over an enhanced P&O method.

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Bakkar, Mostafa, Ahmed Aboelhassan, Mostafa Abdelgeliel, and Michael Galea. "PV Systems Control Using Fuzzy Logic Controller Employing Dynamic Safety Margin under Normal and Partial Shading Conditions." Energies 14, no. 4 (February 5, 2021): 841. http://dx.doi.org/10.3390/en14040841.

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Because of the unpredictable activity of solar energy sources, photovoltaic (PV) maximum power point tracking (MPPT) is essential to guarantee the continuous operation of electrical energy generation at optimal power levels. Several works have extensively examined the generation of the maximum power from the PV systems under normal and shading conditions. The fuzzy logic control (FLC) method is one of the effective MPPT techniques, but it needs to be adapted to work in partial shading conditions. The current paper presents the FLC-based on dynamic safety margin (DSM) as an MPPT technique for a PV system to overcome the limitations of FLC in shading conditions. The DSM is a performance index that measures the system state deviation from the normal situation. As a performance index, DSM is used to adapt the FLC controller output to rapidly reach the global maxima of the PV system. The ability of the proposed algorithm and its performance are evaluated using simulation and practical implementation results for single phase grid-connected PV system under normal and partial shading operating conditions.

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21

Otmani, F. El, A. Abouloifa, M. Aourir, I. Lachkar, FZ Assad, F. Giri, and JM Guerrero. "MPPT Based Sliding Mode Control for Fuel Cell Connected Grid System." IFAC-PapersOnLine 53, no. 2 (2020): 13322–27. http://dx.doi.org/10.1016/j.ifacol.2020.12.165.

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22

Wu, Zhongqiang, Danqi Yu, and Xiaohua Kang. "Application of improved chicken swarm optimization for MPPT in photovoltaic system." Optimal Control Applications and Methods 39, no. 2 (January 5, 2018): 1029–42. http://dx.doi.org/10.1002/oca.2394.

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23

Benbouhenni, Habib, and Nicu Bizon. "A Synergetic Sliding Mode Controller Applied to Direct Field-Oriented Control of Induction Generator-Based Variable Speed Dual-Rotor Wind Turbines." Energies 14, no. 15 (July 22, 2021): 4437. http://dx.doi.org/10.3390/en14154437.

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A synergetic sliding mode (SSM) approach is designed to address the drawbacks of the direct field-oriented control (DFOC) of the induction generators (IGs) integrated into variable speed dual-rotor wind power (DRWP) systems with the maximum power point tracking (MPPT) technique. Using SSM controllers in the DFOC strategy, the active power, electromagnetic torque, and reactive power ripples are reduced compared to traditional DFOC using proportional-integral (PI) controllers. This proposed strategy, associated with SSM controllers, produces efficient state estimation. The effectiveness of the designed DFOC strategy has been evaluated on variable speed DRWP systems with the MPPT technique.

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Marhraoui, Saloua. "Comparing Fuzzy Logic and P&O MPPT Methods for PV System and PI Control Like a Load Controller." Journal of Advanced Research in Dynamical and Control Systems 12, no. 01-Special Issue (February 13, 2020): 452–60. http://dx.doi.org/10.5373/jardcs/v12sp1/20201092.

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25

Sun, Yuliang, Shaomin Yan, Bin Cai, Yuqiang Wu, and Zhongcai Zhang. "MPPT Adaptive Controller of DC-based DFIG in Resistances Uncertainty." International Journal of Control, Automation and Systems 19, no. 8 (June 16, 2021): 2734–46. http://dx.doi.org/10.1007/s12555-020-0302-3.

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de Brito, Moacyr Aureliano Gomes, Marcos G. Alves, and Carlos A. Canesin. "Hybrid MPPT Solution for Double-Stage Photovoltaic Inverter." Journal of Control, Automation and Electrical Systems 30, no. 2 (February 8, 2019): 253–65. http://dx.doi.org/10.1007/s40313-019-00447-0.

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27

Manganiello, Patrizio, Mattia Ricco, Giovanni Petrone, Eric Monmasson, and Giovanni Spagnuolo. "Optimization of Perturbative PV MPPT Methods Through Online System Identification." IEEE Transactions on Industrial Electronics 61, no. 12 (December 2014): 6812–21. http://dx.doi.org/10.1109/tie.2014.2317143.

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28

Oh, Taeho, Dilruba Parvin, Omiya Hassan, Samira Shamsir, and Syed Kamrul Islam. "MPPT integrated DC–DC boost converter for RF energy harvester." IET Circuits, Devices & Systems 14, no. 7 (October 1, 2020): 1086–91. http://dx.doi.org/10.1049/iet-cds.2019.0509.

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Lakshmi, B., and M. S. Sujatha. "Various MPPT Methods to Improve the Solar PV System Efficiency – A Review." International Journal of Control and Automation 12, no. 12 (December 31, 2019): 23–32. http://dx.doi.org/10.33832/ijca.2019.12.12.03.

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Silva, Sergio, Leonardo Sampaio, Fernando Oliveira, and Fábio Durand. "Pso-based Mppt Technique Applied To A Grid-tied Pv System With Active Power Line Conditioning Using A Feed-forward Dc-bus Control Loop." Eletrônica de Potência 21, no. 2 (May 1, 2016): 105–16. http://dx.doi.org/10.18618/rep.2016.2.2615.

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Bijukumar, Bepinkumar, Arunadevi Ganesan Kaushik Raam, Saravana Ilango Ganesan, Chilakapati Nagamani, and Maddikara Jaya Bharata Reddy. "MPPT algorithm for thermoelectric generators based on parabolic extrapolation." IET Generation, Transmission & Distribution 13, no. 6 (March 26, 2019): 821–28. http://dx.doi.org/10.1049/iet-gtd.2017.2007.

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32

Kasa, N., T. Iida, and L. Chen. "Flyback Inverter Controlled by Sensorless Current MPPT for Photovoltaic Power System." IEEE Transactions on Industrial Electronics 52, no. 4 (August 2005): 1145–52. http://dx.doi.org/10.1109/tie.2005.851602.

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Mamarelis, Emilio, Giovanni Petrone, and Giovanni Spagnuolo. "Design of a Sliding-Mode-Controlled SEPIC for PV MPPT Applications." IEEE Transactions on Industrial Electronics 61, no. 7 (July 2014): 3387–98. http://dx.doi.org/10.1109/tie.2013.2279361.

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Renaudineau, Hugues, Fabrizio Donatantonio, Julien Fontchastagner, Giovanni Petrone, Giovanni Spagnuolo, Jean-Philippe Martin, and Serge Pierfederici. "A PSO-Based Global MPPT Technique for Distributed PV Power Generation." IEEE Transactions on Industrial Electronics 62, no. 2 (February 2015): 1047–58. http://dx.doi.org/10.1109/tie.2014.2336600.

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Abdel-Rahim, Omar, Nehmido Alamir, Mohamed Orabi, and Mohamed Ismeil. "Fixed-frequency phase-shift modulated PV-MPPT for LLC resonant converters." Journal of Power Electronics 20, no. 1 (December 9, 2019): 279–91. http://dx.doi.org/10.1007/s43236-019-00001-w.

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Urtasun, Andoni, Pablo Sanchis, and Luis Marroyo. "Small Wind Turbine Sensorless MPPT: Robustness Analysis and Lossless Approach." IEEE Transactions on Industry Applications 50, no. 6 (November 2014): 4113–21. http://dx.doi.org/10.1109/tia.2014.2313650.

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Seguel, Julio López, and Seleme I. Seleme. "Robust Digital Control Strategy Based on Fuzzy Logic for a Solar Charger of VRLA Batteries." Energies 14, no. 4 (February 14, 2021): 1001. http://dx.doi.org/10.3390/en14041001.

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This paper presents the design and implementation of a digital control strategy for a Buck converter, used as a solar charger of valve-regulated lead acid (VRLA) batteries. The control system consists of two fuzzy logic controllers (FLCs), which adjust the appropriate increment of the converter duty cycle based on battery state of charge according to a three-stage charging scheme. One FLC works as a maximum power point tracker (FLC-MPPT), while the other regulates the battery voltage (FLC-VR). This approach of using two different set of membership functions overcomes the limitations of the battery chargers with a single control function, where the voltage supplied to the battery is either not constant due to the operation of the MPPT algorithm (possibly damaging the battery) or is constant due to the operation of the voltage control (hence, MPP cannot be achieved). In this way, the proposed control approach has the advantage of extracting the maximum energy of the PV panel, preventing battery damage caused by variable MPPT voltage, thereby extending the battery’s lifetime. Moreover, it allows overcoming of the drawbacks of the conventional solar chargers, which become slow or inaccurate during abrupt changes in weather conditions. The strategy is developed to be implemented in a low-cost AT91SAM3X8E Arduino Due microcontroller. Simulations by MATLAB/Simulink and experimental results from hardware implementation are provided and discussed, which validate the reliability and robustness of the control strategy.

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N. M. Alahmadi, A., and Hegazy Rezk. "A Robust Single-Sensor MPPT Strategy for Shaded Photovoltaic-Battery System." Computer Systems Science and Engineering 37, no. 1 (2021): 63–71. http://dx.doi.org/10.32604/csse.2021.015029.

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Abderrahim, Zemmit, Herraguemi Kamel Eddine, and Messalti Sabir. "A New Improved Variable Step Size MPPT Method for Photovoltaic Systems Using Grey Wolf and Whale Optimization Technique Based PID Controller." Journal Européen des Systèmes Automatisés 54, no. 1 (February 28, 2021): 175–85. http://dx.doi.org/10.18280/jesa.540120.

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In this work, we have developed two new intelligent maximum power point tracking (MPPT) techniques for photovoltaic (PV) solar systems. To optimize the PWM duty cycle driving the DC/DC boost converter, we have used two optimization algorithms namely the whale optimization algorithm (WOA) and grey wolf optimization (GWO) so we can tune the PID controller gains. The oscillation around the MPP and the fail accuracy under fast variable isolation are among the well-known drawbacks of conventional MPPT algorithms. To overcome these two drawbacks, we have formulated a new objective fitness function that includes WOA/GWO based accuracy, ripple, and overshoot. To provide the most relevant variable step size, this objective fitness function was optimized using the two aforementioned optimization algorithms (i.e., WOA and GWO). We have carried out several tests on Solarex MSX-150 panel and DC/DC boost converter based PV systems. In the simulation results section, we can clearly see that the two proposed algorithms perform better than the conventional ones in term of power overshoot, ripple and the response time.

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Tchouani Njomo, Arnaud Flanclair, Lionel Leroy Sonfack, Rostand Marc Douanla, and Godpromesse Kenne. "Nonlinear Neuro-Adaptive Control for MPPT Applied to Photovoltaic Systems." Journal of Control, Automation and Electrical Systems 32, no. 3 (February 9, 2021): 693–702. http://dx.doi.org/10.1007/s40313-021-00691-3.

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Algarín, Carlos Robles, Roberto Liñán Fuentes, and Adalberto Ospino Castro. "Implementation of a cost-effective fuzzy MPPT controller on the Arduino board." International Journal on Smart Sensing and Intelligent Systems 11, no. 1 (February 28, 2018): 1–10. http://dx.doi.org/10.21307/ijssis-2018-002.

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Zurbriggen, Ignacio Galiano, and Martin Ordonez. "PV Energy Harvesting Under Extremely Fast Changing Irradiance: State-Plane Direct MPPT." IEEE Transactions on Industrial Electronics 66, no. 3 (March 2019): 1852–61. http://dx.doi.org/10.1109/tie.2018.2838115.

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Carannante, G., C. Fraddanno, M. Pagano, and L. Piegari. "Experimental Performance of MPPT Algorithm for Photovoltaic Sources Subject to Inhomogeneous Insolation." IEEE Transactions on Industrial Electronics 56, no. 11 (November 2009): 4374–80. http://dx.doi.org/10.1109/tie.2009.2019570.

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Xu, Zhongyan, Shengyu Tao, Hongtao Fan, Jie Sun, and Yaojie Sun. "Power Limit Control Strategy for Household Photovoltaic and Energy Storage Inverter." Electronics 10, no. 14 (July 16, 2021): 1704. http://dx.doi.org/10.3390/electronics10141704.

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The increased installation capacity of grid-connected household photovoltaic (PV) systems has been witnessed worldwide, and the power grid is facing the challenges of overvoltage during peak power generation and limited frequency regulation performance. With the dual purpose of enhancing the power grid safety and improving the PV utilization rate, the maximum feed-in active power can be regulated by modifying the maximum power point tracking (MPPT) algorithm and battery energy storage (BES) accessibility as control instructions. However, the existing methods not only waste installed PV capacity, but it becomes no longer accessible when the state of charge (SOC) of the BES approaches its upper limit. In response to the above problem, this paper proposes a power limit control strategy to coordinate the MPPT algorithm and the BES accessibility. The proposed strategy directly controls the inverter output current according to the power limit instructions from the electric operation control centers, leading to a bus voltage difference. The difference serves as a control signal for BES and PV. Under a power-limiting scenario, priority is given to power regulation through energy storage to absorb the limited active power. When the SOC of the BES reaches the upper limit of charging, modification of the PV MPPT algorithm facilitates the inverter output power to meet the power limit requirements. To further verify the effectiveness of the proposed power limit control strategy, both simulation and experimental studies are conducted, which consistently indicated a synchronized inverter current with grid voltage and a rapid power response of the power-limiting instruction within 0.2 s. The power limit control strategy not only improves the PV energy utilization but also supports the safe and reliable operation of the power gird in the context of soaring renewable energy penetration.

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Muñoz, Eduardo, Edy Ayala, and Nicolás Pozo. "Estrategia de Control Fuzzy PI en una Turbina Eólica con Generador de Inducción Doblemente Alimentado para Maximizar la Extracción de Potencia en Presencia de Perturbaciones." Revista Técnica "energía" 18, no. 1 (July 29, 2021): 1–10. http://dx.doi.org/10.37116/revistaenergia.v17.n2.2021.428.

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Esta investigación propone una metodología de control aplicada a una técnica en Sistemas de Generación de Energía Eólica (WEGS) para el Seguimiento del Punto de Máxima Potencia (MPPT) basada en un observador Fuzzy y complementada con un controlador PI mediante el método de Control Directo de Velocidad (DSC). Este enfoque permite controlar la corriente de referencia del lado del rotor a través de las variaciones de par y potencia eléctrica en un modelo de Generador de Inducción Doblemente Alimentado (DFIG). En consecuencia, la velocidad del generador se controla para obtener una respuesta rápida del máximo Coeficiente de Potencia (). La construcción de esta estrategia comienza con mediciones directas de las variables eléctricas y mecánicas utilizando herramientas computacionales como FAST y Matlab-Simulink para las simulaciones del modelo del aerogenerador. Esta estrategia DSC presenta un rápido desempeño en el seguimiento del considerando la dinámica de un aerogenerador de 1,5MW; esta estrategia ha sido comparada con un controlador PI tradicional mejorando la extracción de la potencia de salida.

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Sunarno, Epyk, Ramadhan Bilal Assidiq, Syechu Dwitya Nugraha, Indhana Sudiharto, Ony Asrarul Qudsi, and Rachma Prilian Eviningsih. "Application of the Artificial Neural Network (ANN) Method as MPPT Photovoltaic for DC Source Storage." International Review of Automatic Control (IREACO) 12, no. 3 (May 31, 2019): 145. http://dx.doi.org/10.15866/ireaco.v12i3.16455.

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Babes, Badreddine, Amar Boutaghane, Noureddine Hamouda, Sami Kahla, Ahmed Kellai, Thomas Ellinger, and Jürgen Petzoldt. "New Optimal Control of Permanent Magnet DC Motor for Photovoltaic Wire Feeder Systems." Journal Européen des Systèmes Automatisés 53, no. 6 (December 23, 2020): 811–23. http://dx.doi.org/10.18280/jesa.530607.

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This article aims to improve the permanent magnet DC (PMDC) motor performance for photovoltaic (PV) wire-feeder systems (PVWFSs) of arc welding machines. The considered technique is designed by direct speed control based on optimal Fractional-order Fuzzy PID FO-Fuzzy-PID controller. The purpose is to ensure optimal control of wire feed speed reference to reduce torque ripples and hence, the performance of the WFS is improved. The dynamic reaction of the proposed solar PVWFS relies upon the scaling factors of FO-Fuzzy-PID controller, which are optimized by using teaching-learning algorithm based on Particle Swarm Optimization (PSO) method. The maximum power point tracking (MPPT) is achieved using an intelligent FO-Fuzzy-PID current controller based Perturb and Observe (P&O) MPPT algorithm. The PVWFS system incorporating the proposed method is tested and compared with the conventional PID control scheme under different weather conditions. The simulation of the proposed system by MATLAB\SIMULINK is carried out. The simulation results indicate the effectiveness of the considered control strategy in terms of the reduction in torque oscillations, optimizing electrical power and wire feed speed.

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Kariem, Habib, Ezzedine Touti, and Tamer Fetouh. "The efficiency of PSO-based MPPT technique of an electric vehicle within the city." Measurement and Control 53, no. 3-4 (January 7, 2020): 461–73. http://dx.doi.org/10.1177/0020294019882973.

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Electrical vehicle fed by photovoltaic energy represents a complex system, which needs a high-performance control algorithm. Regarding the real situations, mostly the electric vehicle will be moving inside the city. If this system is covered by photovoltaic cells, the efficiency of this renewable energy source will depend on various factors. The shade areas or sunlight zones which exist in the city make the solar system unstable. Resolving this problem can increase the battery autonomy and allow addition of some running kilometers to the vehicle. Based on this objective, this study deals with the problem of solar variation and its influence on vehicle efficiency within the city. The problem is how to extract the maximum energy in this case. In order to maximize the global energy performance and increase vehicle autonomy, the optimal control method will be applied to this photovoltaic system taking into account some performance indicators such as the obtained power, the tracking speed, and the chattering level. Therefore, this study explores two control techniques in order to extract the maximum power from the solar energy system, which are the incremental method and the particle swarm optimization method. Simulink/MATLAB tool is used for simulation and comparison study based on the offered performance indicators. The obtained results show that the particle swarm optimization method has high global performance and an energy gain is obtained.

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Anh Nguyen, Tuan Ngoc, Duy Cong Pham, Nguyen Huu, Chan Thanh, and Anh Ngoc Nguyen. "Implementation of Equilibrium Optimizer Algorithm for MPPT in a wind turbine with PMSG." WSEAS TRANSACTIONS ON SYSTEMS AND CONTROL 16 (April 21, 2021): 216–23. http://dx.doi.org/10.37394/23203.2021.16.18.

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This paper proposes a new equilibrium optimizer algorithm to extracting the maximum power point tracking which is proposed in permanent magnet synchronous generator under randomly different varying wind speed conditions. It was inspired by controlled volume mass balance modes for estimating dynamic and equilibrium states. The equilibrium optimizer algorithm can mutate the random solving a problem via exploration and exploitation. A particle with its concentration updates its concentration with particular terms. It defined as best-so-far solution, called the equilibrium candidate and the other is equilibrium state, which encourages a particle to global search the domain. The tracking performances of equilibrium optimizer algorithm based trackers firstly are evaluated based on MATLAB software. Results of equilibrium optimizer are compared to two categories of existing optimization methods, including the most well-known genetic algorithm, particle swarm optimization. The performance of the equilibrium optimizer algorithm is analyzed, evaluated and compared based on some key parameters, which are the active power, and turbine power factor under randomly different varying wind speed conditions. Additionally, the obtained results show that the equilibrium optimizer tracker has superiority compared with in all the studied cases

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Juma, Mwaka I., Bakari M. M. Mwinyiwiwa, Consalva J. Msigwa, and Aviti T. Mushi. "Design of a Hybrid Energy System with Energy Storage for Standalone DC Microgrid Application." Energies 14, no. 18 (September 21, 2021): 5994. http://dx.doi.org/10.3390/en14185994.

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This paper presents microgrid-distributed energy resources (DERs) for a rural standalone system. It is made up of a solar photovoltaic (solar PV) system, battery energy storage system (BESS), and a wind turbine coupled to a permanent magnet synchronous generator (WT-PMSG). The DERs are controlled by maximum power point tracking (MPPT)-based proportional integral (PI) controllers for both maximum power tracking and error feedback compensation. The MPPT uses the perturb and observe (P&O) algorithm for tracking the maximum power point of the DERs. The PI gains are tuned using the Ziegler–Nichols method. The developed system was built and simulated in MATLAB/Simulink under two conditions—constant load, and step-load changes. The controllers enabled the BESS to charge even during conditions of varying load and other environmental factors such as change of irradiance and wind speed. The reference was tracked extremely well by the output voltage of the DC microgrid. This is useful research for electrifying the rural islanded areas which are too far from the grid.

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