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Journal articles on the topic 'Sensorless maximum power point tracking'

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Published: 5 June 2025

Last updated: 15 July 2025

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El Fadil, H., and F. Giri. "Climatic sensorless maximum power point tracking in PV generation systems." Control Engineering Practice 19, no. 5 (2011): 513–21. http://dx.doi.org/10.1016/j.conengprac.2011.01.010.

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Veligorskyi, Oleksandr, Oleksandr Husev, Viktor Shevchenko, et al. "A novel hysteresis power point optimizer for distributed solar power generation." Electrical, Control and Communication Engineering 14, no. 1 (2018): 12–22. http://dx.doi.org/10.2478/ecce-2018-0002.

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Abstract This paper proposes a new photovoltaic panel maximum-power-point optimizer based on a buck converter. It can be connected to the DC-link distributed energy harvesting system that should perform the true maximum-power-point tracking algorithm based on maintaining a constant DC link voltage. The algorithm is based on the sensorless hysteresis control and ensures high efficiency. Three different realizations of proposed hysteresis optimizers have been analyzed in the paper, including operation principle and adjustment of hysteresis intervals. An experimental study has been performed for a portable low-power photovoltaic system in case of different loads and irradiance levels. The efficiency of maximum power point tracking has been calculated analytically for different hysteresis intervals and validated by experiment, which proved a 97-98 % efficiency of tracking for different PV panel temperatures. The proposed solution is recommended to be used in small- and medium-sized power systems where the price of the conventional maximum power point tracking converter is very high and is comparable to the cost of the individual panel

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Babes, B., N. Hamouda, S. Kahla, H. Amar, and S. S. M. Ghoneim. "Fuzzy model based multivariable predictive control design for rapid and efficient speed-sensorless maximum power extraction of renewable wind generators." Electrical Engineering & Electromechanics, no. 3 (May 30, 2022): 51–62. http://dx.doi.org/10.20998/2074-272x.2022.3.08.

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Introduction. A wind energy conversion system needs a maximum power point tracking algorithm. In the literature, several works have interested in the search for a maximum power point wind energy conversion system. Generally, their goals are to optimize the mechanical rotation or the generator torque and the direct current or the duty cycle switchers. The power output of a wind energy conversion system depends on the accuracy of the maximum power tracking controller, as wind speed changes constantly throughout the day. Maximum power point tracking systems that do not require mechanical sensors to measure the wind speed offer several advantages over systems using mechanical sensors. The novelty. The proposed work introduces an intelligent maximum power point tracking technique based on a fuzzy model and multivariable predictive controller to extract the maximum energy for a small-scale wind energy conversion system coupled to the electrical network. The suggested algorithm does not need the measurement of the wind velocity or the knowledge of turbine parameters. Purpose. Building an intelligent maximum power point tracking algorithm that does not use mechanical sensors to measure the wind speed and extracts the maximum possible power from the wind generator, and is simple and easy to implement. Methods. In this control approach, a fuzzy system is mainly utilized to generate the reference DC-current corresponding to the maximum power point based on the changes in the DC-power and the rectified DC-voltage. In contrast, the fuzzy model-based multivariable predictive regulator follows the resultant reference current with minimum steady-state error. The significant issues of the suggested maximum power point tracking method, such as the detailed design process and implementation of the two controllers, have been thoroughly investigated and presented. The considered maximum power point tracking approach has been applied to a wind system driving a 5 kW permanent magnet synchronous generator in variable speed mode through the simulation tests. Practical value. A practical implementation has been executed on a 5 kW test bench consisting of a dSPACEds1104 controller board, permanent magnet synchronous generator, and DC-motor drives to confirm the simulation results. Comparative experimental results under varying wind speed have confirmed the achievable significant performance enhancements on the maximum wind energy generation and overall system response by using the suggested control method compared with a traditional proportional integral maximum power point tracking controller.

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B., Babes, Hamouda N., Kahla S., Amar H., and S. M. Ghoneim S. "Fuzzy model based multivariable predictive control design for rapid and efficient speed-sensorless maximum power extraction of renewable wind generators." Electrical Engineering & Electromechanics, no. 3 (May 30, 2022): 51–62. https://doi.org/10.20998/2074-272X.2022.3.08.

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Introduction. A wind energy conversion system needs a maximum power point tracking algorithm. In the literature, several works have interested in the search for a maximum power point wind energy conversion system. Generally, their goals are to optimize the mechanical rotation or the generator torque and the direct current or the duty cycle switchers. The power output of a wind energy conversion system depends on the accuracy of the maximum power tracking controller, as wind speed changes constantly throughout the day. Maximum power point tracking systems that do not require mechanical sensors to measure the wind speed offer several advantages over systems using mechanical sensors. The novelty. The proposed work introduces an intelligent maximum power point tracking technique based on a fuzzy model and multivariable predictive controller to extract the maximum energy for a small-scale wind energy conversion system coupled to the electrical network. The suggested algorithm does not need the measurement of the wind velocity or the knowledge of turbine parameters. Purpose. Building an intelligent maximum power point tracking algorithm that does not use mechanical sensors to measure the wind speed and extracts the maximum possible power from the wind generator, and is simple and easy to implement. Methods. In this control approach, a fuzzy system is mainly utilized to generate the reference DC-current corresponding to the maximum power point based on the changes in the DC-power and the rectified DC-voltage. In contrast, the fuzzy model-based multivariable predictive regulator follows the resultant reference current with minimum steady-state error. The significant issues of the suggested maximum power point tracking method, such as the detailed design process and implementation of the two controllers, have been thoroughly investigated and presented. The considered maximum power point tracking approach has been applied to a wind system driving a 5 kW permanent magnet synchronous generator in variable speed mode through the simulation tests. Practical value. A practical implementation has been executed on a 5 kW test bench consisting of a dSPACEds1104 controller board, permanent magnet synchronous generator, and DC-motor drives to confirm the simulation results. Comparative experimental results under varying wind speed have confirmed the achievable significant performance enhancements on the maximum wind energy generation and overall system response by using the suggested control method compared with a traditional proportional integral maximum power point tracking controller.

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Stitou, Mohamed, Abderrahim El Fadili, Fatima Zahra Chaoui, and Fouad Giri. "Output feedback control of sensorless photovoltaic systems, with maximum power point tracking." Control Engineering Practice 84 (March 2019): 1–12. http://dx.doi.org/10.1016/j.conengprac.2018.10.020.

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Chen, Chiung Hsing, Chih-Ming Hong, and Fu-Sheng Cheng. "Intelligent speed sensorless maximum power point tracking control for wind generation system." International Journal of Electrical Power & Energy Systems 42, no. 1 (2012): 399–407. http://dx.doi.org/10.1016/j.ijepes.2012.04.019.

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Albatran, Saher, and Omar Assad. "Online adaptive master maximum power point tracking algorithm and sensorless weather estimation." Energy Systems 11, no. 1 (2018): 73–93. http://dx.doi.org/10.1007/s12667-018-0313-9.

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Martines, Guilherme M. S., Moacyr A. G. De Brito, Edson A. Batista, Ruben B. Godoy, and Tiago H. A. Mateus. "Sensorless MPPT Algorithms for PV Systems in Partially Shaded Scenarios." Eletrônica de Potência 29 (December 3, 2024): e202452. https://doi.org/10.18618/rep.e202452.

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This manuscript presents current sensorless algorithms for maximum power point tracking (MPPT) in partially shaded photovoltaic (PV) systems. The necessity of a current sensor is eliminated with the use of mathematical modeling of the power electronics converter. This approach significantly reduces the implementation cost and the inherent disadvantages in the current sensor circuitry. MPPT techniques based on soft computing are employed, in addition to Perturb and Observe (P&O), due to their ability to explore a larger search space. This feature is advantageous because it minimizes convergence risk to a local maximum, a limitation of traditional techniques. Simulation and experimental results are presented and each algorithm is evaluated through different metrics, such as search time for the global maximum power point (GMPP) and efficiency. The tests consider dynamic irradiance profiles, producing a tracking factor (TF) above 99% and a remarkable fast convergence time.

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Phillips-Brenes, Hayden, Roberto Pereira-Arroyo, Renato Rímolo-Donadío, and Mauricio Muñoz-Arias. "Current-Sensorless Control Strategy for the MPPT of a PV Cell: An Energy-Based Approach." International Journal of Photoenergy 2022 (September 10, 2022): 1–17. http://dx.doi.org/10.1155/2022/1747533.

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A novel energy-based modelling and control strategy is developed and implemented to solve the maximum power point tracking problem when a photovoltaic cell array is connected to consumption loads. A mathematical model that contains key characteristic parameters of an energy converter stage connected to a photovoltaic cell array is proposed and recast using the port-Hamiltonian framework. The system consists of input-output power port pairs and storage and dissipating elements. Then, a current-sensorless control loop for a maximum power point tracking is designed, acting over the energy converter stage and following an interconnection and damping assignment passivity-based strategy. The performance of the proposed strategy is compared to a (classical) sliding mode control law. Our energy-based strategy is implemented in a hardware platform with a sampling rate of 122 Hz, resulting in lower dynamic power consumption compared to other maximum power point tracking control strategies. Numerical simulations and experimental results validate the performance of the proposed energy-based modelling and the novel control law approach.

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Luo, Xiang, and Shuangxia Niu. "Maximum Power Point Tracking Sensorless Control of an Axial-Flux Permanent Magnet Vernier Wind Power Generator." Energies 9, no. 8 (2016): 581. http://dx.doi.org/10.3390/en9080581.

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de Brito, Moacyr A. G., Guilherme M. S. Martines, Anderson S. Volpato, Ruben B. Godoy, and Edson A. Batista. "Current Sensorless Based on PI MPPT Algorithms." Sensors 23, no. 10 (2023): 4587. http://dx.doi.org/10.3390/s23104587.

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This paper presents novel current sensorless maximum-power point-tracking (MPPT) algorithms based on compensators/controllers and a single-input voltage sensor. The proposed MPPTs eliminate the expensive and noisy current sensor, which can significantly reduce the system cost and retain the advantages of the widely used MPPT algorithms, such as Incremental Conductance (IC) and Perturb and Observe (P&O) algorithms. Additionally, it is verified that the proposed algorithms, especially the proposed Current Sensorless V based on PI, can reach outstanding tracking factors (TFs) such as the IC and P&O based on PI algorithms. In this sense, the insertion of controllers inside the MPPT gives them adaptive characteristics, and the experimental TFs are in the remarkable range of more than 99%, with an average yield of 99.51% and a peak of 99.80%.

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Senjyu, Tomonobu, Satoshi Tamaki, Endusa Muhando, et al. "Wind velocity and rotor position sensorless maximum power point tracking control for wind generation system." Renewable Energy 31, no. 11 (2006): 1764–75. http://dx.doi.org/10.1016/j.renene.2005.09.020.

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Linus, Rajin M., and Perumal Damodharan. "Wind Velocity Sensorless Maximum Power Point Tracking Algorithm in Grid-connected Wind Energy Conversion System." Electric Power Components and Systems 43, no. 15 (2015): 1761–70. http://dx.doi.org/10.1080/15325008.2015.1052158.

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Gujar, Nitin P., and Devman D. Gore. "Intelligent Grid Interfaced Solar Water Pumping System." International Journal of Multidisciplinary Research Transactions 4, no. 10 (2022): 9–25. https://doi.org/10.5281/zenodo.7216496.

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This paper deals with a single stage solar powered speed sensorless vector controlled induction motor drive for water pumping system, which is superior to conventional motor drive. The speed is estimated through estimated stator flux. The proposed system includes solar photovoltaic (PV) array, a three-phase voltage source inverter (VSI) and a motor-pump assembly. An incremental conductance (Inc.) based MPPT (Maximum Power Point Tracking) algorithm is used to harness maximum power from a PV array. The smooth starting of the motor is attained by vector control of an induction motor. The desired configuration is designed and simulated in MATLAB/Simulink platform.

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Abouloifa, Abdelmajid, Karim Noussi, Elhoussin Elbouchikhi, Hanane Katir, Ibtissam Lachkar, and Abdelali El Aroudi. "High-Gain Observer-Based Advanced Nonlinear Control of a Grid-Connected Wind Energy Conversion System with Sensorless Maximum Power Point Tracking." Machines 10, no. 11 (2022): 1074. http://dx.doi.org/10.3390/machines10111074.

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This paper deals with the control development of a wind energy conversion system (WECS) interfaced to a utility grid by using a doubly fed induction generator (DFIG), a back-to-back (B2B) converter and an RL filter for optimal power extraction. The aim was to design a sensorless controller to improve the system reliability and to simultaneously achieve the regulation of the generator speed, reactive power and DC-link voltage. The proposed global control scheme combines: (i) a high-gain observer employed to estimate the generator speed and the mechanical torque, usually regarded as accessible, (ii) a sensorless MPPT block developed to provide optimal generator speed reference, which is designed on the basis of the mechanical observer and a polynomial wind-speed estimator and (iii) a finite-time controller (FTC) applied to the B2B converter to meet the output reference’s tracking objectives in a short predefined finite time by using the backstepping and Lyapunov approaches. The proposed controller performance is formally analysed, and its capabilities are verified by numerical simulations using a 2 MW DFIG wind turbine (WT) under different operating conditions.

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Fathabadi, Hassan. "Novel high accurate sensorless dual-axis solar tracking system controlled by maximum power point tracking unit of photovoltaic systems." Applied Energy 173 (July 2016): 448–59. http://dx.doi.org/10.1016/j.apenergy.2016.03.109.

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Wang, Jie, and Didi Bo. "Adaptive fixed-time sensorless maximum power point tracking control scheme for DFIG wind energy conversion system." International Journal of Electrical Power & Energy Systems 135 (February 2022): 107424. http://dx.doi.org/10.1016/j.ijepes.2021.107424.

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Baike Shen, B. Mwinyiwiwa, Yongzheng Zhang, and Boon-Teck Ooi. "Sensorless Maximum Power Point Tracking of Wind by DFIG Using Rotor Position Phase Lock Loop (PLL)." IEEE Transactions on Power Electronics 24, no. 4 (2009): 942–51. http://dx.doi.org/10.1109/tpel.2008.2009938.

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Obeidi, Nabil, Mostefa Kermadi, Bachir Belmadani, Abdelkarim Allag, Lazhar Achour, and Saad Mekhilef. "A Current Sensorless Control of Buck-Boost Converter for Maximum Power Point Tracking in Photovoltaic Applications." Energies 15, no. 20 (2022): 7811. http://dx.doi.org/10.3390/en15207811.

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In the present paper, a current sensorless (CSL) method for buck-boost converter control is proposed for maximum power point tracking (MPPT) photovoltaic applications. The proposed control scheme uses the mathematical model of the buck-boost converter to derive a predefined objective function for the MPPT control. The proposed scheme does not require any current sensor and relies only on the input voltage signal, which decreases the implementation cost. The proposed method is successfully implemented using a Matlab/Simulink/Stateflow environment, and its effectiveness is compared over the perturb and observe (P&O) method. An experimental rig, that includes a buck-boost converter, a PV simulator, and a resistive load, is used for the experimental validation. A rapid Arduino prototyping platform is used for the digital implementation, where the SAM3X8E microcontroller of the Arduino DUE board, which integrates an ARM Cortex-M3 MCU, is used as a target hardware for the proposed model-based controller developed under the Stateflow environment. Furthermore, the integrated pulse width modulation (PWM) macrocell is used to generate accurate PWM gate-drive signals for the buck-boost converter. Compared to the P&O, the presented simulation and experimental results show that the proposed method has reduced the computation burden and the sensor cost of implementation by 24.3%, and 27.95%, respectively.

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Gruner, Víctor Ferreira, Jefferson William Zanotti, Walbermark Marques Santos, et al. "Modified Current Sensorless Incremental Conductance Algorithm for Photovoltaic Systems." Energies 16, no. 2 (2023): 790. http://dx.doi.org/10.3390/en16020790.

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This paper proposes a novel maximum power point tracking algorithm applied to photovoltaic systems. The proposed method uses the derivative of power versus voltage to define the tracking path and has the advantage of requiring only a voltage sensor to be implemented. The absence of the current sensor and the auxiliary circuitry employed for conditioning the current signal imply cost reduction, configuring the main contribution of the proposed method, whose performance is kept close to the classical incremental conductance method, even with the reduced number of components. A DC-DC zeta converter is introduced in the content of this work as an interface between a photovoltaic array and a resistive load. The paper describes the operating principle and presents the mathematical formulation related to the proposed algorithm. Interesting simulation and experimental results are presented to validate the theory by comparing the proposed method with its traditional version under several scenarios of solar irradiance and temperature.

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Abo-Khalil, Ahmed G., and Ali S. Alghamdi. "MPPT of Permanent Magnet Synchronous Generator in Tidal Energy Systems Using Support Vector Regression." Sustainability 13, no. 4 (2021): 2223. http://dx.doi.org/10.3390/su13042223.

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In this paper, an improved Maximum Power Point Tracking (MPPT) algorithm for a tidal power generation system using a Support Vector Regression (SVR) is proposed. To perform this MPPT, a tidal current speed sensor is needed to track the maximum power. The use of these sensors has a lack of reliability, requires maintenance, and has a disadvantage in terms of price. Therefore, there is a need for a sensorless MPPT control algorithm that does not require information on tidal current speed and rotation speed that improves these shortcomings. Sensorless MPPT control methods, such as SVR, enables the maximum power to be output by comparing the relationship between the output power and the rotational speed of the generator. The performance of the SVR is influenced by the selection of its parameters which is optimized during the offline training stage. SVR has a strength and better response than the neural network since it ensures the global minimum and avoids being stuck at local minima. This paper proposes a high-efficiency grid-connected tidal current generation system with a permanent magnet synchronous generator back-to-back converter. The proposed algorithm is verified experimentally and the results confirm the excellent control characteristics of the proposed algorithm.

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Tiang, Tow Leong, and Dahaman Ishak. "Novel MPPT Control in Permanent Magnet Synchronous Generator System for Battery Energy Storage." Applied Mechanics and Materials 110-116 (October 2011): 5179–83. http://dx.doi.org/10.4028/www.scientific.net/amm.110-116.5179.

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This paper presents a novel sensorless maximum power point tracking (MPPT) control strategy for capturing the maximum energy from the fluctuating wind speed that being used in the stand-alone small scale variable speed wind turbine generator system (VSWTGS). The generated electricity from the wind turbine systems is used to charge battery energy storage. The whole system including the wind turbine, permanent magnet synchronous generator (PMSG), power converter, filter and lead acid battery has been simulated in Matlab/SimPowerSystem simulation software. The MPPT controller is developed to function as a wind speed estimator to generate an appropriate duty cycle for controlling power MOSFET switch in of the boost converter in order to capture maximum power in variable wind speed. From the simulation results, the power converters and filters are showing good performance in charging the lead acid battery. Besides, the novel MPPT controller is capable of extracting the maximum power from the fluctuating wind speed and exhibits good performance in both steady state and transient condition.

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Cortes-Vega, David, Hussain Alazki, and Jose Luis Rullan-Lara. "Current Sensorless MPPT Control for PV Systems Based on Robust Observer." Applied Sciences 12, no. 9 (2022): 4360. http://dx.doi.org/10.3390/app12094360.

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Photovoltaic (PV) systems are among the most used alternatives for electrical power generation from renewable sources. To ensure that PV systems make the most of the available solar energy, maximum power point tracking (MPPT) schemes must be implemented, which usually require voltage and current sensors to track the PV power. This paper presents the design of a robust observer using the Attractive Ellipsoid Method to achieve a precise estimation of PV current under parametric uncertainty and output perturbations. The application of such an observer enables the PV generation system to operate in a current sensorless mode, which reduces the overall cost of the system and enhances its reliability. The convergence of the observer is guaranteed by solving an optimization problem which generates the optimal gains using Linear Matrix Inequalities (LMI). To prove the effectiveness of the proposed sensorless scheme, simulations are performed in Matlab under test profiles based on the EN50530 standard and parameter uncertainty conditions, obtaining an accurate estimation which is used for MPPT operation.

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Abd Elkader, Fathy, Basem Elhady, and Ahmed Kalas. "Sensor and Sensorless Speed Control of Doubly Fed Induction Generator Wind Turbines for Maximum Power Point Tracking." Port-Said Engineering Research Journal 18, no. 2 (2014): 8–16. http://dx.doi.org/10.21608/pserj.2014.45256.

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Liu, Peter, Wen-Tsung Yang, Chang-En Yang, and Chia-Lien Hsu. "Sensorless wind energy conversion system maximum power point tracking using Takagi–Sugeno fuzzy cerebellar model articulation control." Applied Soft Computing 29 (April 2015): 450–60. http://dx.doi.org/10.1016/j.asoc.2015.01.019.

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Hassan, Marwa, Alsnosy Balbaa, Hanady Issa, and Noha El-Amary. "Asymptotic Output Tracked Artificial Immunity Controller for Eco-Maximum Power Point Tracking of Wind Turbine Driven by Doubly Fed Induction Generator." Energies 11, no. 10 (2018): 2632. http://dx.doi.org/10.3390/en11102632.

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This paper aims to design a controller for a Doubly Fed Induction Generator (DFIG) targeting the Eco-Maximum Power Point Tracking (EMPPT) for environmental aspects. The proposed controller consists of two clusters, which are the novel Artificial Immunity sensorless Eco-Maximum Power Point Tracking (AI EMPPT) and the asymptotic non-linear control techniques. The main target of the AI EMPPT is to reduce the carbon dioxide emission by generating the maximum possible power from the renewable electrical energy resource, which is wind electrical power generation to replace the fossil-fuel conventional generation. To build the AI EMPPT, an Artificial Immunity System Estimator (AISE) based on artificial immunity technique and a Model Reference Adaptive System (MRAS) are used to estimate the DFIG rotor speed. Then, the AI EMPPT is applied to provide the reference electromagnetic torque signal. Subsequently, the reference electromagnetic torque interacts with the estimated generator speed, determined by the wind mechanical power, to supply the wind electrical power. The second cluster is the asymptotic non-linear control technique which proposes the reference signal tracking of the rotor direct and quadratic current, respectively. Thus, assigning specific zeros through feedback ensures the reproduction of an output that converges asymptotically to a required reference rotor current. For online operation, the Artificial Immunity Technique (AIT) is utilized to deal with the generated control reference signal. A proposal hardware implementation on Field Programmed Gate Array (FPGA) is also presented. The introduced approach was applied to a wind turbine generator driving a 3.7 kW load. MATLAB program was used to simulate and test the performance of the proposed control methods. The results to show the effectiveness of the proposed technique. The reduction in CO2 emission was calculated.

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Kazmi, Syed Muhammad Raza, Hiroki Goto, Hai-Jiao Guo, and Osamu Ichinokura. "A Novel Algorithm for Fast and Efficient Speed-Sensorless Maximum Power Point Tracking in Wind Energy Conversion Systems." IEEE Transactions on Industrial Electronics 58, no. 1 (2011): 29–36. http://dx.doi.org/10.1109/tie.2010.2044732.

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El Yaakoubi, Ali, Kamal Attari, Adel Asselman, and Abdelouahed Djebli. "Novel power capture optimization based sensorless maximum power point tracking strategy and internal model controller for wind turbines systems driven SCIG." Frontiers in Energy 13, no. 4 (2017): 742–56. http://dx.doi.org/10.1007/s11708-017-0462-x.

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Ma, Leiming, Lingfei Xiao, Jianfeng Yang, Xinhao Huang, and Xiangshuo Meng. "Sensorless intelligent second-order integral sliding mode maximum power point tracking control for wind turbine system based on wind speed estimation." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 235, no. 7 (2021): 1046–63. http://dx.doi.org/10.1177/0959651820982405.

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Aiming at the maximum power point tracking for wind turbine, a sensorless intelligent second-order integral sliding mode control based on wind speed estimation is proposed in this article. The maximum wind energy capture is realized by controlling permanent magnet synchronous motor to adjust the speed of wind turbine. First, an intelligent second-order integral sliding mode control is designed for the speed loop and current loop control, which has fast convergence speed, strong robustness and can effectively reduce chattering. Second, a novel cascade observer based on direct sliding mode observer and extended high-gain observer is used to estimate the rotor speed and position. Besides, combined radial basis function neural network is used to estimate the valid value of wind speed. Both simulation and experiment are implemented, which verify the effectiveness of the proposed strategy under the condition of considering both model uncertainty and external disturbance.

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Dursun, Emre Hasan, and Ahmet Afsin Kulaksiz. "Second-Order Fast Terminal Sliding Mode Control for MPPT of PMSG-based Wind Energy Conversion System." Elektronika ir Elektrotechnika 26, no. 4 (2020): 39–45. http://dx.doi.org/10.5755/j01.eie.26.4.25762.

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This article proposes a new maximum power point tracking (MPPT) controller based on voltage-mode Second-Order Fast Terminal Sliding Mode Control (SO-FTSMC) to obtain better performance in the power extraction from Permanent Magnet Synchronous Generator (PMSG)-based Wind Energy Conversion System (WECS). The major objective of the study is the design of SO-FTSMC that can ensure the operation of the system in maximum power reference with higher efficiency, less steady-state error, and voltage fluctuation. Maximum power references are determined by mechanical sensorless MPPT approach. The small-scale WECS configuration incorporates wind turbine, PMSG, uncontrolled rectifier, boost converter, and MPPT controller. SO-FTSMC method has not been performed before as a voltage regulator in such a topology. The proposed controller has been validated for two different wind speed test scenarios in simulation environment, which can be applied effectively to PMSG-based WECS. Moreover, Conventional SMC (C-SMC) is created and then performance of controllers is compared in these wind speed scenarios according to maximum extracted average power, output voltage fluctuation, and voltage error in steady-state, MPPT efficiency, and performance indices. Obtained results indicate that proposed SO-FTSMC-based MPPT controller achieves superior performance.

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Selvi, B. kalai, and Sridhar rajan. "Sensorless Fuzzy-Logic-Based Maximum Power Point Tracking Control For A Small-Scale Wind Power Generation Systems With A Switched mode Rectifier." International Journal of MC Square Scientific Research 9, no. 2 (2017): 115–25. http://dx.doi.org/10.20894/ijmsr.117.009.002.014.

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Lee, Joonmin, and Young-Seok Kim. "Sensorless fuzzy-logic-based maximum power point tracking control for a small-scale wind power generation systems with a switched-mode rectifier." IET Renewable Power Generation 10, no. 2 (2016): 194–202. http://dx.doi.org/10.1049/iet-rpg.2015.0250.

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Pham, Dzung Quoc, Vu Truong Dan Nguyen, Khoa Dinh Le, Anh Bao Nguyen, and Diep Chi Le. "The Modified Control Method for the Single-Stage Three-Phase GridConnected Photovoltaic System." Science and Technology Development Journal 16, no. 4 (2013): 19–32. http://dx.doi.org/10.32508/stdj.v16i4.1581.

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Single-stage topology and the maximum power point tracking (MPPT) algorithm have advantages such as simple configuration and high efficiency in grid-connected photovoltaic (PV) systems. In conventional systems, current and voltage sensors of PV system are normally used for MPPT. This paper presents a modified control algorithm for the single-stage three-phase grid-connected PV system without PV current sensor with a variable step MPP-tracker. This algorithm is not derived from complex state equations and is not dependent on any circuit parameters. It simply calculates the output power of the inverter to replace the input power of the PV systems in the MPPT algorithm. The modified algorithm is simulated by using Matlab/Simulink software and implemented in the experimental prototype. With the single-stage configuration and PV current sensorless method, the prototype is suitable for lowcost high efficient implementation in the practice.

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Ki, Song-Do, Cheol-Woong Choi, Jae-Sub Ko, and Dae-Kyong Kim. "Current-Sensorless Method for Photovoltaic System Using Capacitor Charging Characteristics." Energies 17, no. 19 (2024): 4971. http://dx.doi.org/10.3390/en17194971.

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The installed capacity of photovoltaic (PV) systems has increased significantly over the past few decades, and related technologies have advanced significantly. The electrical characteristics of a PV system change nonlinearly based on irradiation and temperature, and the I–V characteristic curve, expressed in terms of the voltage and current, is used to verify these characteristics. The maximum power point tracking (MPPT) control method was applied to maximize the performance of the PV system. Voltage and current sensors are used to control the I–V characteristic curve and MPPT; however, current sensors have various disadvantages in terms of price and system configuration. Therefore, this study presents a method for calculating the current of a PV system using the charging characteristics of a capacitor. The method presented in this paper analyzes the I–V characteristic curve’s qualities through simulations and experiments under normal, shaded, and mismatched conditions of the PV module.

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Belmokhtar, K., M. L. Doumbia, and K. Agbossou. "Novel fuzzy logic based sensorless maximum power point tracking strategy for wind turbine systems driven DFIG (doubly-fed induction generator)." Energy 76 (November 2014): 679–93. http://dx.doi.org/10.1016/j.energy.2014.08.066.

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Tighirt, Abdelhakim, Mohamed Aatabe, Fatima El Guezar, Hassane Bouzahir , Alessandro N. Vargas , and Gabriele Neretti . "A New Stochastic Controller for Efficient Power Extraction from Small-Scale Wind Energy Conversion Systems under Random Load Consumption." Energies 17, no. 19 (2024): 4927. http://dx.doi.org/10.3390/en17194927.

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This paper presents an innovative scheme to enhance the efficiency of power extraction from wind energy conversion systems (WECSs) under random loads. The study investigates how stochastic load consumption, modeled and predicted using a Markov chain process, impacts WECS efficiency. The suggested approach regulates the rectifier voltage rather than the rotor speed, making it a sensorless and reliable method for small-scale WECSs. Nonlinear WECS dynamics are represented using Takagi–Sugeno (TS) fuzzy modeling. Furthermore, the closed-loop system’s stochastic stability and recursive feasibility are guaranteed regardless of random load changes. The performance of the suggested controller is compared with the traditional perturb-and-observe (P&O) algorithm under varying wind speeds and random load variations. Simulation results show that the proposed approach outperforms the traditional P&O algorithm, demonstrating higher tracking efficiency, rapid convergence to the maximum power point (MPP), reduced steady-state oscillations, and lower error indices. Enhancing WECS efficiency under unpredictable load conditions is the primary contribution, with simulation results indicating that the tracking efficiency increases to 99.93%.

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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 (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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Loon, Chan Men, and Muhamad Zalani Daud. "Sensorless dual axis solar tracker using improved sun position algorithm." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 3 (2020): 1305. http://dx.doi.org/10.11591/ijpeds.v11.i3.pp1305-1312.

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This paper presents development of a prototype sensorless dual axis solar tracker for maximum extraction of solar energy. To prove the concept and evaluate the proposed algorithm, a low cost widely availabe materials were used which was programmed based on Arduino microcontroller. The porposed algorithm works based on two search methods namely the global search that approximates the best point location in a region, and local search that further determines the actual sun’s position. Experimental results showed that the proposed algorithm gives better performance compared to the existing sun position algorithm (SPA) - based method as well as the fixed panel system. In terms of total output power, the proposed algorithm gives 17.96% more efficient than the fixed system and 6.38% better than the SPA-based system. Furthermore, the percentage error of the experimental measured angle to the actual sun azimuth angle was relatively minimal (less than 3%) during clear day operation. The system was proven to be effective in tracking the sun for improved energy production of solar PV panels and the proposed algorithm also can be used for designing the tracker with larger size of solar PV systems.

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Chan, Men Loon, and Zalani Daud Muhamad. "Sensorless dual axis solar tracker using improved sun position algorithm." International Journal of Power Electronics and Drive System (IJPEDS) 11, no. 3 (2020): 1305–12. https://doi.org/10.11591/ijpeds.v11.i3.pp1305-1312.

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Abouobaida, Hassan, and Said Bied. "Modelling and Control Design for Energy Management of Grid Connected Hybrid PV-wind System." International Journal of Applied Power Engineering 7, no. 2 (2018): 166–80. https://doi.org/10.11591/ijape.v7.i2.pp166-180.

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This paper deals with the control of hybrid PV-WIND power conversion structure. This paper develops a very important contribution which is the use of a single DC to DC converter, linearization of control of the Three-Level Boost Converter (TLBC) considering the imper fections of the passive components. The TLBC control provides balancing of capacitor voltages and maximum power operation of PV generator. For reasons of simplicity, a linearization based on the dynamic compensation of the disturbance is proposed. A sensorless Maximum Power Point Tracking (MPPT) algorithm is used to maximize a power extracted of the wind generator. The proportional relation between the rotational speed and the output voltage of the rectifier allows to use a voltage sensor to estimate the DC bus voltage reference instead of a mechanical speed sensor. The control of the three-phase inverter allows a transfer of the active power, the power factor close to the unit and thus a limitation of the reactive power injected into the grid. The external control loop performs the regulation of the common DC bus voltage while the internal control loop regulates the dq components of the currents injected into the grid. The simulation results showed the validity of the control approach. The proposed power conversion structure based on a single static converter has shown very good performance in terms of efficiency, the quality of the energy produced, complementarity between the two renewable sources and reliability. The paper ends with conclusions.

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Khan, Rashid, Laiq Khan, Shafaat Ullah, Irfan Sami, and Jong-Suk Ro. "Backstepping Based Super-Twisting Sliding Mode MPPT Control with Differential Flatness Oriented Observer Design for Photovoltaic System." Electronics 9, no. 9 (2020): 1543. http://dx.doi.org/10.3390/electronics9091543.

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The formulation of a maximum power point tracking (MPPT) control strategy plays a vital role in enhancing the inherent low conversion efficiency of a photovoltaic (PV) module. Keeping in view the nonlinear electrical characteristics of the PV module as well as the power electronic interface, in this paper, a hybrid nonlinear sensorless observer based robust backstepping super-twisting sliding mode control (BSTSMC) MPPT strategy is formulated to optimize the electric power extraction from a standalone PV array, connected to a resistive load through a non-inverting DC–DC buck-boost power converter. The reference peak power voltage is generated via the Gaussian process regression (GPR) based probabilistic machine learning approach that is adequately tracked by the proposed MPPT scheme. A generalized super-twisting algorithm (GSTA) based differential flatness approach (DFA) is used to retrieve all the missing system states. The Lyapunov stability theory is used for guaranteeing the stability of the proposed closed-loop MPPT technique. The Matlab/Simulink platform is used for simulation, testing and performance validation of the proposed MPPT strategy under different weather conditions. Its MPPT performance is further compared with the recently proposed benchmark backstepping based MPPT control strategy and the conventional MPPT strategies, namely, sliding mode control (SMC), proportional integral derivative (PID) control and the perturb-and-observe (P&O) algorithm. The proposed technique is found to have a superior tracking performance in terms of offering a fast dynamic response, finite-time convergence, minute chattering, higher tracking accuracy and having more robustness against plant parametric uncertainties, load disturbances and certain time-varying sinusoidal faults occurring in the system.

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Pham, Tuynh Van, and Anh Tan Nguyen. "A Modified Reduced-Order Generalized Integrator–Frequency-Locked Loop-Based Sensorless Vector Control Scheme Including the Maximum Power Point Tracking Algorithm for Grid-Connected Squirrel-Cage Induction Generator Wind Turbine Systems." Inventions 9, no. 2 (2024): 44. http://dx.doi.org/10.3390/inventions9020044.

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In this paper, an improved speed sensorless control method including the maximum power point tracking (MPPT) algorithm for grid-connected squirrel-cage induction generator (SCIG) wind turbine systems using modified reduced-order generalized integrator (ROGI)–frequency-locked loop (FLL) with the DC offset compensation capability is proposed. The rotor flux linkages are estimated by the modified ROGI-FLL-based observer, of which the inputs are d-q axis rotor EMFs, and hence the position of rotor flux linkage can be obtained directly based on these estimated flux linkages using the arc tangent function. The DC offset in the estimated rotor flux linkages, which can cause oscillations in estimated rotor speed, leading to oscillations in SCIG stator active power due to power signal feedback (PSF)-MPPT algorithm, can be significantly reduced using the DC offset compensators included in modified ROGI-FLL structure. Moreover, the negative effects of high-frequency components on the performance of the rotor flux linkage estimation can be remarkably mitigated owing to the excellent high-frequency component rejection capability of ROGI. The dynamic response analysis of the modified ROGI-FLL with DC offset compensators is provided as well. The feasibility of the proposed method has been demonstrated in comparison with dual SOGI-FLL with DC offset compensator-based existing method.

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Solís-Cervantes, Cesar Ulises, Sergio Isai Palomino-Resendiz, Diego Alonso Flores-Hernández, Marco Antonio Peñaloza-López, and Carlos Manuel Montelongo-Vazquez. "Design and Implementation of Extremum-Seeking Control Based on MPPT for Dual-Axis Solar Tracker." Mathematics 12, no. 12 (2024): 1913. http://dx.doi.org/10.3390/math12121913.

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The increase in the production efficiency of photovoltaic technology depends on its alignment in relation to the solar position. Solar tracking systems perform the tracking action by implementing control algorithms that help the reduction of tracking errors. However, conventional algorithms can reduce the life of actuators and mechanisms due to control action, significantly reducing operation times and profitability. In this article, an unconventional control scheme is developed to address the mentioned challenges, presenting the design and implementation of an extremum-seeking control to perform maximum power point tracking for a two-axis solar tracker instrumented with a solar module. The proposed controller is governed by the dynamics of a classic proportional-integral scheme and assisted by sensorless feedback. Also, it has an anti-wind-up-type configuration for the integral component and counts with a variable amplitude for the dither signal. The proposal is validated experimentally by comparison between a fixed system and a two-axis system in azimuth-elevation configuration. In addition, two performance indices are defined and analyzed, system energy production and tracking error. The results show that the proposal allows producing up to 27.75% more than a fixed system, considering the tracker energy consumption due to the tracking action and a pointing accuracy with ±1.8∘ deviation. Finally, an analysis and discussion are provided based on the results, concluding that the proposed algorithm is a viable alternative to increase the performance of tracked photovoltaic systems.

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Shetty, Divya, Jayalakshmi N. Sabhahit, and Ganesh Kudva. "A Methodology to Optimize PMSM Driven Solar Water Pumps Using a Hybrid MPPT Approach in Partially Shaded Conditions." Clean Technologies 6, no. 3 (2024): 1229–59. http://dx.doi.org/10.3390/cleantechnol6030060.

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Solar water pumps are crucial for farmers, significantly reducing energy costs and providing independence from conventional fuels. Their adoption is further incentivized by government subsidies, making them a practical choice that aligns with sustainable agricultural practices. However, the cost of the required solar panels for the chosen power makes it essential to optimize solar water pumping systems (SWPS) for economic viability. This study enhances the efficiency and reliability of permanent magnet synchronous motor (PMSM)-driven SWPS in rural areas using hybrid maximum power point tracking (MPPT) algorithms and voltage-to-frequency (V/f) control strategy. It investigates the sensorless scalar control method for PMSM-based water pumps and evaluates various MPPT algorithms, including grey wolf optimization (GWO), particle swarm optimization (PSO), perturb and observe (PO), and incremental conductance (INC), along with hybrid combinations. The study, conducted using MATLAB Simulink, assesses these algorithms on convergence time, MPPT accuracy, torque ripple, and system efficiency under different partial shading conditions. Findings reveal that INC-GWO excels, providing higher accuracy, faster convergence, and reduced steady-state oscillations, thus boosting system efficiency. The V/f control strategy simplifies control mechanisms and enhances performance. Considering system non-idealities and maximum duty cycle limitations, PMSM-based SWPS achieve superior efficiency and stability, making them viable for off-grid water pumping applications.

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Abouobaida, Hassan, and Said El Bied. "Modelling and Control Design for Energy Management of Grid Connected Hybrid PV-wind System." International Journal of Applied Power Engineering (IJAPE) 7, no. 2 (2018): 166. http://dx.doi.org/10.11591/ijape.v7.i2.pp166-180.

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This paper deals with the control of hybrid PV-WIND power conversion structure. This paper develops a very important contribution which is the use of a single DC to DC converter, linearization of control of the three- level boost converter (TLBC) considering the imperfections of the passive components. The (TLBC) control provides balancing of capacitor voltages and maximum power operation of PV generator. For reasons of simplicity, a linearization based on the dynamic compensation of the disturbance is proposed. A sensorless maximum power point tracking (MPPT) algorithm is used to maximize a power extracted of the wind generator. The proportional relation between the rotational speed and the output voltage of the rectifier allows to use a voltage sensor to estimate the DC bus voltage reference instead of a mechanical speed sensor. The control of the three-phase inverter allows a transfer of the active power, the power factor close to the unit and thus a limitation of the reactive power injected into the grid. The external control loop performs the regulation of the common DC bus voltage while the internal control loop regulates the dq components of the currents injected into the grid. The simulation results showed the validity of the control approach. The proposed power conversion structure based on a single static converter has shown very good performance in terms of efficiency, the quality of the energy produced, complementarity between the two renewable sources and reliability. The paper ends with conclusions.

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Arjun, Kumar GB, Shivashankar, and Keshavamurthy. "Design and control of grid-connected solar-wind integrated conversion system with DFIG supplying three-phase four-wire loads." International Journal of Power Electronics and Drive System (IJPEDS) 12, no. 2 (2021): 1150–61. https://doi.org/10.11591/ijpeds.v12.i2.pp1150-1161.

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This paper describes the architecture and control of an autonomous hybrid solar-wind system (AHSWS) powered distributed generation system supplying to a 3ϕ-4 wire system. It includes a nonlinear controlling technique for maximum power point tracking (MPPT) used in doubly fed induction generator dependent wind energy translation scheme and solar photovoltaic system (SPVS). In the hybrid model, the DC/DC converter output from the PV system is explicitly coupled with the DC-link of DFIG's back-to-back converter. An arithmetical model of the device is developed, derived using a suitable d-q reference frame. The grid-voltage-oriented vector regulation is required to manage the GSC to keep the steady-state voltage of the DC bus and to adjust reactive power on the grid side. Also, the stator-voltage-oriented control scheme offers a stable function of DFIG to regulate the RSC on the stator edge for reactive and active power management in this approach. DC/DC converter is being used to maintain the maximum power from SPVS. A Perturb & Observe method is used for tracing maximum power in an SPVS. The simulation designs of 4.0kW DFIG and 4.5kW solar array simulator are built-in SIMPOWER software kit of MATLAB, it is shown to achieve optimum efficiency under various mechanical and electrical circumstances. It can produce rated frequency and voltage in both scenarios.

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González-Medina, Raúl, Marian Liberos, Silvia Marzal, Emilio Figueres, and Gabriel Garcerá. "A Control Scheme without Sensors at the PV Source for Cost and Size Reduction in Two-Stage Grid Connected Inverters." Energies 12, no. 15 (2019): 2955. http://dx.doi.org/10.3390/en12152955.

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In order to reduce the cost of PV facilities, the market requires low cost and highly reliable PV inverters, which must comply with several regulations. Some research has focused on decreasing the distortion of the current injected into the grid, reducing the size of the DC-link capacitors and removing sensors, while keeping a good performance of the maximum power point tracking (MPPT) algorithms. Although those objectives are different, all of them are linked to the inverter DC-link voltage control loop. Both the reduction of the DC-link capacitance and the use of sensorless MPPT algorithms require a voltage control loop faster than that of conventional implementations in order to perform properly, but the distortion of the current injected into the grid might rise as a result. This research studies a complete solution for two-stage grid-connected PV inverters, based on the features of second-order generalized integrators. The experimental tests show that the proposed implementation has a performance similar to that of the conventional control of two-stage PV inverters but at a much lower cost.

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Ramasamy, Bharani Kumar, Aravindan Palaniappan, and Sanavullah Mohamed Yakoh. "Direct‐drive low‐speed wind energy conversion system incorporating axial‐type permanent magnet generator and Z ‐source inverter with sensorless maximum power point tracking controller." IET Renewable Power Generation 7, no. 3 (2013): 284–95. http://dx.doi.org/10.1049/iet-rpg.2012.0248.

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Saha, Biswajit, Aryadip Sen, Bhim Singh, Kumar Mahtani, and José A. Sánchez-Fernández. "Quadrature-Phase-Locked-Loop-Based Back-Electromotive Force Observer for Sensorless Brushless DC Motor Drive Control in Solar-Powered Electric Vehicles." Applied Sciences 15, no. 2 (2025): 574. https://doi.org/10.3390/app15020574.

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This work presents a sensorless brushless DC motor (BLDCM) drive control, optimized for solar photovoltaic (PV)- and battery-fed light electric vehicles (LEVs). A back-electromotive force (EMF) observer integrated with an enhanced quadrature-phase-locked-loop (QPLL) structure is proposed for accurate rotor position estimation, addressing limitations of existing control methods at low speeds and under dynamic conditions. The study replaces the conventional arc-tangent technique with a QPLL-based approach, eliminating low-pass filters to enhance system adaptability and reduce delays. The experimental results demonstrate a significant reduction in commutation error, with a nearly flat value at 0 degrees during steady-state and less than 8 degrees under dynamic conditions. Furthermore, the performance of a modified single-ended primary-inductor converter (SEPIC) for maximum power point tracking (MPPT) in solar-powered LEVs is verified, minimizing current ripple and ensuring smooth motor operation. The system also incorporates a regenerative braking mechanism, extending the vehicle’s range by efficiently recovering kinetic energy through the battery with 30.60% efficiency. The improved performance of the proposed method and system over conventional approaches contributes to the advancement of efficient and sustainable solar-powered BLDC motor-based EV technologies.

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