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A positive output-super lift Luo converter fed brushless DC motor drive using alternative energy sources

INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS 2021年第2期31卷

作者： Femi, R. Sree Renga Raja, T. Shenbagalakshmi, R. Univ Coll Engn Nagercoil Dept Elect & Elect Engn Nagercoil 629004 Tamil Nadu India SKN Sinhgad Inst Technol & Sci Dept Elect Engn Pune Maharashtra India

In this work, solar PV system and wind driven by permanent magnet synchronous generator (PMSG) are the sources which are driven by a brushless DC motor (BLDC). The solar PV system employs super lift Luo converter to attain DC voltage regulation. The primary intention of employing positive output-super lift (PO-SL) Luo converter is to acquire high voltage gain ratio as well as to derive maximum power from solar panel. The output extracted from the wind is fed to the PWM rectifier to convert AC into DC. The speed regulation of BLDC drive for pumping application is attained via variable DC-Link capacitor through VSI. Additional control circuits are not necessary to regulate the speed of drive. An appropriate control of PO-SL Luo converter duty cycle using optimized control algorithm offers smooth starting of BLDC drive. Maximum power point techniques are adopted to derive the maximum power from a PV network and the fuzzy based maximum power point tracking (mppt) approach has been found to offer better results for unexpectedly varying environment conditions as compared to other approaches. In order to regulate the output voltage from the wind system, PI controller is utilized. It also provides additional support to the entire proposed system in absence of poor solar irradiance. The modeled drive system is capable of achieving higher efficiency. The real-time implementation of the proposed system is also validated through experimental setup.

关键词： BLDC drive efficiency mppt algorithm PI controller PO‐ SL Luo converter speed control VSI

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Integral sliding mode control for DFIG based WECS with mppt based on artificial neural network under a real wind profile

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ENERGY REPORTS 2021年 7卷 4809-4824页

作者： Chojaa, Hamid Derouich, Aziz Chehaidia, Seif Eddine Zamzoum, Othmane Taoussi, Mohammed Elouatouat, Hasnae Sidi Mohamed Ben Abdellah Univ Higher Sch Technol Ind Technol & Serv Lab Fes 30000 Morocco Univ Badji Mokhtar Res Lab Ind Risks Non Destruct Control & Operatin Annaba Algeria Mohammed V Univ Rabat Res Ctr Sci & Technol Engn & Hlth Higher Natl Sch Comp Sci & Syst Anal Rabat Morocco

Handling the internal parametric variations and the nonlinearities of the high rated wind energy conversion system (WECS) is remained among the main challenges to maximize the produced energy, ameliorate its quality and ensure its efficient integration on the grid. In this context, a robust integral sliding mode control (ISMC) with Lyapunov function is proposed to control the active and reactive powers of a doubly fed induction generator (DFIG) based wind turbine, and to assure high dynamic performances according to the wind speed variation. To operate around an optimal rotational speed, a robust mppt algorithm with mechanical speed control based on artificial Neural Network Controller (ANNC) is presented in order to extract the maximum power. Thereafter, the robust integral SMC are replaced by Field Oriented Control (FOC_PI) for comparative purposes. The objective is to prove the best performances of the system obtained by the proposed control method in terms of the dynamic response, total harmonic distortion THD (%) of the injected current into the grid, the reference tracking ability, Overshoot (%), precision and robustness. The effectiveness and robustness of each control techniques has been implemented and tested under MATLAB/Simulink environment by using a 1.5 MW wind system model. (C) 2021 Published by Elsevier Ltd.

关键词： Wind energy conversion system (WECS) mppt algorithm Artificial neural network controller (ANN) Integral sliding mode controller (ISMC) Field Oriented Control (FOC)

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Maximum Power Point Tracking for Photovoltaic Panels Using Model Predictive Control and Incremental Conductance

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2021年第4-5期49卷 345-360页

作者： Lopes Filho, Gilberto Pereira Franco, Ricardo Augusto Teles Vieira, Flavio Henrique Univ Fed Goias UFG Escola Engn Elect Mecaninca & Comp Goiania Go Brazil Univ Fed Goias UFG Inst Informat Goiania Go Brazil

In this work, a novel maximum power point tracking algorithm (mppt) based on Model Predictive Control (MPC) for photovoltaic systems is proposed. The considered system is composed by a photovoltaic panel connected to a load using a flyback converter. The proposed approach combines MPC with a modified Incremental Conductance algorithm with a variable step size, verified in this work to be more efficient than the Perturb and Observe algorithm in tracking maximum power point, making the PV system to generate more energy. Computational simulations are carried out to compare the performance of the considered mppt algorithms, analyzing the output voltage and output power behavior at the photovoltaic panel. The results of the simulations show that the proposed algorithm provides better performance for the photovoltaic system than the main mppt algorithms in the literature.

关键词： mppt algorithm MPC photovoltaic panel

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Maximum power point tracking algorithm for photovoltaic systems considering error minimization and power derivative

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INTERNATIONAL JOURNAL OF EMERGING ELECTRIC POWER SYSTEMS 2021年第3期22卷 297-308页

作者： Lopes Filho, Gilberto Pereira Franco, Ricardo Augusto Teles Vieira, Flavio Henrique Univ Fed Goias BR-74605220 Goiania Go Brazil

In this work, a new maximum power point tracking algorithm (mppt) for photovoltaic systems is proposed. The considered system is composed of a photo-voltaic panel charging a battery using a buck-type DC-DC converter. Computational simulations are carried out to compare the performances of the mppt algorithms, therein analyzing the output voltage and output power behavior at the photovoltaic panel. Three evaluation scenarios are considered: with constant irradiance and temperature, randomly chosen conditions and using real data. The results of the simulations show that the proposed algorithm applied to the photovoltaic system achieves a better performance than the main mppt algorithms in the literature.

关键词： buck converter mppt algorithm photovoltaic panel

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A Comprehensive Control Strategy for a Push-Pull Microinverter Connected to the Grid

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ENERGIES 2023年第7期16卷 3196页

作者： Diaz, Manuel Munoz, Javier Rivera, Marco Rohten, Jaime Univ Talca Fac Engn Engn Sci Masters Program Curico 3340000 Chile Univ Talca Fac Engn Curico 3340000 Chile Univ Nottingham Fac Engn 15 Triumph Rd Nottingham NG7 2GT England Univ Bio Bio Dept Elect & Elect Engn Concepcion 4051381 Chile

The effects of partial shading or dust accumulation on the panels of photovoltaic systems connected to the grid can generate a considerable reduction in energy performance, being necessary to provide the appropriate voltage to the grid regardless of the irradiance level. This paper addresses this problem and presents a comprehensive control strategy and its implementation for a grid-connected microinverter composed of a push-pull converter followed by an H-bridge inverter. In the push-pull converter, a hybrid mppt algorithm and a PI control enable work in the MPP of the PV panel. In the H-bridge inverter, a cascade control consisting of a PI control and a predictive control allows the connection to the grid. A proof-of-concept prototype is implemented in order to validate the proposal. Experimental tests were performed by connecting the microinverter to a PV panel and a programmable photovoltaic panel emulator to check the mppt performance. Furthermore, partial shading conditions were simulated on the dc source to check if the global maximum power point is reached. Experimental results demonstrate the feasibility of the topology and the control approach, obtaining mppt performance in the topology above 99% at different power and voltage levels on the mppt, even in the presence of partial shading conditions.

关键词： microinverter mppt algorithm push-pull converter renewable energy

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Method to Improve the Power Coefficient of Vertical Axis Wind Turbines 1

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AUN/SEED-Net Joint Regional Conference in Transportation, Energy, and Mechanical Manufacturing Engineering, RCTEMME 2021

作者： Nguyen, Bao The Ngo, Minh Van Ngo, Huy Gia University of Technology – Vietnam National University Ho Chi Minh City Viet Nam Institute of Sustainable Energy Development Ho Chi Minh City Viet Nam

ISBN: (数字)9789811919688

ISBN: (纸本)9789811919671

Vertical axis wind turbines (VAWTs) have recently been gotten the attention for off-grid power generation due to their advantages over the popular horizontal axis wind turbines (HAWTs) such as omni-directionality, simplicity in design, operating at a lower tip speed ratio (TSR) leading to lower noise emission, etc. These advantages of VAWTs make them more suitable for the urban environment. The paper first applies the Double-Multiple Stream tube (DMST) Model to calculate the power coefficient of a VAWT using GOE 222 blades, then determines the optimum tip speed ratio to achieve the maximum power coefficient CP. After that, a method to improve the power coefficient CP is proposed. This method is based on an mppt algorithm of adjusting the output voltage of the controller to achieve the maximum power output of VAWTs. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Double-Multiple Stream tube (DMST) model mppt algorithm Power coefficient CP Tip speed ratio (TSR) Vertical axis wind turbines (VAWT)

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A novel optimiser of mppt by using PSO-AG and PID controller

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INTERNATIONAL JOURNAL OF AMBIENT ENERGY 2021年第1期43卷 5199-5206页

作者： El Hariz, Zahira Hicham, Aissaoui Mohammed, Diany Sultan Moulay Slimane Univ Sustainable Dev Lab Beni Mellal Morocco

This article presents a new methodology based on the application of the proportional-integral-derivative controller (PID) for the monitoring of the maximum power point of a solar system. The method explored is an evolving technique called PSOAG used in the detection and exploitation of the maximum power of the photovoltaic panel to improve its efficiency. The proposed methodology is based on three optimisation techniques: perturbation and observation (P&O), genetic algorithm (AG) and the particle swarm of optimisation (PSO). The main role of the PSO method, on the one hand, is to help the PID controller to discover the gains, in a dynamic situation, and on the other hand to increase the response time, the Settling Time and reduce the ripples of the power signal. The analysis of the performances and the rentability of the proposed method are made for a photovoltaic module-type Soltech 1STH-250-WH. In addition, the performance is also analysed by a comparative study with PSO-PID and AG-PID methods.

关键词： Solar energy mppt algorithm Particle Swarm of Optimisation genetic algorithm PID controller

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Photovoltaic Class-E Inverter for Resonance Wireless Power Transfer for Electric Vehicle Charging Applications with Optimization algorithms

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ENERGY TECHNOLOGY 2023年第9期11卷 2300304-2300304页

作者： Chehab, Mohamed Haikel Khelil, Makram Salah, Chokri Ben Tlija, Mehdi Rabhi, Abdelhamid Univ Monastir Lab Automat Elect Syst & Environm LASEE Monastir 5000 Tunisia Univ Sousse Issat Sousse Sousse 4003 Tunisia King Saud Univ Coll Engn Dept Ind Engn POB 800 Riyadh 11421 Saudi Arabia Univ Picardie Jules Verne MIS Lab F-80000 Amiens France

A wireless power transfer (WPT) station supplied by an array of solar panels is presented, where solar energy comes from an array of panels with 120 V voltage and 3 A current. It is subjected to maximum power point tracking algorithm optimization on a boost converter, where the duty cycle of the converter is adjusted with an interval chosen between [0.2, 0.8], which is used to iteratively compare between the input and output signals in order to have a maximum power at the output. After regulating the panel array signal through the boost converter, the signal is transferred to an additional middle stage whose role is to raise the frequency until it reaches the resonance frequency of the WPT charger. The device responsible for this task is an inverter based on a class-E inverter architecture and a GaN transistor technology. The inverter is controlled by a DSP card in a hard-switch mode and delivers the output signal with a frequency of 10 Mhz, which is the resonance frequency of spiral coils of wireless chargers. Herein, the signal nature can be seen at the terminal of a fixed load with signal optimization through the mppt algorithm and the HF inverter control mode.

关键词： Class-E inverter electromagnetic simulation EV charging mppt algorithm RWPT solar energy

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A Reliability-Optimized Maximum Power Point Tracking algorithm Utilizing Neural Networks for Long-Term Lifetime Prediction for Photovoltaic Power Converters

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ENERGIES 2023年第16期16卷 6071页

作者： Shahbazi, Mahmoud Smith, Niall Andrew Marzband, Mousa Habib, Habib Ur Rahman Univ Durham Dept Engn Durham DH1 3LE England Teesside Univ Net Zero Ind Innovat Ctr Middlesbrough TS1 3BA England

The reliability of power converters in photovoltaic systems is critical to the overall system reliability. This paper proposes a novel active thermal-controlled algorithm that aims to reduce the rate of junction temperature increase, therefore, increasing the reliability of the device. The algorithm works alongside a normal perturb and observe maximum power point tracking algorithm, taking control when certain temperature criteria are met. In conjunction with a neural network, the algorithm is applied to long-term real mission profile data. This would grant a better understanding of the real-world trade-offs between energy generated and lifetime improvement when using the proposed algorithm, as well as shortening study cycle times. The neural network, when applied to 365 days of data, was 28 times faster than using standard electrothermal modeling, and the lifetime consumption was predicted with greater than 96.5% accuracy. Energy generated was predicted with greater than 99.5% accuracy. The proposed algorithm resulted in a 3.3% reduction in lifetime consumption with a 1.0% reduction in the total energy generated. There is a demonstrated trade-off between lifetime consumption reduction and energy-generated reduction. The results are also split by environmental conditions. Under very variable conditions, the algorithm resulted in a 4.4% reduction in lifetime consumption with a 1.4% reduction in the total energy generated.

关键词： solar PV lifetime improvement regression neural networks active thermal control mppt algorithm power converter reliability

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Series Arc Fault Characteristics and Detection Method of a Photovoltaic System

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ENERGIES 2023年第24期16卷 8016页

作者： Pang, Ruiwen Ding, Wenfang Hubei Univ Technol Sch Elect & Elect Engn Wuhan 430068 Peoples R China

The DC arc is the main cause of fire in photovoltaic (PV) systems. This is due to the fact that the DC arc has no zero-crossing point and is prone to stable combustion. Failure to detect it in a timely manner can seriously endanger the PV system. This study analyzes the influences of the series arc and the maximum power point tracking (mppt) algorithm on the PV output characteristics based on the PV equivalent circuit module. The PV voltage and current variation characteristics are obtained when the series arc occurs. The findings indicate that the input voltage of the converter remains unchanged due to the mppt algorithm before and after the series arc occurs. Furthermore, the PV faulty string output current will drastically decrease when the series arc fault occurs. On this basis, a series arc detection method based on the current change is proposed, suppressing the combustion of the series arc by increasing the target voltage of the mppt algorithm. The experimental results show that the proposed method can effectively detect and extinguish the series arc in the PV system within 0.6 s. Compared to the other methods, the proposed method can be integrated into the PV system without additional hardware.

关键词： photovoltaic system series arc detection mppt algorithm series arc extinguishing

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