Maximum Power Point Tracking Controller Connecting PV System to Grid (original) (raw)
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Sensorless Fuzzy Logic Controller for Maximum Power point Tracking of Grid Connected PV System
The photovoltaic (PV) generators have a nonlinear V-I characteristics and maximum power points which vary with the illumination level and temperature. Using maximum power point tracker (MPPT) with the intermediate converter can increase the system efficiency by matching the PV systems to the load. This paper presents a sensorless MPPT based on the principle of power equilibrium at dc link using Fuzzy Logic Controller (FLC).
… Society Winter Meeting …, 2002
This paper proposes a method of maximum power point tracking using adaptive fuzzy logic control for grid-connected photovoltaic systems. The system is composed of a boost converter and a single-phase inverter connected to a utility grid. The maximum power point tracking control is based on adaptive fuzzy logic to control a switch of a boost converter. Adaptive fuzzy logic controllers provide attractive features such as fast response, good performance. In addition, adaptive fuzzy logic controllers can also change the fuzzy parameter for improving the control system. The single phase inverter uses predictive current control which provides current with sinusoidal waveform. Therefore, the system is able to deliver energy with low harmonics and high power factor. Both conventional fuzzy logic controller and adaptive fuzzy logic controller are simulated and implemented to evaluate performance. Simulation and experimental results are provided for both controllers under the same atmospheric condition. From the simulation and experimental results, the adaptive fuzzy logic controller can deliver more power than the conventional fuzzy logic controller. q
Implementation of a novel fuzzy-logic based MPPT for grid-connected photovoltaic generation system
2011 IEEE Trondheim PowerTech, 2011
This paper presents modeling and simulation of a grid connected photovoltaic (PV) generation system with maximum power point tracking (MPPT) using a novel fuzzy logic controller (FLC). The system is composed of a PV array, boost converter with MPPT and a single phase inverter connected to utility grid. The MPPT is based on fuzzy logic to control IGBT switch of the boost converter. The performance of the proposed FLC for MPPT is evaluated by simulation and the results show that the FLC is more efficient in finding the maximum power point than the conventional incremental conductance method when the PV system is subjected to variations in external operating conditions (insulation level and module temperature). . Her current research interests concern FACTS technology, harmonic analysis and electrical system automation and decentralised control. Giovanni Brusco (Italy, 1980) received his degree in Electronics Engineering from the University of Calabria, Italy, in 2007. He is actually a PhD student at the University of Calabria. His current research interests concern renewable energy sources and distributed generation.
Fuzzy logic control based maximum power point tracking technique in standalone photovoltaic system
International Journal of Power Electronics and Drive Systems (IJPEDS), 2023
This study describes the development of a smart technique for tracking the highest power point on a standalone photovoltaic (SAPV) system when temperature and irradiance conditions are changing using fuzzy logic control (FLC). The PV systems comprises of a PV array, a boost converter, a controller for tracking the maximum power point, and an inverter to power the AC loads. The FLC-based maximum power point tracking (MPPT) is proposed because the technique is not complex and does not need a deep comprehension of the particular model of the system. Furthermore, the technique is efficient and fast response in tracking maximum power (MP) from the PV array. The technique overcame the limitation of the conventional MPPT technique that resulted in slow tracking of the MP and was not accurate on the optimal position of the PV array output power. The SAPV system is integrated with the sealed lead acid (SLA) battery bank as an alternative power source and makes up for power shortages by supplying energy to the load without interruption during power shortages. A system for managing the battery has been included in the system to preserve the battery's longevity by controlling the battery's charging process. The PV system is able to supply single-phase output AC voltage of 230 Vrms and has low total harmonic distortion (THD) that is suitable for home appliances. The achieved simulation results demonstrate the effectiveness of the suggested fuzzy logic controller in tracking the MPP.
Maximum Power Point Trackingfor single phase photovoltaic system using fuzzy logic
2018
A modeling technique for maximum power point tracking using fuzzy logicof PV systemis presented in this paper. The main focus of this paper is to simplify modeling of single phase PV system. Then a fuzzy logic based maximum power point has been implemented. Thiswill help to track power efficiently. Keywords—FuzzyLogic,MPPT,PV model, MATLAB/SIMULINK.
MPPT and Power Factor Control for Grid Connected PV Systems with Fuzzy Logic Controllers
International Journal of Power Electronics and Drive Systems (IJPEDS)
Two fuzzy logic controllers are proposed in this paper to control a three phase inverter for grid connected photovoltaic system. The first controller was used to predict the DC voltage that allows the three phase inverter to track the maximum power point of photovoltaic array under different environmental conditions such as irradiances and temperature. The second was used to control the active power and reactive power injected into the grid in order to inject the maximum active power produced by photovoltaic systems into grid with high efficiency and low total harmonic distortion using the same three phase inverter. The system components are photovoltaic array, DC link voltage, three-phase inverter, inverter control, LC filter, transformer and grid. To verify the effectivnesse of the introdueced system, modeling and simulation are verified in Matlab/Simulink due to its frequent use and its effectiveness.
MPPT & Power Factor Control for Grid Connected PV Systems with Fuzzy Logic Controllers
International Journal of Power Electronics and Drive System(IJPEDS), 2018
Two fuzzy logic controllers are proposed in this paper to control a three phase inverter for grid connected photovoltaic system. The first controller was used to predict the DC voltage that allows the three phase inverter to track the maximum power point of photovoltaic array under different environmental conditions such as irradiances and temperature. The second was used to control the active power and reactive power injected into the grid in order to inject the maximum active power produced by photovoltaic systems into grid with high efficiency and low total harmonic distortion using the same three phase inverter. The system components are photovoltaic array, DC link voltage, three-phase inverter, inverter control, LC filter, transformer and grid. To verify the effectivnesse of the introdueced system, modeling and simulation are verified in Matlab/Simulink due to its frequent use and its effectiveness.
International Journal of Academic Research in Economics and Management Sciences
The performance of the Photovoltaic (PV) System is dependent upon the environment conditions due to the variation of the solar irradiance and cell temperature. This affects the quality of the output voltage that is generated by the photovoltaic modules. To overcome these challenges, an artificial intelligence approach is implemented into the system. The objective of the proposed work is to develop a boost converter to control the output power generated by the photovoltaic modules by increasing the output power. In order to adjust power factor and power for a threephase grid inverter system, the boost converter is integrated with a three-phase inverter that uses the Pulse Width Modulation (PWM) control approach. Since it's the most important component of any grid-connected system and enables the source generated to feed into the grid, it evolved to control power to the grid. Therefore, the three-phase inverter with PWM control is proposed to optimize the performance of the PV system. A Fuzzy Logic Control (FLC) is implemented in the system as an artificial intelligence alternative for a PV system that works rapidly, accurately, and efficiently to track the Maximum Power Point (MPP) under varying weather conditions and solar irradiation. By using the FLC, the constraints that come from conventional technologies could be improved and a better grid-connected photovoltaic system be provided. The proposed PV system is modelled and simulated in MATLAB/Simulink. The simulations results are presented.
Renewable Energy and Power Quality Journal, 2015
Most of the Maximum Power Point Tracking (MPPT) techniques for Photovoltaic (PV) system utilize the PV voltage and current measurements. An MPPT technique for grid connected PV system, which does not require PV measurements, is proposed and implemented. This approach utilizes post-stage inverter current instead of calculating solar array power. This approach is called Power Conditioning System (PCS). PCS requires a searching engine to track the Maximum Power Point (MPP) of the PV system. Fuzzy logic is one of the most powerful MPPT engines, which has high performance and robustness. Therefore, Fuzzy Logic Control (FLC) method is implemented and compared with the other methods. Moreover a proposed method that combines FLC with PCS is designed and tested. In addition, the PCS employing an adaptive fuzzy controller is also designed in order to enhance system performance and robustness. To compare between classical MPPT techniques and the proposed techniques, simulations of overall system using different MPPT techniques are performed. The simulation results are analysed. Moreover, Practical implementation is carried out to validate the simulation results.