• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.4
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• pp.297-304
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• 2022

This study compares the performance of artificial intelligence (AI)-based maximum power point tracking (MPPT) methods under partial shading conditions in a photovoltaic generation system. Although many studies on AI-based MPPT have been conducted, few studies comparing the tracking performance of various AI-based global MPPT methods seem to exist in the literature. Therefore, this study compares four representative AI-based global MPPT methods including fuzzy logic control (FLC), particle swarm optimization (PSO), grey wolf optimization (GWO), and genetic algorithm (GA). Each method is theoretically analyzed in detail and compared through simulation studies with MATLAB/Simulink under the same conditions. Based on the results of performance comparison, PSO, GWO, and GA successfully tracked the global maximum power point. In particular, the tracking speed of GA was the fastest among the investigated methods under the given conditions.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.382-383
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• 2018

To increase the efficiency of a wind energy conversion system (WECS), the maximum power point tracking (MPPT) algorithm is usually employed. This paper proposes an optimal MPPT algorithm which tracks a sudden wind speed change condition fast. The proposed method can be implemented without the prior information on the wind turbine parameters, generator parameters, air density or wind speed. By investigating the directions of changes of the mechanical output power in wind turbine and rotor speed of the generator, the proposed MPPT algorithm is able to determine an optimal speed to achieve the maximum power point. Then, this optimal speed is set to the reference of the speed control loop. As a result, the proposed MPPT algorithm forces the system to operate at the maximum power point by using a three-phase converter. The simulation results based on the PSIM are given to prove the effectiveness of the proposed method.

• Journal of Power Electronics
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• v.12 no.3
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• pp.503-508
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• 2012

Tracking the Maximum Power Point (MPP) of a photovoltaic (PV) array is usually an essential part of a PV system. The problem addressed by Maximum Power Point Tracking (MPPT) techniques is to find the voltage $V_{MPP}$ or current $I_{MPP}$ at which a PV array should operate to generate the maximum power output $P_{MPP}$ under a given temperature and irradiance. MPPT control methods such as the perturb and observe method and the incremental conductance method require a microprocessor or DSP to determine if the duty cycle should be increased or not. This paper proposes a simple and fast analog MPPT method. The proposed control scheme tracks the MPP very quickly and its hardware implementation is simple when compared with the conventional techniques. The new algorithm can successfully track the MPP even in the case of rapidly changing atmospheric conditions. In addition, it has higher efficiency than ordinary algorithms.

• Journal of Power Electronics
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• v.16 no.1
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• pp.277-286
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• 2016

This paper offers two Maximum Power Point Tracking (MPPT) systems for Photovoltaic (PV) applications. The first MPPT method is based on a fixed frequency Model Predictive Control (MPC). The second MPPT technique is based on the Predictive Hysteresis Control (PHC). An experimental demonstration shows that the proposed techniques are fast, accurate and robust in tracking the maximum power under different environmental conditions. A DC/DC converter with a high voltage gain is obligatory to track PV applications at the maximum power and to boost a low voltage to a higher voltage level. For this purpose, a high gain Switched Inductor Quadratic Boost Converter (SIQBC) for PV applications is presented in this paper. The proposed converter has a higher gain than the other transformerless topologies in the literature. It is shown that at a high gain the proposed SIQBC has moderate efficiency.

• Journal of Power Electronics
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• v.6 no.3
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• pp.226-234
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• 2006

Photovoltaic (PV) generators have nonlinear V-I characteristics and maximum power points which vary with illumination level and temperature. Using a maximum power point tracker (MPPT) with an intermediate converter can increase the system efficiency by matching the PV systems to the load. This paper presents a maximum power point tracker based on fuzzy logic and a control scheme for a single-phase inverter connected to the utility grid. The fuzzy logic controller (FLC) provides an adaptive nature for system performance. Also the FLC provides excellent features such as fast response, good performance and the ability to change the fuzzy parameters to improve the control system. A single-phase AC-DC inverter is used to connect the PV system to the grid utility and local loads. While a control scheme is implemented to inject the PV output power to the utility grid at unity power factor and reduced harmonic level. The simulation results have shown the effectiveness of the proposed scheme.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.10
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• pp.15-19
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• 2011

We have proposed a maximum power point tracking (MPPT) circuit for thermoelectric generator (TEG) using a Boost converter. The key point of the proposed MPPT circuit is that the duty ratio of the boost converter automatically moves to Maximum Power Point by comparing of consecutive sampling voltage using two comparators. From the simulation results, we showed that the proposed circuit can find the maximum power point within 2 CLK periods and to generate optimal PWM signal within 3 CLK periods. The proposed MPPT circuit was designed by using a CMOS 0.18 um process, and it is now on the fabrication.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1075-1082
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• 2010

This paper analyzes a operating characteristic for maximum power point tracking (MPPT) of photovoltaic generation system. MPPT methods are used to maximize PV array output power by tracking maximum power point(MPP) continuously. To increase the output efficiency of PV system, it is important to have more efficient MPPT. MPPT algorithm is widely used the control method such as the perturbation and observation(PO) method, incremental conductance(IC) method and constant voltage(CV) method. In case of the radiation is changed, this paper proposes a response characteristic with MPPT control algorithms. Also, it proposes the direct for a novel MPPT control algorithm development through the analyzed data, hereby proves the effectiveness of this paper.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.7
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• pp.1039-1048
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• 2013

Generally, the buck converter controller was designed to control output voltage of the converter. However, design of the controller in photovoltaic power conditioning system is different from general design. the controller in photovoltaic power conditioning system controls input voltage of the converter(output voltage of the solar cell) for MPPT(Maximum Power Point Tracking). This paper proposes novel buck converter model which can control input voltage of the converter. We integrate this model with a model of solar cell. and linearize at the operating point(MPP). In addition, we determine whether or not suitable for the general linear controller design into small and large signal analysis.

• Journal of Power Electronics
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• v.16 no.1
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• pp.287-296
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• 2016

Conventional maximum power point tracking (MPPT) methods are ineffective under partially shaded conditions because multiple local maximum can be exhibited on power-voltage characteristic curve. This study proposes an improved cuckoo search (ICS) MPPT method after investigating the cuckoo search (CS) algorithm applied in solving multiple MPPT. The algorithm eliminates the random step in the original CS algorithm, and the conception of low-power, high-power, normal and marked zones are introduced. The adaptive step adjustment is also realized according to the different stages of the nest position. This algorithm adopts the large step in low-power and marked zones to reduce search time, and a small step in high-power zone is used to improve search accuracy. Finally, simulation and experiment results indicate that the promoted ICS algorithm can immediately and accurately track the global maximum under partially shaded conditions, and the array output efficiency can be improved.

• Advances in Energy Research
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• v.8 no.3
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• pp.185-202
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• 2022

This research work focuses to design and simulate a 200W solar power system with electrical power conservation scheme as well as thermal power conservation modeling to improve power extraction from solar power plant. Many researchers have been already designed and developed different methods to extract maximum power while there were very researches are available on improving solar power thermally and mechanically. Thermal parameters are also important while discussing about maximizing power extraction of any power plant. A specific type of coolant which have very high boiling point is proposed to be use at the bottom surface of solar panel to reduce the temperature of panel in summer. A comparison between different maximum power point tracking (MPPT) technique and proposed MPPT technique is performed. Using this proposed Thermo-electrical MPPT (TE-MPPT) with Deep Learning Algorithm model 40% power is conserved as compared to traditional solar power system models.