• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11b
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• pp.153-156
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• 2001

Maximum Power Point Tracking(MPPT) is used in wind power generation systems to maximize wind power turbin output power, irrespective of wind speed conditions and of the load electrical characteristics. In this paper we do the equivalent modeling the mechanical energy of wind power turbine according to wind speed into the synchronous generator. We analyse the equivalent modeling output part of rectifier into DC/DC converter input part theoretically. We design a control algorithm for variable voltage according to wind speed intensity and density so that load voltage of chopper is controlled steadily using the maximum power point tracking (MPPT) control method. We analyse a battery charging characteristics and a charging circuit for power storage enabling the supply of stable power to the load. We design a system and do the modeling of it analytically so that it supplies a stable power to the load by constructing a DC-AC inverter point. Also we design a charging circuit usable in actual wind power generation system of 30kW and confirm its validity.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2001.11a
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• pp.153-156
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• 2001

Maximum Power Point Tracking(MPPT) Is used in wind power generation systems to maximize wind power turbin output power, irrespective of wind speed conditions and of the load electrical characteristics. In this paper we do the equivalent modeling the mechanical energy of wind power turbine according to wind speed into the synchronous generator. We analyse the equivalent modeling output part of rectifier into DC/DC converter input part theoretically. We design a control algorithm for variable voltage according to wind speed intensity and density so that load voltage of chopper is controlled steadily using the maximum power point tracking(MPPT) control method. We analyse a battery charging characteristics and a charging circuit for power storage enabling the supply of stable power to the load. We design a system and do the modeling of it analytically so that it supplies a stable power to the load by constructing a DC-AC inverter point. Also we design a charging circuit usable in actual wind power generation system of 30kW and confirm its validity.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.2
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• pp.9-18
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• 2014

This paper proposes the fuzzy PI controller for maximum power point tracking(MPPT) control of photovoltaic system. The output characteristics of the solar cell are a nonlinear and affected by a temperature, the solar radiation. The MPPT control is a very important technique in order to increase an output and efficiency of the photovoltaic system. The conventional perturbation and observation(PO) and incremental conductance(IC) are the method which finding maximum power point(MPP) by the continued self-excitation vibration, and uses the fixed step size. If the fixed step size is a large, the tracking speed of maximum power point is faster, but the tracking accuracy in the steady state is decreased. On the contrary, when the fixed step size is a small, the tracking accuracy is increased and the tracking speed is slower. Therefore, this paper proposes the MPPT control using the fuzzy PI controller that can be improve a MPPT control performance. The fuzzy PI controller is adjusted a input of PI controller by fuzzy control and compensated a cumulative error of fuzzy control by PI controller. The fuzzy PI MPPT control is compared to conventional PO and IC MPPT method for various temperature and radiation condition. This paper proves the validity of the fuzzy PI controller using these results.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.635-638
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• 2001

Photovoltaic (PV) pumping systems with maximum power point tracking (MPPT) technique aims at obtaining the highest possible power to the pump under various insolation and temperature, thus overcomes the mismatch between the photovoltaic panel and the pumping load. A simple method of tracking the maximum power points and forcing the system to operate close to these points is presented in this paper. The MC68HC908GP32 micro control unit (MCU) is employed to implement the proposed MPPT controller. Experimental results will also show the performances of the photovoltaic pumping system with the MPPT technique.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.1256-1258
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• 2003

The solar cells should be operated at the maximum power point because its output characteristics are greatly fluctuate on the variations of insolation, temperature and loads. To obtain maximum power from solar cell, photovoltaic system cell power system usually requires maximum power point tracking controller. This paper propose Maximum power point tracking method using zero slope of differential value of maximum power. The power compare method traces to maximum power point rapidly but oscillate on the maximum power point largely, when quantity insolation variation is big. The power compare method is traces to maximum power point slowly but oscillate maximum point on the maximum power point smally, when quantity insolation variation is small. To solve two problem of the power compare method, designed zero slope of differential value of maximum power.

• 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.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.1
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• pp.1-5
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• 2020

Solar power generation systems require maximum power point tracking (MPPT) control to operate PV panels at their maximum power point (MPP). Most conventional MPPT algorithms are based on the slope-tracking concept. A typical slope-tracking method is the perturb and observe (P&O) algorithm. The P&O algorithm measures the current and voltage of a PV panel to find the operating point of the voltage at which the calculated power is maximized. However, the measurement error of the sensor causes irregularity in the calculation of the generated power and voltage control. This irregularity leads to the problem of not finding the correct MPP operating point. In this work, the power output of a PV panel based on the P&O algorithm is simulated by considering the insolation profiles from typical clear and cloudy weather conditions and the errors of current and voltage sensors. Simulation analysis suggests the optimal control period and perturbation voltage of MPPT to maximize its target efficiency under real weather conditions with sensor tolerance.

• 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.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.3
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• pp.159-166
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• 2021

This study compares the maximum power point tracking (MPPT) control methods of a thermoelectric generator on vehicles. The researchers conduct comparisons on five different MPPT methods, including a fractional open circuit voltage method, a perturbation and observation (P&O) method, an incremental conductance method, a linear extrapolation-based MPPT (LEMPPT) method, and a LEMPPT/P&O hybrid method. These five MPPT methods are theoretically analyzed in detail, and the comparisons are conducted through MATLAB/Simulink simulation results. The comparison outcomes reveal that linear MPPT methods, including LEMPPT and LEMPPT/P&O hybrid methods, are more suitable for a thermoelectric generator on vehicles than the other MPPT methods examined in this work.

• KSBB Journal
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• v.29 no.4
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• pp.225-231
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• 2014

A microbial fuel cell (MFC) and bioelectrochemical systems are novel bioprocesses which employ exoelectrogenic biofilm on electrode as a biocatalyst for electricity generation and various useful chemical production. Previous reports show that electrogenic biofilms of MFCs are time varying systems and dynamically interactive with the electrically conductive media (carbon paper as terminal electron acceptor). It has been reported that maximum power point tracking (MPPT) method can automatically control load by algorithm so that increase power generation and columbic efficiency. In this study, we developed logic based control strategy for external load resistance by using $LabVIEW^{TM}$ which increases the power production with using flat-plate MFCs and MPPT circuit board. The flat-plate MFCs inoculated with anaerobic digester sludge were stabilized with fixed external resistance from $1000{\Omega}$ to $100{\Omega}$. Automatic load control with MPPT started load from $52{\Omega}$ during 120 hours of operation. MPPT control strategy increased approximately 2.7 times of power production and power density (1.95 mW and $13.02mW/m^3$) compared to the initial values before application of MPPT (0.72 mW and $4.79mW/m^3$).