• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.2
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• pp.99-104
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• 2019

Solar power generation systems require maximum power point tracking (MPPT) control to acquire maximum power using inefficient and high-cost PV modules. Most conventional MPPT algorithms are based on the slope-tracking concept. The perturb and observe (P&O) algorithm is a typical slope-tracking method. The two factors that determine the MPPT performance of P&O algorithm are the MPPT control period and the magnitude of the perturbation voltage. The MPPT controller quickly moves to the new maximum power point at insolation change when the perturbation voltage is set to large, and the error of output power will be huge in the steady state even when insolation is not changing. The dynamics of the MPPT controller can be accelerated even though the perturbation voltage is set to small when the MPPT control period is set to short. However, too short MPPT control period does not improve MPPT performance but consumes the MPPT controller resources. Therefore, analyzing the performance of the MPPT controller is necessary for actual insolation conditions in real weather environment to determine the optimum MPPT control period and the magnitude of the perturbation voltage. This study proposes an optimum MPPT control period that maximizes MPPT efficiency by measuring and analyzing actual insolation profiles in typical clear and cloudy weather in central Korea.

• Journal of Power Electronics
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• v.14 no.6
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• pp.1281-1292
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• 2014

Photovoltaic (PV) solar systems with series-connected module integrated converters (MICs) are receiving increased attention because of their ability to create high output voltage while performing local maximum power point tracking (MPPT) control for individual solar panels, which is a solution for partial shading effects in PV systems at panel level. To eliminate the partial shading effects in PV system more effectively, sub-MICs are utilized at the cell level or grouped cell level within a PV solar panel. This study presents the results of a series-output-connection MPPT (SOC-MPPT) controller for sub-MIC architecture using a single sensor at the output and a single digital MPPT controller (sub-MIC SOC-MPPT controller and architecture). The sub-MIC SOC-MPPT controller and architecture are investigated based on boost type sub-MICs. Experimental results under steady-state and transient conditions are presented to verify the performance of the controller and the effectiveness of the architecture.

• 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.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.5
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• pp.484-493
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• 2011

The MPPT algorithm using neuro-fuzzy controller is proposed to improve the performance of fuzzy controller in this paper. The width of membership function and fuzzy rule have an effect on the performance of fuzzy controller. The neuro-fuzzy controller has the response characteristic which is superior to the existing fuzzy controller, because of using the optimal width of the fuzzy membership function through the neural learning. The superior control characteristic of a proposed algorithm is confirmed through simulation and experiment results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.471-478
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• 2011

This paper proposes a method of maximum power point tracking (MPPT) using fuzzy logic control for grid-connected photovoltaic systems (PV). First, for the purpose of comparison, because of its proven and good performances, the incremental conductance (IncCond) technique is briefly introduced. A double fuzzy logic controller (DFLC) based MPPT is then proposed which has shown better performances compared to the IncCond MPPT based approach. Modeling and Simulation in grid-connected PV system results are provided for both controllers under same atmospheric condition based PSCAD/EMTDC. The double fuzzy logic MPPT controller is then simulated and evaluated, which has shown better performances.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.35-38
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• 2018

This paper describes a low-power MPPT interface for DC-type energy harvesting sources. The proposed circuit consists of an MPPT controller, a bias generator, and a voltage detector. The MPPT controller consists of an MPG (MPPT Pulse Generator) with a schmitt trigger, a logic gate operating according to energy type (light, heat), and a sample/hold circuit. The bias generator is designed by employing a beta multiplier structure, and the voltage detector is implemented using a bulk-driven comparator and a two-stage buffer. The proposed circuit is designed with $0.35{\mu}m$ CMOS process. The simulation results show that the designed circuit consumes less than 100nA of current at an input voltage of less than 3V and the maximum power efficiency is 99.7%. The chip area of the designed circuit is $1151{\mu}m{\times}940{\mu}m$.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.10
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• pp.1865-1874
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• 2011

This paper proposes a novel maximum power point tracking(MPPT) using a new fuzzy control(NFC) algorithm for robust in insolation variation. Maximum power point(MPP) of solar cell has to achieve for improving output efficiency because it is changed with insolation and temperature. Conventional MPPT controller such as constant voltage(CV), perturbation and observation(PO) and incremental conductance(IC) are researched. But these controller have the problem that is failure to MPP with environment changing. The proposed NFC controller is based the fuzzy control algorithm and able to robust control with environment changing. Also the proposed controller of PV system is modeled by PSIM and the response characteristics according to the parameter variation is compared and analyzed. The validity of this controller is proved through response results.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.2
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• pp.27-32
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• 2015

A maximum power point tracking (MPPT) algorithm using fuzzy controller was considered. MPPT method was implemented based on the voltage and reference PV voltage value was obtained from Artificial Neural Network (ANN)-model of PV modules. Therefore, measuring only the PV module voltage is adequate for MPPT operation. Fuzzy controller is used to directly control dc-dc buck converter. The simulation results have been used to verify the effectiveness of the algorithm. The proposed method is compared with conventional PO(perturbation & observation), IC(Incremental Conductance) method. The nonlinearity and adaptiveness of fuzzy controller provided good performance under parameter variations such as solar irradiation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1864-1871
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• 2012

This paper proposes the hybrid proportional integral(HBPI) 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 and influence of a shadow. The MPPT control is a very important technique in order to increase an output and efficiency of the photovoltaic system. The conventional constant voltage(CV), 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, in order to solve these problems, this paper proposes HBPI controller that is adjusted gain of conventional PI control using fuzzy control, and the maximum power point tracks using this controller. The validity of the controller proposed in this paper proves through the results of the comparisons.

• Solar Energy
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• v.18 no.1
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• pp.27-34
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• 1998

A maximum power point tracking(MPPT) converter, to enhance the converter efficiency is evaluated within the laboratory. The converter is controlled to track the maximum power point of the input photovoltaic(PV) source by varying the input and output parameter-conditions of irradiation, temperature, etc. The purpose of this paper is to develop a new maximum power point tracking(MPPT) using neural controller. Neural controller are applied to control of MPPT by boosting converter duty ratios compensation effect with 8 bit single chip 8051 microcontroller.