• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.958-959
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• 2015

This paper proposes adaptive incremental conductance(A-IC) algorithm for maximum power point tracking(MPPT) control of photovoltaic. Conventional Perturbation & Observation(PO) and IC MPPT control algorithm generally uses fixed step size. A small fixed step size will cause the tracking speed to decrease and tracking accuracy of the MPP will decrease due to large fixed step size. Therefore, this paper proposes N-IC MPPT algorithm that adjust automatically step size according to operating conditions. To improve tracking speed and accuracy, when operating point is far from maximum power point(MPP), step size uses maximum value and when operating point is near from MPP, step size uses variable step size that adjust according to slope of P-V curve. The validity of MPPT algorithm proposed in this paper prove through compare with conventional IC MPPT algorithm.

• 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 $4.79mW/m^3$).

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.379-382
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• 2013

In conventional solar energy harvesting systems, continuous perturbation techniques of the duty cycle or switching frequency of a power converter have been used to implement MPPT(Maximum Power Point Tracking) control. In this paper, we propose a new MPPT technique to control the duty cycle of a power switch powering a power converter. The proposed circuit is designed in 0.35um CMOS process, and the designed chip area including pads is $770um{\times}800um$.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.392-395
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• 2011

In this paper, a vibration energy harvesting circuit using the piezoelectric element has been designed. MPPT (maximum power point tracking control) control function has been implemented to deliver the maximum power to the load by using the electric power-voltage characteristic of the piezoelectric element. The designed MPPT circuit traces the maximum power point by sampling periodically the open circuit voltage of the full wave rectifier circuit and delivers the maximum available power to the load. The vibration energy harvesting circuit is designed with $0.18{\mu}m$ CMOS process. The maximum power efficiency is 91%, and the chip area except pads is $1,100{\mu}m{\times}730{\mu}m$.

• Journal of Power Electronics
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• v.15 no.1
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• pp.54-64
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• 2015

This paper presents a current sensorless maximum power point tracking (MPPT) control method for dual-mode photovoltaic (PV) module-type interleaved flyback inverters (ILFIs). This system, called the MIC (Module Integrated Converter), has been recently studied in small PV power generation systems. Because the MIC is an inverter connected to one or two PV arrays, the power system is not affected by problems with other inverters. However, since the each PV array requires an inverter, there is a disadvantage that the initial installation cost is increased. To overcome this disadvantage, this paper uses a flyback inverter topology. A flyback inverter topology has an advantage in terms of cost because it uses fewer parts than the other transformer inverter topologies. The MPPT control method is essential in PV power generation systems. For the MPPT control method, expensive dc voltage and current sensors are used in the MIC system. In this paper, a MPPT control method without current sensor where the input current is calculated by a simple equation is proposed. This paper also deals with dual-mode control. Simulations and experiments are carried out to verify the performance and effectiveness of the proposed current sensorless MPPT control method on a 110 [W] prototype.

• 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.

• New & Renewable Energy
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• v.8 no.3
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• pp.14-22
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• 2012

Performance of photovoltaic (PV) generator systems relies on its operating conditions. Maximum power extracted from PV generators depends strongly on solar irradiation, load impedance, and ambient temperature. A most maximum power point tracking (MPPT) algorithm is based on a perturb and observe method and an incremental conductance method. It is well known the latter is better in terms of dynamics and tracking characteristics under condition of rapidly changing solar irradiation. However, in case of digital implementation, the latter has some error for determining a maximum power point. This paper presents a PID based MPPT algorithm for such PV systems. We use neural network technique for determining PID parameters by online learning approach. And we construct a boost converter to regulate the output voltage from PV generator system. Computer simulation is carried out to evaluate the proposed MPPT method and we accomplish comparative study with a perturb and observe based MPPT method to prove its superiority.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1248-1258
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• 2019

This paper presents a moth-flame optimization (MFO)-based maximum power point tracking (MPPT) method for photovoltaic (PV) systems. The MFO algorithm is a new optimization method that exhibits satisfactory performance in terms of exploration, exploitation, local optima avoidance, and convergence. Therefore, the MFO algorithm is quite suitable for solving multiple peaks of PV systems under partial shading conditions (PSCs). The proposed MFO-MPPT is compared with four MPPT algorithms, namely the perturb and observe (P&O)-MPPT, incremental conductance (INC)-MPPT, particle swarm optimization (PSO)-MPPT and whale optimization algorithm (WOA)-MPPT. Simulation and experiment results demonstrate that the proposed algorithm can extract the global maximum power point (MPP) with greater tracking speed and accuracy under various conditions.

• Proceedings of the KIPE Conference
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• 2011.11a
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• pp.285-286
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• 2011

Maximum Power Point Tracker (MPPT) is the big issue in generating power based on Wind Energy Conversion System. In case of unknown turbine characteristic, it is useful to implement MPPT based on fuzzy logic control. This kind of control is able to find the value of duty cycle to meet maximum power point at particular wind speed. There are many methods to develop MPPT based fuzzy logic controls. In this paper, two of the methods are compared both at low and high fluctuating wind speed.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.6
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• pp.105-113
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• 2013

In this paper a micro solar energy harvesting system with MPPT(Maximum Power Point Tracking) control using a miniature PV(photovoltaic) cell of which the output is less than 0.5V is proposed. The MPPT control is implemented using linear relationship between the open-circuit voltage of a PV cell and its MPP(Maximum Power Point) voltage such that a pilot PV cell can track the MPP of the main PV cell in real time. The proposed circuit is designed in 0.18um CMOS process. The designed chip area is $900um{\times}1370um$ including a load charge pump and pads. Measured results show that the designed system can track the MPP voltage changes with variations of light intensity. The designed circuit with MPPT control delivers MPP voltages to load even though the load is heavy such that it can supply more power when the MPPT control is applied. The proposed circuit does not require any precharged battery resulting in more suitability for miniaturized self-powered systems compared to the existing works.