• 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.

• Journal of Power Electronics
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• v.18 no.4
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• pp.1201-1210
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• 2018

The applications of thermoelectric generators (TEGs) have received a lot of attention both in terms of harvesting waste thermal energy and the need for multi-levels of power. It is critical to track the optimum electrical operating point using DC to DC converters controlled by a pulse that is generated through a maximum power point tracking algorithm (MPPT). In this paper, the hardware implementation of a short-current pulse algorithm has been demonstrated under steady stated and transient conditions. In addition, the MPPT algorithm has been proposed, which is one of the most effective and applicable algorithms for obtaining the maximum power point of TEGs. During this study, the proposed prototype has been validated both analytically and experimentally. It has also demonstrated successful performance, which highlights the claimed advantages of the proposed MPPT solution.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.1968-1975
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• 2009

The paper proposes a novel control algorithm for tracking maximum power of PV generation system.. The maximum power of PV array is determinated by a insolation and temperature. Prior considered the term in PV generation system is how maximum power point(MPP) is accurately tracked.. The paper proposes a fuzzy neural network(FNN) control algorithm so as to accurately track those maximum power points. The proposed control algorithm comprises the antecedence part of fuzzy rule and clustering method, multi-layer neural network in the consequent part. FNN has the advantages which are depicted both high performance and robustness in fuzzy control and high adaptive control in neural network.. Specially, it can show the outstanding control performance for parameter variations appling to non-linear character of PV array. In this paper, the tracking speed and the accuracy prove the validity through comparing a proposed algorithm with a conventional one.

• Journal of the Semiconductor & Display Technology
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• v.21 no.1
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• pp.114-118
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• 2022

The photovoltaic system is affected by various conditions such as temperature and irradiance. Because non-uniform irradiation and partial shading conditions affect the entire string of cells connected in series, a bypass diode is used to bypass the current flow normally. In order to find the maximum power point in partial shade conditions, it is necessary to estimate various methods of maximum power point tracking. In this paper, the hybrid method of MPPT using Lambert W function and perturbation & observation algorithm is proposed under partial shading conditions. The simulation results are obtained using MATLAB/Simulink and shows the improvement of the accuracy of MPPT.

• 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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.11
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• pp.67-72
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• 2011

Recently, photovoltaic generator system is widely extended by energy policy of the government. Add to this, for high efficiency of power generation per natural light unit area is needed to sun tracking system. And it is needed to condensed light generator for reducer of equipment expense. As method of solving this problem, this paper is developed multi-flat reflector sun tracking system for sun photocell maximum power generation. The system is consisted of multi-flat reflector and two axes machinery and sun location perceiver and AVR controller. GaAs 3J cell generated 6.75 times power more than silicon cell by times condensing light system. As a result, condensing light system of multi-flat reflector generated maximum power and showed reducing costs to photovoltaic generator.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.05a
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• pp.316-321
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• 2007

This paper is proposed a novel method to approximate the maximum power for a photovoltaic inverter system and tracking method. It is designed for power systems application and utilities. The proposed Maximum Power Point Tracking(MPPT) control has the advantage to provide a new simple way to approximate the optimal or rated voltage, the optimal or rated current and maximum power rating produced by a solar panel and the photovoltaic inverter. And this straightforward method will be named linear reoriented coordinates method(LRCM) with the advantage that Pmax and $V_{op}$ can be approximated using the satre variable as the dynamic model without using complicate approximations or Taylor series. Furthermore tracking method is improved over 50% photovoltaic efficiency. This paper is proposed MPPT using LRMC and tracking method using weather condition of domestic moderate program technique. This paper is proposed the experimental results to verify the effectiveness of the new methods.

• The Transactions of the Korean Institute of Power Electronics
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• v.18 no.4
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• pp.376-386
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• 2013

This paper proposes an improved Maximum Power Point Tracking method and design methods of unmanned solar vehicle system by parts of hardware, unmanned driving control and power conversion. The hardware design is offered on the weight reduction and structural reliability by using structural analysis software. The technique of curve fitting is applied to unmanned control system due to minimizing the vehicle's behavior. Furthermore, lateral controller applying actuator dynamics is robust enough to prevent performance degradation by measurement noise regarding position and heading angle. The power conversion system contains battery charger system and tapped-inductor boost converter. In the battery charger system, variable step-size MPPT is conducted for quick response of maximum power point tracking. The validity of the proposed algorithm are verified by simulations and experiments.

• 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.

• Journal of Power Electronics
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• v.14 no.4
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• pp.722-732
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• 2014

The power-voltage (P-V) curve of photovoltaic (PV) arrays connected in parallel to bypass diodes would have several local maximum power points (LMPP) under partial shading conditions (PSC). Conventional maximum power point tracking (MPPT) methods fail to search for the global maximum power point (MPP) because the searched peak point may remain at the LMPP on the P-V curve under PSC. This study proposes an improved MPPT algorithm to ensure that PV arrays operate at global maximum power point (GMPP) under PSC. The proposed algorithm is based on a critical study and a series of observations of PV characteristics under PSC. Results show the regularity of voltage interval between LMPPs. The algorithm has the advantages of rapidly reaching GMPP, maintaining stability, and recovering GMPP quickly when the operating condition changes. Simulation and experimental results demonstrate the feasibility of the proposed algorithm.