• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.1
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• pp.33-38
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• 2006

This paper proposes a simple MPPT control scheme of a based Current-Control-Loop system that can be obtains a lot of advantage to compare with another digital control method, P&O(Perturbation and Observation) and IncCond(Incremental Conductance) algorithm, that is applied mostly a PV system. An existent method is needed an expensive processor such as DSP that calculated to change the measure power of a using current and voltage sensor at the once. Therefore, it is applied a small home power generation system that required many expenses. But, a proposed method is easy to solve the cost reduction and power unbalance Problems that it is used by control scheme to limit error of a current control of common sensor. This proposed algorithm had verified through a simulation and an experiment results on battery charger using PIC that is the microprocessor of a low price.

• 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.

• Journal of the Korean Solar Energy Society
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• v.31 no.2
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• pp.16-21
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• 2011

Since the maximum power operating point(MPOP) of PCS alters with changing atmospheric conditions temperature conditions shadow conditions it is important to operate for PCS to keep maximum power point tracking(MPPT) continuously. This paper presents the results of modeling PV system by PSIM simulator and investigates the influence on the PV system from aspect of power quality i.e. voltage drop. This paper investigates four MPPT algorithms; Perturbation & Observation(P&O) Improved P&O Incremental Conductance(Incond) Differential coefficient method simulated with irradiation temperature change and shadow conditions.

• Journal of Advanced Marine Engineering and Technology
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• v.33 no.4
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• pp.588-594
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• 2009

The maximum power point operation point(MPPOP) of photovoltaic(PV) power generation systems changes with varying atmospheric conditions such as temperature, solar radiation. For achieving a high efficiency in PV system, it is very important for PV system to track the MPPOP correctly according to operation condition. Although the MPPT(maximum power point tracking) algorithm which applied P&O(Perturbation & Observation) or IncCnd(Incremental Conductance) algorithm tracks the MPPOP efficiently, its efficiency drops noticeably in case that the incidence angle of PV panel on buoy changes rapidly. To solve this problem, this paper proposes maximum power point searching and tracking algorithm(MPPST). The proposed algorithm set the specific area and measures the PV voltage at the same interval. The proposed algorithm have been obtained high efficiency than P&O algorithm through ocean experiment.

• Journal of the Korean Solar Energy Society
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• v.39 no.2
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• pp.1-9
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• 2019

In order to increase the power generation efficiency of the photovoltaic system, a new algorithm that can follow the maximum power point of the photovoltaic power generation system having nonlinear output characteristics is proposed. Conventional maximum power point tracking (MPPT) algorithms such as Perturbation and Observation (P&O) and InCond (Increment and Conductance) schemes can not find the global maximum power point at a plurality of pole points in the unmatched state of unbalanced PV modules. However, even if the global maximum power point is found at a plurality of pole points, the global maximum power that can not be the real maximum power by the photovoltaic generation system. In order to solve this problem, a few PV companies propose installing several small PV inverters instead of if big one. However, since this will require additional costs, we herein propose a Multi-MPPT system using individual 3-point MPPT to track true MPPT at a plurality of pole points in the unmatched state of unbalanced PV modules.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.228-229
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• 2007

현재까지 계통연계형 태양광 시스템의 최대전력추종(MPPT)방법에 대한 많은 연구가 진행되고 있다. 그 중 대표적인 최대 전력 추종 방법에는 일정전압 제어방식, P&O(Perturbation and Observation)제어방식, IncCond(Incremental Condutance) 제어 방식이 있다. 이 중 일정전압 제어방식은 일사량, 온도 등을 고려해 특정한 값의 태양전지 출력전압을 고정시키도록 하여, 최대전력점 근처에서 동작하도록 제어하는 방식이다. 이 방식은 태양전지 입력 전류 센서가 필요없고, 저일사량 조건에서 다른 기법에 비해 우수한 효율 특성을 나타내고 있다. 하지만, 온도 및 일사 조건에 따라 변하는 최대전력전압지점을 추종하지 못해 다양한 조건에서 최대전력추종효율이 떨어지는 단점이 있다. 이에 본 논문에서는 다양한 일사 조건 및 온도 조건에 대응하는 최대 출력전압을 실시간으로 산출하여, 이를 통해 최대전력추종제어를 하는 방법을 제안하고자 한다. 제안된 기법은 다양한 일사조건 및 온도변화에 대해 능동적으로 대응하여 우수한 추종효율 특성을 나타내고, 또한 입력 DC 전류 센서를 제거하고, 내부 연산이 간단함으로써 경제적인 면에서 유리하다. 본 논문에서 제안된 최대전력 추종기법의 타당성을 검증하기 위해서 PSIM 시뮬레이션을 통해 그 타당성을 검증 하였다.

• The Journal of Korean Institute of Information Technology
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• v.17 no.9
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• pp.19-30
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• 2019

Photovoltaic power generation requires MPPT algorithm to track stable and efficient maximum power output power point according to external changes such as solar radiation and temperature. This study implemented a model that could track MPP more quickly than original MPPT algorithm using artificial neural network. The proposed model finds the current and voltage of MPP using the original MPPT algorithm for various combinations of insolation and temperature for training data of artificial neural networks. The acquired MPP data was learned using the input node as insolation and temperature and the output node as the current and voltage. The Experiment results show tracking time of the original algorithms P&O, InC and Fuzzy were respectively 0.428t, 0.49t and 0.4076t for the 0t~0.3t range, and MPP tracking time of the proposed model was 0.32511t and it is 0.1t faster than the original algorithms.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.8
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• pp.549-557
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• 2019

In this paper, we focus on the real-time detection method of a seismic ionospheric disturbance using Global Navigation Satellite System (GNSS) signal. First, the monitor for the detection of the seismic ionospheric disturbance is studied based on the estimated ionospheric delay using the GNSS signals. And then, the threshold for the automatic detection is computed. Moreover, to discriminate the seismic ionospheric disturbance against the other ionospheric anomalies due to other error sources such as cycle slips, the signatures of the ionospheric perturbation caused by the seismic wave is investigated. Based on the observation, the detection strategy is proposed. Using GPS observations collected from the 47 permanent stations in South Korea and Japan, the proposed real-time detection method is evaluated.

• Journal of Integrative Natural Science
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• v.15 no.3
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• pp.99-110
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• 2022

Solar photovoltaic (PV) system shows a non-linear current (I) -voltage (V) characteristics, which depends on the surrounding environment factors, such as irradiance, temperature, and the wind. Solar PV system, with current (I) - voltage (V) and power (P) - Voltage (V) characteristics, specifies a unique operating point at where the possible maximum power point (MPP) is delivered. At the MPP, the PV array operates at maximum power efficiency. In order to continuously harvest maximum power at any point of time from solar PV modules, a good MPPT algorithms need to be employed. Currently, due to its simplicity and easy implementation, Perturb and Observe (P&O) algorithms are the most commonly used MPPT control method in the PV systems but it has a drawback at suddenly varying environment situations, due to constant step size. In this paper, to overcome the difficulties of the fast changing environment and suddenly changing the power of PV array due to constant step size in the P&O algorithm, least mean Square (LMS) methods is proposed together with P&O MPPT algorithm which is superior to traditional P&O MPPT. PV output power is predicted using LMS method to improve the tracking speed and deduce the possibility of misjudgment of increasing and decreasing the PV output. Simulation results shows that the proposed MPPT technique can track the MPP accurately as well as its dynamic response is very fast in response to the change of environmental parameters in comparison with the conventional P&O MPPT algorithm, and improves system performance.

• Journal of Advanced Navigation Technology
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• v.24 no.4
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• pp.291-298
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• 2020

This study proposed a model that can track MPP faster than the existing MPPT algorithm using the particle swarm optimization algorithm (PSO). The proposed model highly sets the acceleration constants of gbest and pbest in the PSO algorithm to quickly track the MPP point and eliminates the power instability problem. In addition, this algorithm was re-executed by detecting the change in power of the solar panel according to the rapid change in solar radiation. As a result of the experiment, MPP time was 0.03 seconds and power was 131.65 for 691.5 W/m2, and MPP was tracked at higher power and speed than the existing P&O and INC algorithms. The proposed model can be applied when a change in the amount of power is detected by partial shading in a Photovoltaic power plant with Photovoltaic connected in parallel. In order to improve the MPPT algorithm, this study needs a comparative study on optimization algorithms such as moth flame optimization (MFO) and whale optimization algorithm (WOA).