• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.281-292
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• 2016

The proposed scheme is based on the modified perturb and observe (P&O) algorithm combined with the sliding mode technique. A modified P&O algorithm based sliding mode controller is developed to study the effects of partial shade, temperature, and insolation on the performance of maximum power point tracking (MPPT) used in photovoltaic (PV) systems. Under partially shaded conditions and temperature, the energy conversion efficiency of a PV array is very low, leading to significant power losses. Consequently, increasing efficiency by means of MPPT is particularly important. Conventional techniques are easy to implement but produce oscillations at MPP. The proposed method is applied to a model to simulate the performance of the PV system for solar energy usage, which is compared to the conventional methods under non-uniform insolation improving the PV system utilization efficiency and allowing optimization of the system performance. The modified perturb and observe sliding mode controller successfully overcomes the issues presented by non-uniform conditions and tracks the global MPP. Compared to MPPT techniques, the proposed technique is more efficient; it produces less oscillation at MPP in the steady state, and provides more precise tracking.

• Journal of Power Electronics
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• v.18 no.6
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• pp.1805-1818
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• 2018

This paper proposes a novel hybrid maximum power point tracking (MPPT) algorithm combining a Whale Optimization Algorithm (WOA) and the conventional Perturb & Observation (P&O) to track/extract the highest amount of power from a solar photovoltaic (SPV) system working under partial shading conditions (PSCs). The proposed hybrid algorithm is based on a WOA which predicts the initial global peak (GP) and is followed by P&O in the final stage to achieve a quicker convergence to a GP. Thus, this hybrid algorithm overcomes the computational burden encountered in a standalone WOA, grey wolf optimization (GWO) and hybrid GWO reported in the literature. The conventional algorithm searches for the maximum power point (MPP) in the predicted region by the WOA. The proposed MPPT technique is modelled and simulated using MATLAB/Simulink for simulating an environment to check its effectiveness in accurately tracking the MPP during the GP region. This hybrid algorithm is compared with a standalone WOA, GWO and hybrid GWO. From the simulating results, it is shown that the proposed algorithm offers high tracking performance and that it increases the output power level of a SPV system under partial shading. The algorithm also verified experimentally on various PSCs.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.797-807
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• 2016

The discussion in this paper aims to introduce an approach to detect drowsiness with Android based smartphones using the OpenCV platform tools. OpenCV for Android actually provides powerful tools for real-time body's parts tracking. We discuss here about the maximization of the accuracy in real-time eye tracking. Then we try to develop an approach for detecting eye blink by analyzing the structure and color variations of human eyes. Finally, we introduce a time variable to capture drowsiness.

• ETRI Journal
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• v.39 no.1
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• pp.76-86
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• 2017

In this study, we propose an automatic contrast enhancement method based on transfer function modification (TFM) by histogram equalization. Previous histogram-based global contrast enhancement techniques employ histogram modification, whereas we propose a direct TFM technique that considers the mean brightness of an image during contrast enhancement. The mean point shifting method using a transfer function is proposed to preserve the mean brightness of an image. In addition, the linearization of transfer function technique, which has a histogram flattening effect, is designed to reduce visual artifacts. An attenuation factor is automatically determined using the maximum value of the probability density function in an image to control its rate of contrast. A new quantitative measurement method called sparsity of a histogram is proposed to obtain a better objective comparison relative to previous global contrast enhancement methods. According to our experimental results, we demonstrated the performance of our proposed method based on generalized measures and the newly proposed measurement.

• Proceedings of the KIPE Conference
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• 2012.07a
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• pp.248-249
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• 2012

PV 어레이에 부분적으로 음영이 발생하면 그 P-V 특성은 여러 개의 MPP를 보인다. 이런 상황에서는 global MPP를 찾아내기 위한 특수한 기법이 요구된다. 본 논문에서는 기존에 제안된, 부분 음영 조건 발생 시 global MPP를 찾아내는 MPPT 기법을 개선하고 실험을 통하여 유효성을 검증한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.291-298
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• 2020

The power generation of a PV system changes according to the weather variables, such as solar radiation and temperature. In particular, the output characteristics of photovoltaic systems, which are sensitive to changes in solar radiation, can be produced effectively and reliably in various weather conditions through MPPT (Maximum Power Point Tracking) control. This paper proposes a fuzzy-based MPPT control method to improve the efficiency and stability of the power production from a solar system. To verify the performance of the proposed method, under the same weather environment, the efficiency and stability of the newly proposed fuzzy logic were compared and evaluated empirically with P&O (Perturb and Observe), a representative algorithm of MPPT control. Furthermore, the circuits designed to improve the reliability and reliability of the hardware were manufactured from Printed Circuit Boards (PCB) to conduct experiments. Based on the results of the experiment during a certain period, the fuzzy-based MPPT proposed in this paper improved the efficiency by more than 4.4% compared to the MPPT based on the existing P&O algorithm and decreased the fluctuation width by more than 39.7% at the maximum power point.

• Journal of Power Electronics
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• v.17 no.2
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• pp.476-489
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• 2017

Under partial shading conditions (PSCs), multiple maximums may be exhibited on the P-U curve of string inverter photovoltaic (PV) systems. Under such conditions, heuristic methods are invalid for extracting a global maximum power point (GMPP); intelligent algorithms are time-consuming; and model-based methods are complex and costly. To overcome these shortcomings, a novel hybrid MPPT (MPF-IP&O) based on a model-based peak forecasting (MPF) method and an improved perturbation and observation (IP&O) method is proposed. The MPF considers the influence of temperature and does not require solar radiation measurements. In addition, it can forecast all of the peak values of the PV string without complex computation under PSCs, and it can determine the candidate GMPP after a comparison. Hence, the MPF narrows the searching range tremendously and accelerates the convergence to the GMPP. Additionally, the IP&O with a successive approximation strategy searches for the real GMPP in the neighborhood of the candidate one, which can significantly enhance the tracking efficiency. Finally, simulation and experiment results show that the proposed method has a higher tracking speed and accuracy than the perturbation and observation (P&O) and particle swarm optimization (PSO) methods under PSCs.

• International Journal of Reliability and Applications
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• v.13 no.2
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• pp.91-104
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• 2012

Sarhan and Kundu (2009) introduced a new distribution named as the generalized linear failure rate distribution. This distribution generalizes several well known distributions. The probability density function of the generalized linear failure rate distribution can be right skewed or unimodal and its hazard function can be increasing, decreasing or bathtub shaped. This distribution can be used quite effectively to analyze lifetime data in place of linear failure rate, generalized exponential and generalized Rayleigh distributions. In this paper, we apply the simulated annealing algorithm to obtain the maximum likelihood point estimates of the parameters of the generalized linear failure rate distribution. Simulated annealing algorithm can not only find the global optimum; it is also less likely to fail because it is a very robust algorithm. The estimators obtained using simulated annealing algorithm have been compared with the corresponding traditional maximum likelihood estimators for their risks.

• 전기의세계
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• v.21 no.3
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• pp.48-52
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• 1972

The application of pontryagin's Maximum Principle to the optimal control eventually leads to the problem of solving the two point boundary value problem. Most of problems have been related to their own special factors, therfore it is very hard to recommend the best method of deriving their optimal solution among various methods, such as iterative Runge Kutta, analog computer, gradient method, finite difference and successive approximation by piece-wise linearization. The gradient method has been applied to the optimal control of two point boundary value problem in the power systems. The most important thing is to set up some objective function of which the initial value is the function of terminal point. The next procedure is to find out any global minimum value from the objective function which is approaching the zero by means of gradient projection. The algorithm required for this approach in the relevant differential equations by use of the Runge Kutta Method for the computation has been established. The usefulness of this approach is also verified by solving some examples in the paper.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.5
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• pp.604-612
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• 2008

The ozone concentration is one of the important environmental issue for measurement of the atmospheric condition of the country. This study focuses on applying the Autoregressive Error (ARE) model for analyzing the ozone data at middle part of the Gyeonggi-Do, Anyang monitoring site in Korea. In the ARE model, eight meteorological variables and four pollution variables are used as the explanatory variables. The eight meteorological variables are daily maximum temperature, wind speed, amount of cloud, global radiation, relative humidity, rainfall, dew point temperature, and water vapor pressure. The four air pollution variables are sulfur dioxide $(SO_2)$, nitrogen dioxide $(NO_2)$, carbon monoxide (CO), and particulate matter 10 (PM10). The result shows that ARE models both overall and monthly data are suited for describing the oBone concentration. In the ARE model for overall ozone data, ozone concentration can be explained about 71% to by the PM10, global radiation and wind speed. Also the four types of ARE models for high level of ozone data (over 80 ppb) have been analyzed. In the best ARE model for high level of ozone data, ozone can be explained about 96% by the PM10, daliy maximum temperature, and cloud amount.