• Journal of Power Electronics
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• v.9 no.4
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• pp.604-611
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• 2009

A dP/dV feedback-controlled MPPT (Maximum Power Point Tracking) method for photovoltaic power systems using II-SEPIC (Isolated Inverse-SEPIC; Single Ended Primary Inductance Converter) is presented and a current-mode dP/dV feedback-controlled MPPT method is devised to apply for the PV power converter system. A control strategy for the current-mode dP/dV feedback control system is developed in this paper and the proposed MPPT shows relatively satisfactory dynamics against rapidly changing insolation conditions. In order to verify the validity and effectiveness of the proposed method, simulations and experiments of the PV power system using II-SEPlC converter are performed. These simulation and experiment results show that the proposed method enables the PV power system to extract maximum power from the photovoltaic module against the solar insolation variation.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.9
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• pp.74-82
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• 2013

This paper presents a novel maximum power point tracking for a photovoltaic power (PV) system with a direct control plan. Maximum power point tracking (MPPT) must usually be integrated with photovoltaic (PV) power systems so that the photovoltaic arrays are able to deliver maximum available power. The maximum available power is tracked using specialized algorithms such as Perturb and Observe (P&O) and incremental Conductance (indCond) methods. The proposed method has the direct control of the MPPT algorithm to change the duty cycle of a dc-dc converter. The main difference of the proposed system to existing MPPT systems includes elimination of the proportional-integral control loop and investigation of the effect of simplifying the control circuit. The proposed method thus has not only faster dynamic performance but also high tracking accuracy. Without a conventional controller, this method can control the dc-dc converter. A simulation model and the direct control of MPPT algorithm for the PV power system are developed by Matlab/Simulink, SimPowerSystems and Matlab/Stateflow.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.212-216
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• 2011

Fault detection technique for photovoltaic power systems is significant to dramatically reduce economic damage in industrial fields. This paper presents a novel fault detection approach using Fourier neural networks and stochastic decision making strategy for photovoltaic systems. We achieve neural modeling to represent its nonlinear dynamic behaviors through a gradient descent based learning algorithm. Next, a general likelihood ratio test (GLRT) is derived for constructing a decision malling mechanism in stochastic fault detection. A testbed of photovoltaic power systems is established to conduct real-time experiments in which the DC power line communication (DPLC) technique is employed to transfer data sets measured from the photovoltaic panels to PC systems. We demonstrate our proposed fault detection methodology is reliable and practicable over this real-time experiment.

• Proceedings of the KIEE Conference
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• 2004.04a
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• pp.187-191
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• 2004

Photovoltaic and wind power generation have an advantage of unpolluted and unlimited amount of energy resource. Since there is such an advantage in these energies, But photovoltaic system and wind system cannot always generate stable output with ever-changing weather condition. In this paper, the auxiliary power generator for hybrid system(photovoltaic 500[W], wind power generation 400[W]) was suggested. the auxiliary power generator that uses elastic energy of spiral spring to photovoltaic system was also added for present system. when output of photovoltaic system gets lower than 24[V], power was continuously supplied to load through the inverter by charging energy of spiral spring operates in DC generator.

• Transactions on Electrical and Electronic Materials
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• v.18 no.1
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• pp.30-34
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• 2017

The building integrated photovoltaic system (BIPV) attracts attention with regard to the future of the photovoltaic (PV) industry. It is because one of the promising national and civilian projects in the country. Since land area is limited, there is considerable interest in BIPV systems with a variety of angles and shapes of PV panels. It is therefore expected to be one of the major fields for the PV industry in the future. Since the irradiation is different from each installation angle, the output can be predicted by the angles. This is critical for a PV system to be operated at maximum power and use an efficient design. The development characteristics of tilted angles based on data results obtained via long-term monitoring need to be analyzed. The ratio of the theoretically available and actual outputs is compared with the installation angles of each PV module to provide a suitable PV system for the user.

• Current Photovoltaic Research
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• v.4 no.2
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• pp.80-86
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• 2016

Since the last five years it has become a lot of solar power plants installed. However, by installing the large-scale solar power station it is not easy to predict the actual generation years. Because there are a variety of factors, such as changes daily solar radiation, temperature and humidity. If the power output can be measured accurately it predicts profits also we can measure efficiency for solar power plants precisely. Therefore, Prediction of power generation is forecast to be a useful research field. In this study, out discovering the factors that can improve the accuracy of the prediction of the photovoltaic power generation presents the means to apply them to the power generation amount prediction.

• Proceedings of the KIEE Conference
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• 2009.04a
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• pp.46-48
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• 2009

This paper aims to investigate generation conditions necessary for the most efficient generation by measuring electricity power under various irradiation conditions, since the photovoltaic generation system has high costs and low efficiency. In addition, because the irradiation varies hourly, daily, monthly, and yearly, the research on the irradiation necessary for photovoltaic generation was carried out by analyzing the pattern o( Bower under various irradiation conditions. Also, after measuring the daily variations of irradiation and generation power, the monthly accumulated irradiation and monthly accumulate power which had the most generation power were investigated and the pattern of the annual generation power was analyzed. The results of this study are as follows. As for the relationship between the photovoltaic generation system and the irradiation, the generation power increased with the irradiation and when the irradiation was more than 600 $[W/m^2]$ the generation power amounted to more than 100 [Wh] as the resonable result.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.353-360
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• 2016

Recently, solar photovoltaic(PV) power generation which generates electrical power from solar panels composed of multiple solar cells, showed the most prominent growth in the renewable energy sector worldwide. However, in spite of increased demand and need for a photovoltaic power generation, it is difficult to early detect defects of solar panels and equipments due to wide and irregular distribution of power generation. In this paper, we choose an optimal machine learning algorithm for estimating the generation amount of solar power by considering several panel information and climate information and develop a defect detection system by using the chosen algorithm generation. Also we apply the algorithm to a domestic solar photovoltaic power plant as a case study.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.984-993
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• 2014

In this paper, we propose a design for an efficient hybrid LED street lighting management system using standalone solar photovoltaic. The proposed efficient hybrid LED street lighting management system was composed of hybrid power conditioning system, gateways, LED street lights and a monitoring server. The hybrid power conditioning system was designed to charge produced power by solar photovoltaic panels in day time, and supply power to the LED street lights in night time. If there is insufficient power, the system was designed to operate using firm power, because the system utilizes photovoltaic power. A system control algorithm allied to the lighting management system, and experimented by being configured to the functions that are able to perform real-time monitoring and remote control through the lighting management system even when absent. In the result of the efficiency analysis of the hybrid lighting management system proposed in this paper, we were able to increase the energy efficiency compared to existing lighting control systems by reducing power consumption and electricity costs.

• Journal of the Korean Society for Railway
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• v.20 no.4
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• pp.474-481
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• 2017

When designing photovoltaic power plants in Korea, the prediction of photovoltaic power generation at the design phase is carried out using PVSyst, PVWatts (Overseas power generation prediction software), and overseas weather data even if the test site is a domestic site. In this paper, for a comparative study to predict power generation using weather information, domestic photovoltaic power plants in two regions were selected as target sites. PVsyst, which is a commercial power generation forecasting program, was used to compare the accuracy between the predicted value of power generation (obtained using overseas weather information (Meteonorm 7.1, NASA-SSE)) and the predicted value of power generation obtained by the Korea Meteorological Administration (KMA). In addition, we have studied ways to improve the prediction of power generation through comparative analysis of meteorological data. Finally, we proposed a revised solar power generation prediction model that considers climatic factors by considering the actual generation amount.