• Current Photovoltaic Research
• /
• v.10 no.3
• /
• pp.77-83
• /
• 2022

Renewable energy is receiving attention again as a way to realize carbon neutrality to overcome the climate change crisis. Among renewable energy sources, the installation of Photovoltaic is continuously increasing, and as of 2020, the global cumulative installation amount is about 590 GW and the domestic cumulative installation amount is about 17 GW. Accordingly, O&M technology that can analyze the power generation and fault diagnose about PV plants the is required. In this paper, a study was conducted to diagnose fault using I-V curves of PV strings and deep learning. In order to collect the fault I-V curves for learning in the deep learning, faults were simulated. It is partial shade and voltage mismatch, and I-V curves were measured on a sunny day. A two-step data pre-processing technique was applied to minimize variations depending on PV string capacity, irradiance, and PV module temperature, and this was used for learning and validation of deep learning. From the results of the study, it was confirmed that the PV fault diagnosis using I-V curves and deep learning is possible.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.19 no.1
• /
• pp.31-40
• /
• 2014

This paper describes an optimal configuration for multi-central inverters in a medium-voltage (MV) grid, which is suitable for large-scale photovoltaic (PV) power plants. We theoretically analyze a proposed common-mode equivalent model for problems associated with multi-central transformerless-type three-phase full bridge(3-FB) PV inverters employing two-winding MV transformers. We propose a synchronized PWM control strategy to effectively reduce the common-mode voltages that may simultaneously occur. In addition, we propose that the existing 3-FB topology may also have the configuration of a multi-central inverter with a two-winding MV transformer by making a simple circuit modification. Simulation and experimental results of three 350kW PV inverters in a multi-central configuration verify the effectiveness of the proposed synchronization control strategy. The modified transformerless-type 3-FB topology for a multi-central PV inverter configuration is verified using an experimental prototype of a 100kW PV inverter.

• ETRI Journal
• /
• v.45 no.6
• /
• pp.996-1006
• /
• 2023

Renewable energy is promoted massively to overcome problems that fossil fuel power plants generate. One popular renewable energy type that offers easy installation is a photovoltaic (PV) system. However, the energy harvested through a PV system is not optimal because influenced by exposure to solar irradiance in the PV module, which is constantly changing caused by weather. The maximum power point tracking (MPPT) technique was developed to maximize the energy potential harvested from the PV system. This paper presents the MPPT technique, which is operated on a new high-gain voltage DC/DC converter that has never been tested before for the MPPT technique in PV systems. Fuzzy logic (FL) was used to operate the MPPT technique on the converter. Conventional and adaptive perturb and observe (P&O) techniques based on variables step size were also used to operate the MPPT. The performance generated by the FL algorithm outperformed conventional and variable step-size P&O. It is evident that the oscillation caused by the FL algorithm is more petite than variables step-size and conventional P&O. Furthermore, FL's tracking speed algorithm for tracking MPP is twice as fast as conventional P&O.

• International journal of advanced smart convergence
• /
• v.11 no.3
• /
• pp.187-196
• /
• 2022

In this paper, we propose an example of designing and constructing a roof-type solar power plant structure equipped with a Pseudo-BIPV (Building-Integrated Photovoltaic) shape suitable for use as a roof of a small warehouse with a sandwich-type panel structure. As the characteristics of the roof-type solar power generation facility to be installed in the small warehouse proposed in this study, the shape of the roof is not a general A type, but a right-angled triangle shape with the slope is designed to face south. We chose a structure in which an inverter for one power plant and a control facility are linked by grouping several roofs of buildings. In addition, the height of the roof structure is less than 20 cm from the floor, and it has a shape similar to that of the BIPV, so it is building-friendly because it is almost in close contact with the roof. At the same time, the roof creates a reflective light source due to the white color. By linking this roof with a double-sided solar panel, we designed it to obtain both the advantage of the roof-friendliness and the advantage of efficiency improvement for the electric power generation based on the double-sided panel. Compared to the existing solar power generation facilities using A-shaped cross-sectional modules, the power generation efficiency of roofs in this case is increased by more than 11%, which we can confirm, through the comparison analysis of monitoring data between power plants in the same area. Therefore, if the roof-type solar structure suitable for the small warehouse we have presented in this paper is used, the facilities of electric power generation is eco-friendly. Further it is easier to obtain facility certification compared to the BIPV, and improved capacity of the power generation can be secured at low material cost. It is believed that the roof-type solar power generation facility we proposed can be usefully used for warehouse or factory-based smart housing. Sensor devices for monitoring, CCTV monitoring, or safety and environment management, operating in connection with the solar power generation facilities, are linked with the Internet of Things (IoT) solution, so they can be monitored and controlled remotely.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.34 no.6
• /
• pp.619-627
• /
• 2016

Cells of a PV (photovoltaic) module can suffer defects due to various causes resulting in a loss of power output. As a malfunctioning cell has a higher temperature than adjacent normal cells, it can be easily detected with a thermal infrared sensor. A conventional method of PV cell inspection is to use a hand-held infrared sensor for visual inspection. The main disadvantages of this method, when applied to a large-scale PV power plant, are that it is time-consuming and costly. This paper presents an algorithm for automatically detecting defective PV panels using images captured with a thermal imaging camera from an UAV (unmanned aerial vehicle). The proposed algorithm uses statistical analysis of thermal intensity (surface temperature) characteristics of each PV module to verify the mean intensity and standard deviation of each panel as parameters for fault diagnosis. One of the characteristics of thermal infrared imaging is that the larger the distance between sensor and target, the lower the measured temperature of the object. Consequently, a global detection rule using the mean intensity of all panels in the fault detection algorithm is not applicable. Therefore, a local detection rule was applied to automatically detect defective panels using the mean intensity and standard deviation range of each panel by array. The performance of the proposed algorithm was tested on three sample images; this verified a detection accuracy of defective panels of 97% or higher. In addition, as the proposed algorithm can adjust the range of threshold values for judging malfunction at the array level, the local detection rule is considered better suited for highly sensitive fault detection compared to a global detection rule. In this study, we used a panel area extraction method that we previously developed; fault detection accuracy would be improved if panel area extraction from images was more precise. Furthermore, the proposed algorithm contributes to the development of a maintenance and repair system for large-scale PV power plants, in combination with a geo-referencing algorithm for accurate determination of panel locations using sensor-based orientation parameters and photogrammetry from ground control points.

• Transactions of the Korean hydrogen and new energy society
• /
• v.22 no.2
• /
• pp.240-248
• /
• 2011

All-vanadium redox flow battery (VRFB) has been studied actively as one of the most promising electrochemical energy storage systems for a wide range of applications such as electric vehicles, photovoltaic arrays, and excess power generated by electric power plants at night time. Among consisting elements of the VRFB, the ion exchange membrane and the electrode play important roles. In this study, carbon PVC coposite sheets for the VRFB have been developed and electrochemical characteristics investigated. Current collector for VRFB, carbon PVC composite sheets (CPCS), were prepared with G-1028 as a conducting particle, PVC as a polymer, Dibutyl phthalate (DBP) as a plasticizer and fumed Silica (FS) as a dispersion agent. CPCS has been shown to have the characteristics as an excellent current collector for VRFB and electrochemical properties of specific resistivity 0.31 ${\Omega}cm$, which were composed of G-1028 80 wt%, PVC 10 wt%, DBP 5 wt% and FS 5 wt%.

• Transactions of the Korean hydrogen and new energy society
• /
• v.22 no.5
• /
• pp.721-727
• /
• 2011

All vanadium redox-flow battery (VRFB) has been studied actively as one of the most promising electrochemical energy storage systems for a wide rage of applications such as electric vehicles, photovoltaic arrays, and excess power generated by electric power plants at night time. In this study, carbon felt electrodes were treated by electrochemical oxidation with KOH, and the cyclic voltammetry were studied in order to investigate redox reactivity of vanadium ion species with carbon felt electrodes. Besides the effect of electrochemical oxidation on the surface chemistry of carbon felt electrodes were investigated using the X-ray photoelectron spectroscopy (XPS). After electrochemical oxidation, XPS analysis of PAN based GF20-3 carbon felt electrode revealed on increase in the overall surface oxygen content of the carbon felts after electrochemical oxidation. Redox reaction characteristics using cyclic voltammetry (CV) were ascertained that the electrochemical treated electrode were more reversible than the untreated electrode.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.1
• /
• pp.219-224
• /
• 2019

The number of solar power installation companies including domestic small scale (50kW or less) is increasing rapidly, but the efficient operation system and management are insufficient. Therefore, a new type of operating system is needed as a maintenance management aspect to maximize the generation amount in the current state rather than the additional function which causes the increase of the generation cost. In this paper, we utilize Big Data and sensor network to maximize the operating efficiency of solar power plant and analyze the expert system to develop power generation prediction technology, module unit fault detection technology, life prediction of inverter components and report technology, maintenance optimization And to develop a smart monitoring system that enables optimal operation of photovoltaic power plants such as development of algorithms and economic analysis.

• Journal of Environmental Impact Assessment
• /
• v.26 no.6
• /
• pp.479-494
• /
• 2017

After Fukushima incident, negative sentiment towards nuclear power has led to transition in policies that reduce the dependency on nuclear power in some countries. President Moon of Republic of Korea also announced a national plan of decommissioning retired nuclear power plants stage by stage. Therefore, nuclear power that once was considered the critical solution to energy security and climate change is now a limited option. This study aims to find an optimal energy mix in Korea's electricity system from 2016 through 2030 to combat climate change through energy transition with minimum cost. The study is divided into two different scenarios; energy transition and nuclear sustenance, to compare the total costs of the systems. Both scenarios show that electricity generated by wind technology increases from 2018 whereas that of photovoltaic(PV) increases from 2021. However, the total cost of the energy transition scenario was USD 4.7 billion more expensive than the nuclear sustenance scenario.

• Journal of Urban Science
• /
• v.8 no.1
• /
• pp.7-14
• /
• 2019

Recently, interest in solar energy, which is the center of new government energy policy, is increasing. However, the focus is on mass production of solar power plants, and policies and related technologies for maintenance and management of existing installed PV modules are insufficient. In this study, we use UAV (Unmanned Aerial Vehicle) to acquire RGB and infrared images, apply it to the structure-from-motion (SfM) based image analysis tool, model the three- And the position of the hot spot was monitored and coordinates were detected. As a result, it is possible to provide basic spatial information for maintenance of solar module by monitoring and position detection of hot-spot suspected solar cells by superimposing infrared image and RGB image based on unmanned aerial vehicle.