• 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.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.6
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• pp.535-540
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• 2022

DC-link capacitors are reliability-critical components in a photovoltaic (PV) inverter. Typically, the lifetime of a DC-link capacitor is evaluated by considering the voltage and hot-spot temperature of the capacitor under the specific operating condition of the PV inverter. However, the output of the PV inverter is determined by solar irradiation and ambient temperature, which vary with the seasons; accordingly, the hot-spot temperature of the capacitor also changes. Therefore, the mission profile of the PV system should be considered to effectively evaluate the reliability of the DC-link capacitor. In this study, the reliability of the DC-link capacitor of a three-level NPC inverter is comparatively analyzed with and without considering the mission profiles of the PV system, where two mission profiles recorded in Arizona and Iza are considered. The accumulated damage of the DC-link capacitor is calculated based on the lifetime model by analyzing its thermal loading. Afterward, a reliability evaluation of the DC-link capacitor is performed at the component level and then at the system level by considering all capacitors by means of Monte Carlo analysis. Results reveal the importance of performing a mission-profile-based reliability evaluation during the design of high-reliability PV inverters to achieve the target reliability performance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.11
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• pp.57-68
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• 2013

The market for distributed power generation based on renewable energy is increasing, particularly for standalone mini-grid applications in developing countries with limited energy resources. Stand-alone power systems (SAPS) are of special interest combined with renewable energy design in areas not connected to the electric grid. Traditionally, such systems have been powered by diesel engine generator sets (DEGS), but also hybrid systems with photovoltaic and/or wind energy conversion systems (WECS) are becoming quite common nowadays. Hybrid energy systems can now be used to generate energy consumed in remote areas and stand-alone microgrids. This paper describes the design, simulation and feasibility study of a hybrid energy system for a stand-alone power system. A simulated model is developed to investigate the design and performance of stand-alone hydrogen renewable energy systems. The analysis presented here is based on transient system simulation program (TRNSYS) with realistic ventilation load of a large store. Design of a hybrid energy system is site specific and depends on the resources available and the load demand.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.5
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• pp.93-99
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• 2017

A model was developed using Artificial Neural Networks (ANNs) based on Principal Component Analysis (PCA), to accurately predict the air humidity inside an experimental greenhouse located in Daegu (latitude $35.53^{\circ}N$, longitude $128.36^{\circ}E$, and altitude 48 m), South Korea. The weather parameters, air temperature, relative humidity, solar radiation, and carbon dioxide inside and outside the greenhouse were monitored and measured by mounted sensors. Through the PCA of the data samples, three main components were used as the input data, and the measured inside humidity was used as the output data for the ALYUDA forecaster software of the ANN model. The Nash-Sutcliff Model Efficiency Coefficient (NSE) was used to analyze the difference between the experimental and the simulated results, in order to determine the predictive power of the ANN software. The results obtained revealed the variables that affect the inside air humidity through a sensitivity analysis graph. The measured humidity agreed well with the predicted humidity, which signifies that the model has a very high accuracy and can be used for predictions based on the computed $R^2$ and NSE values for the training and validation samples.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.39-44
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• 2023

Renewable energy such as solar and wind power is a resource that is sensitive to weather conditions and environmental changes. Since the amount of power generated by a facility can vary depending on the installation location and structure, it is important to accurately predict the amount of power generation. Using meteorological data, a data preprocessing process based on principal component analysis was conducted to monitor the relationship between features that affect energy production prediction. In addition, in this study, the prediction was tested by reconstructing the dataset according to the sensitivity and applying it to the machine learning model. Using the proposed model, the performance of energy production prediction using random forest regression was confirmed by predicting energy production according to the meteorological environment for new and renewable energy, and comparing it with the actual production value at that time.

• Environmental and Resource Economics Review
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• v.30 no.3
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• pp.435-469
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• 2021

The main purpose of this study is to identify the determinants of electricity import and export in 26 European Union countries using the Spatial durbin model(SDM). In particular, we would like to mainly explain it based on the amount of power generated by each energy source. Not just the usual way of constructing a weighting matrix based on contiguity, we adopt a weighting method based on the proportion of trade among countries with connected electricity systems. Moreover, the electricity systems of European countries are directly and indirectly connected, which is reflected in the weighting matrix. According to the results, nuclear power has a positive effect on exports and a negative effect on imports, and an increase in wind and solar power has a positive effect on both exports and imports by increasing power system instability. While Korea is unable to trade electricity due to geopolitical conditions, the results of this study are expected to provide implications for energy policies.

• Journal of Energy Engineering
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• v.26 no.2
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• pp.99-120
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• 2017

In SS branch of Korea District Heating Corporation, Combined Heat & Power power plant with 99MW capacity and 98Gcal / h capacity is operated as a district electricity business. In this region, it is difficult to operate the generator due to the problem of surplus heat treatment between June and September due to the economic recession and the decrease in demand, so it is urgent to develop an economical energy new business model. In this study, we will develop an optimized operation model by introducing a renewable energy hybrid system based on actual operation data of this site. In particular, among renewable energy sources, fuel cell (Fuel Cell) power generation which can generate heat and electricity at the same time with limited location constraints, photovoltaic power generation which is representative renewable energy, ESS (Energy Storage System). HOMER (Hybrid Optimization of Multiple Energy Resources) program was used to select the optimal model. As a result of the economic analysis, 99MW CHP combined cycle power generation is the most economical in terms of net present cost (NPC), but 99MW CHP in terms of carbon emission trading and renewable energy certificate And 5MW fuel cells, and 521kW of solar power to supply electricity and heat than the supply of electricity and heat by 99MW CHP cogeneration power, it was shown that it is economically up to 247.5 billion won. we confirmed the results of the improvement of the zone electricity business condition by introducing the fuel cell and the renewable energy hybrid system as the optimization process model.

• 한국태양에너지학회:학술대회논문집
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• 2008.04a
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• pp.348-358
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• 2008

Unlike structures in the air, the vibration analysis of a submerged or floating structure such as offshore structures is possibly only when the fluid-structures is understood, as the whole or part of the structure is in contact with water. Through the comparision between the experimental result and the finite element analysis result for a simple cylindrical model, it was verified that an added mass effects on the cylindrical structure. Using the commercial FEA program ANSYS(v.11.0), underwater added mass was superposed on the mass matrix of the structure. A frequency response analysis of forced vibration in the frequency considered the dynamic load was also performed. It was proposed to find the several important modes of resonance peak for these fixed cylindrical type structures. Furthermore, it is expected that the analysis method and the data in this study can be applied to a dynamic structural design and dynamic performance evaluation for the ground and marine purpose of power generator by wind.

• The Journal of Society for e-Business Studies
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• v.24 no.4
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• pp.119-133
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• 2019

Recently, the importance prediction of photovoltaic power (PV) is considered as an essential function for scheduling adjustments, deciding on storage size, and overall planning for stable operation of PV facility systems. In particular, since most of PV power is generated in peak time, PV power prediction in a peak time is required for the PV system operators that enable to maximize revenue and sustainable electricity quantity. Moreover, Prediction of the PV power output in peak time without meteorological information such as solar radiation, cloudiness, the temperature is considered a challenging problem because it has limitations that the PV power was predicted by using predicted uncertain meteorological information in a wide range of areas in previous studies. Therefore, this paper proposes the LSTM (Long-Short Term Memory) based the PV power prediction model only using the meteorological, seasonal, and the before the obtained PV power before peak time. In this paper, the experiment results based on the proposed model using the real-world data shows the superior performance, which showed a positive impact on improving the PV power in a peak time forecast performance targeted in this study.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.6
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• pp.587-599
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• 2018

In building-integrated photovoltaic (BIPV) systems, power generation functions are integrated into building functions by installing solar modules in combination with building materials. While this integration appears to be attractive, a design method is needed to achieve maximum power generation. Previously, the influence of the design elements on power generation was analyzed by computer simulations and demonstration tools. On the other hand, problems remain due to the inaccuracy of power generation analysis and relationship analysis, and limited demonstration. To solve this problem, this paper proposed the use of an extended demonstration mock-up. The mock-up was designed and constructed by implementing the design elements of the module types, installation angles, and direction. The actual operation data for one year were analyzed to evaluate the effects of the design elements on power generation. These results can be used to determine the feasibility of future BIPV systems and the optimal selection of system design elements.