• Journal of the Korean Solar Energy Society
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• v.39 no.4
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• pp.41-54
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• 2019

The proportion of solar photovoltaic power generation has steadily increased in the power trade market. Solar energy forecast is highly important for the stable trade of volatile solar energy in the existing power trade market, and it is necessary to identify accurately any forecast error according to the forecast lead time. This paper analyzes the latest study trend in solar energy forecast overseas and presents a consistent comparative assessment by adopting a single statistical variable (nRMSE) for forecast errors according to lead time and forecast technology.

• The KIPS Transactions:PartA
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• v.10A no.6
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• pp.757-768
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• 2003

Recently, the renewable energy resources play an important role as an energy resources of future due to an environmental pollution and lack of resources and so on. The development and diffusion of information systems related to renewable energy resources have been driven actively abroad. However, at domestic an efficient history management for renewable energy resource data and web retrieve service are not provided. Therefore, in this paper, we propose a history data management system for the renewable energy resources, which stores and manages vast history information of renewable energy resource data systematically. This system collects renewable energy resource data in the outside observation system and stores them in the history database. The stored Information is retrieved through the history query process and can be provided in various forms - table, graph, chart and counter line, etc. - on the internet. Especially, the proposed system manages the history data in real-time so the latest information is always provided to the users through the web interface.

• Journal of the Korean Solar Energy Society
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• v.38 no.2
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• pp.45-53
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• 2018

For the preliminary step for estimating the performance of roof-type photovoltaic system in urban areas, we analyzed the solar radiation reduction ratio by shadow effect by buildings using DSM (Digital Surface Model) and GIS (Geographical Information System) tools. An average loss by the shadow is about 19% in Seoul. The result was related to the building density and distribution. Monthly results show that the winter season (December and January) was more affected by the shading than during the summer season (June and July). It is expected that useful empirical formulas can be made if more detailed correlation studies are performed.

• Journal of the Korean Solar Energy Society
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• v.40 no.3
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• pp.43-52
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• 2020

By blocking irradiance, shadows cast by high-rise buildings in urban areas can reduce the power generation efficiency of PV panels installed on low-rise buildings. As the conventionally installed PV panel is not suitable for the urban environment, which is unfavorable for power generating, a more radical solution is required. This study aims to help solve this problem by estimating the optimal PV panel angle. Using the proposed method, the optimal PV angle was calculated by considering shadows that could be cast by nearby buildings throughout the year, and the correlation between solar shading and elevation angle was discovered based on the calculated data.

• Journal of the Korean Solar Energy Society
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• v.38 no.6
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• pp.27-36
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• 2018

Typical Meteorological Year Dataset is necessary for the renewable energy feasibility study. Since National Renewable Energy Laboratory has been built Typical Meteorological Year Dataset in 1978, gridded datasets taken from numerical weather prediction or satellite imagery are employed to produce Typical Meteorological Year Dataset. In general, Typical Meteorological Year Dataset is generated by using long-term in-situ observations. However, solar insolation is not usually measured at synoptic observing stations and therefore it is limited to build the Typical Meteorological Year Dataset with only in-situ observation. This study attempts to build the Typical Meteorological Year Dataset with satellite derived solar insolation as an alternative and then we evaluate the Typical Meteorological Year Dataset made by using satellite derived solar irradiance at Daejeon ground station. The solar irradiance is underestimated when satellite imagery is employed.

• Journal of the Korean Solar Energy Society
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• v.39 no.3
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• pp.67-79
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• 2019

The reliable Typical Meteorological Year (TMY) data, sometimes called Test Reference Year (TRY) data, are necessary in the feasibility study of renewable energy installation as well as zero energy building. In Korea, there are available TMY data; TMY from Korea Institute of Energy Research (KIER), TRY from the Korean Solar Energy Society (KSES) and TRY from Passive House Institute Korea (PHIKO). This study aims at examining their characteristics by using Principle Component Analysis (PCA) at six ground observing stations. First step is to investigate the annual averages of meteorological elements from TMY data and their standard deviations. Then, PCA is done to find which principle components are derived from different TMY data. Temperature and solar irradiance are determined as the main principle component of TMY data produced by KIER and KSES at all stations whereas TRY data from PHIKO does not show similar result from those by KIER and KSES.

• 한국태양에너지학회:학술대회논문집
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• 2008.11a
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• pp.306-309
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• 2008

Renewable energy information becomes one of the greatest issues, but it is difficult for a general user to manage and utilize new renewable energy information. Therefore we develop the utilization system of the resource map which aimed to provide the information for space analysis and vertification of the validity for development of each part of solar, wind, smallhydro, biomass, geothermal. But this system is needed to gather more supporting data and make resonable index to make various decisions.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.13-19
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• 2014

To develop a wind farm in a mountainous terrain like Korea, it is generally more advantageous to install wind turbines along a mountain ridge where has relatively better wind resource because that is open in all directions and free from shielding by the surrounding topography. In this study, the SRTM (Shuttle Radar Topography Mission) v4.1 3 arc-second resolution digital elevation database and the geomorphometric characterization software LandSerf v2.3 are used to extract ridge lines for assessing a wind farm siting in mountainous terrain. The effectiveness of wind farm siting along a ridge line is confirmed that the most of wind turbines in the Gangwon, Taegisan, and Maebongsan wind farms in Korea's mountainous terrain are placed along the primary and secondary ridge lines where wind resource is relatively outstanding.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2177-2193
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• 2018

This paper studies resource allocation schemes for the relay-aided cooperative system consisting of multiple source-destination pairs and decode-forward (DF) relays. Specially, relaying selection, multisubcarrier pairing and assignment, and power allocation are investigated jointly. We consider a combinatorial optimization problem on quality of experience (QoE) and energy consumption based on relay-aided cooperative system. For providing better QoE and lower energy consumption we formulate a multi-objective optimization problem to maximize the total mean opinion score (MOS) value and minimize the total power consumption. To this end, we employ the nondominated sorting genetic algorithm version II (NSGA-II) and obtain sets of Pareto optimal solutions. Specially, two formulas are devised for the optimal solutions of the multi-objective optimization problems with and without a service priority constraint. Moreover, simulation results show that the proposed schemes are superior to the existing ones.

• Journal of the Korean Solar Energy Society
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• v.39 no.6
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• pp.113-125
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• 2019

With the opening of the small power brokerage business market in December 2018, the small power trading market has started in Korea. Operators must submit the day-ahead estimates of power output and receive incentives based on its accuracy. Therefore, the accuracy of power generation forecasts is directly affects profits of the operators. The forecasting process for power generation can be divided into two procedure. The first is to forecast solar irradiation and the second is to transform forecasted solar irradiation into power generation. There are two methods for transformation. One is to simulate with physical model, and another is to use regression model. In this study, we found the best-fit regression model by analyzing hourly data of PV output and solar irradiation data during three years for 242 PV plants in Korea. The best model was not a linear model, but a sigmoidal model and specifically a Gompertz model. The combined linear regression and Gompertz curve was proposed because a the curve has non-zero y-intercept. As the result, R² and RMSE between observed data and the curve was significantly reduced.