• Journal of the Korean Solar Energy Society
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• v.36 no.2
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• pp.19-29
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• 2016

Whilst there are growing interests in pursuing energy efficiency and zero-energy buildings in built environment, it is widely recognised that Building-Integrated Photovoltaic (BIPV) is one of the most promising and required technologies to achieve these goals in recent years. Although BIPV is a broadly utilized technique in variety of fields in built environments, it is required that generation of BIVP should be analysed and calculated by external specialists. The aim of this research is to focus on developing a new diagram for prediction of the pre-estimation model in early design stage to harness solar radiation data, PV types, slopes, azimuth and so forth. The results of this study show as follows: 1) We analysed 162 districts in a national level and the examined areas were categorised into five zones. The standard deviation of the results was 2.9 per cent; 2) The increased value of solar radiation on a vertical plane in five categorised zones was 42kWh/m3, and the result was similar to the average value of 43.8kWh/m3; and 3) The pre-estimation of diagram was developed based on the categorisation of zones and azimuth as well as the results of the developed diagram showed little difference compared to the previously utilised method. The suggested diagram in this paper will contribute to estimate BIPV without any external contribution to calculate the value. Even though the result of this study shows little difference, it is required to investigate a number of different variables such as BIPV types, modules, slope angle and so forth in order to develop an integrated pre-estimation diagram.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.28-36
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• 2023

Solar radiation that is measured at relatively small number of weather stations is one of key inputs to crop models for estimation of crop productivity. Solar radiation products derived from GK-2A and Himawari 8 satellite data have become available, which would allow for preparation of input data to crop models, especially for assessment of crop productivity under an agrivoltaic system where crop and power can be produced at the same time. The objective of this study was to compare the degree of agreement between the solar radiation products obtained from those satellite data. The sub hourly products for solar radiation were collected to prepare their daily summary for the period from May to October in 2020 during which both satellite products for solar radiation were available. Root mean square error (RMSE) and its normalized error (NRMSE) were determined for daily sum of solar radiation. The cumulative values of solar radiation for the study period were also compared to represent the impact of the errors for those products on crop growth simulations. It was found that the data product from the Himawari 8 satellite tended to have smaller values of RMSE and NRMSE than that from the GK-2A satellite. The Himawari 8 satellite product had smaller errors at a large number of weather stations when the cumulative solar radiation was compared with the measurements. This suggests that the use of Himawari 8 satellite products would cause less uncertainty than that of GK2-A products for estimation of crop yield. This merits further studies to apply the Himawari 8 satellites to estimation of solar power generation as well as crop yield under an agrivoltaic system.

• Korean Journal of Construction Engineering and Management
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• v.16 no.2
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• pp.65-76
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• 2015

The Clean Development Mechanism (CDM) is the multi-lateral 'cap and trade' system endorsed by the Kyoto Protocol. CDM allows developed (Annex I) countries to buy CER credits from New and Renewable (NE) projects of non-Annex countries, to meet their carbon reduction requirements. This in effect subsidizes and promotes NE projects in developing countries, ultimately reducing global greenhouse gases (GHG). To be registered as a CDM project, the project must prove 'additionality,' which depends on numerous factors including the adopted technology, baseline methodology, emission reductions, and the project's internal rate of return. This makes it difficult to determine ex ante a project's acceptance as a CDM approved project, and entails sunk costs and even project cancellation to its project stakeholders. Focusing on hydro power projects and employing UNFCCC public data, this research developed a prediction model using logistic regression and CART to determine the likelihood of approval as a CDM project. The AUC for the logistic regression and CART model was 0.7674 and 0.7231 respectively, which proves the model's prediction accuracy. More importantly, results indicate that the emission reduction amount, MW per hour, investment/Emission as crucial variables, whereas the baseline methodology and technology types were insignificant. This demonstrates that at least for hydro power projects, the specific technology is not as important as the amount of emission reductions and relatively small scale projects and investment to carbon reduction ratios.

• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.229-256
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• 2023

The increase in telecommuting and household electricity demand due to the pandemic has led to significant changes in electricity demand patterns. This has led to difficulties in identifying KEPCO's PPA (power purchase agreements) and residential solar power generation and has added to the challenges of electricity demand forecasting and grid operation for power exchanges. Unlike other energy resources, electricity is difficult to store, so it is essential to maintain a balance between energy production and consumption. A shortage or overproduction of electricity can cause significant instability in the energy system, so it is necessary to manage the supply and demand of electricity effectively. Especially in the Fourth Industrial Revolution, the importance of data has increased, and problems such as large-scale fires and power outages can have a severe impact. Therefore, in the field of electricity, it is crucial to accurately predict the amount of power generation, such as renewable energy, along with the exact demand for electricity, for proper power generation management, which helps to reduce unnecessary power production and efficiently utilize energy resources. In this study, we reviewed the renewable energy generation forecasting system, its objectives, and practical applications to construct optimal aggregated power resources using data from 169 power plants provided by the Ministry of Trade, Industry, and Energy, developed an aggregation algorithm considering the settlement of the forecasting system, and applied it to the analytical logic to synthesize and interpret the results. This study developed an optimal aggregation algorithm and derived an aggregation configuration (Result_Number 546) that reached 80.66% of the maximum settlement amount and identified plants that increase the settlement amount (B1783, B1729, N6002, S5044, B1782, N6006) and plants that decrease the settlement amount (S5034, S5023, S5031) when aggregating plants. This study is significant as the first study to develop an optimal aggregation algorithm using aggregated power resources as a research unit, and we expect that the results of this study can be used to improve the stability of the power system and efficiently utilize energy resources.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.123-125
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• 2018

태양광발전시스템은 낮은 효율의 PV 패널을 사용하여 최대의 전력을 생산하기 위해 PV 패널의 최대전력점에서 운전하는 MPPT(Maximum Power Point Tracking) 제어가 반드시 필요하다. 기존의 MPPT 알고리즘은 대부분 경사법에 기초하고 있으며 그 중 대표적인 방법이 P&O(Perturb and Observe) 알고리즘이다. P&O 알고리즘의 MPPT 성능을 좌우하는 두 가지 인수는 MPPT 제어주기와 변량전압의 크기이다. MPPT 제어기의 빠른 동특성과 극대화된 효율을 위한 최적의 MPPT 제어주기와 변량전압의 크기를 결정하기 위해서는 실제 날씨 환경에서 다양한 일사량 프로파일 패턴에 대한 MPPT 제어기의 성능분석이 필수적이다. 본 논문에서는 대한민국 중부지역의 전형적인 맑은 날씨와 흐린 날씨에서 실제 일사량을 측정하고, 취득한 일사량데이터를 기초로 저자가 개발한 다이오드 등가모델을 적용하여 시뮬레이션을 수행하였다. 이를 기반으로 MPPT 제어주기의 설정값에 따른 PV 패널의 전력생산량을 예측하여 MPPT 목표 효율을 극대화할 수 있는 최적의 MPPT 제어주기를 제시한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.871-874
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• 2010

Needs for Smart Grid development are increasing all over the world as a solution to its problem according to depletion of energy resources, climatic and environmental rapidly change and growing demand for electrical power. Especially decentralized power is attracting world's attention. In this mood a new era for a unit scale of decentralized power environment is on its way in building. However there is a problem to have to be solved in the uniformity of power quality because the amount of power generated from renewable energy resources such as wind power and solar light is very sensitive to climate fluctuation. And thus this paper tries to suggest an energy management method on basis of real time monitoring for meteorological data. In the current situation of lacking in USN-based killer application in Smart Grid field, this paper proposes the USN-based DER management system which collects the meteorological data and control power system througout utilizing wireless sensor network technique this business. This communication technique is regarded to be efficient in aspects of installation cost and tits maintenance cost. The proposed EMS model embodies the method for predicting the power generation by monitoring and analyzing the climatic data and controling the efficient power distribution between the renewable energy and the existing power. The ultimate goal of this paper is to provide the technological basis for achieving zero-energy house.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.4
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• pp.28-35
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• 2012

Recently, as the social interest increase has been focused on new renewable energy system to build-up sustainable urban planning system, the related studies have been actively conducting. As well as in other areas, the construction area, which accounts for over 40% of the total energy consumption, clearly showed this tendency. Whereas, various landscape facilities applying renewable energy equipments have been manufactured and installed, systematic study available for planning and designing is rarely found in Korea. This study is expected to contribute to the landscape planning and designing by quantifying the energy-efficient and economic advantages of the renewable energy system for landscape facilities. For this purpose, the analysis on the energy-efficiency and economic values under the scenario that the current fossil power supply for the streetlights in urban parks in Seoul, Daegu, and Incheon were replaced by photovoltaic power generation were performed through RETScreen$^{(R)}$ a clean energy simulation program based on the NASA Satellite Meteorological Data. As a result, the generated power and the economic values vary depending on the climatic features of the appointed cities. This study will be used to build up the effective decision-making in applying the clean renewable system to the plan and design of landscaping.