• Title/Summary/Keyword: Solar Energy Resource

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The Analysis of a Potential Solar Energy Resource Map (태양에너지 가용잠재량 자원지도 분석)

  • Jeong, Jong-Chul
    • Journal of Environmental Impact Assessment
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    • v.21 no.4
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    • pp.573-579
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    • 2012
  • Many countries have recently been expanding efforts for low-carbon global economy to solve the problem of global warming. Development and research for various types of new reusable energy is on the rise throughout the world. The most promising source of energy is the solar photovoltaic energy and the government take an initiative to establish both short-term and long-term policies to develop the solar energy potential resource map. The solar energy and industrialize area researched by GIS methods for optimum site for solar power transfer system. This study attempts to address the hot issue of the development and suitability of the solar photovoltaic energy site using GIS spatial analysis. We need to analyze and describe the solar technology, green energy policies and the energy market trend of the field.

Trend Review of Solar Energy Forecasting Technique (태양에너지 예보기술 동향분석)

  • Cheon, Jae ho;Lee, Jung-Tae;Kim, Hyun-Goo;Kang, Yong-Heack;Yun, Chang-Yeol;Kim, Chang Ki;Kim, Bo-Young;Kim, Jin-Young;Park, Yu Yeon;Kim, Tae Hyun;Jo, Ha Na
    • 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.

Analysis of Clear Sky Index Defined by Various Ways Using Solar Resource Map Based on Chollian Satellite Imagery (천리안 위성 영상 기반 태양자원지도를 활용한 다양한 정의에서의 청천지수 특성 분석)

  • Kim, Chang Ki;Kim, Hyun-Goo;Kang, Yong-Heack;Yun, Chang-Yeol
    • Journal of the Korean Solar Energy Society
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    • v.39 no.3
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    • pp.47-57
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    • 2019
  • Clear sky indices were estimated by various ways based on in-situ observation and satellite-derived solar irradiance. In principle, clear sky index defined by clear sky solar irradiance indicates the impacts of cloud on the incoming solar irradiance. However, clear sky index widely used in energy sciences is formulated by extraterrestrial irradiance, which implies the extinction of solar irradiance due to mainly aerosol, water vapor and clouds drops. This study examined the relative difference of clear sky indices and then major characteristics of clear sky irradiance when sky is clear are investigated. Clear sky is defined when clear sky index based on clear sky irradiance is higher than 0.9. In contrast, clear sky index defined by extraterrestrial irradiance is distributed between 0.4 and 0.8. When aerosol optical depth and air mass coefficient are relative larger, solar irradiance is lower due to enhanced extinction, which leads to the lower value of clear sky index defined by extraterrestrial irradiance.

Derivation of Typical Meteorological Year of Daejeon from Satellite-Based Solar Irradiance (위성영상 기반 일사량을 활용한 대전지역 표준기상년 데이터 생산)

  • Kim, Chang Ki;Kim, Shin-Young;Kim, Hyun-Goo;Kang, Yong-Heack;Yun, Chang-Yeol
    • 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.

A Change of Yearly Solar Radiation Energy Resources in Korea (국내 태양광자원의 경년변화)

  • Jo, Dok-Ki;Kang, Young-Heack
    • Journal of the Korean Solar Energy Society
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    • v.30 no.2
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    • pp.81-86
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    • 2010
  • Since the solar energy resource is the main input for sizing any solar photovoltaic system and solar thermal power system, it is essential to utilize the solar radiation data as a application and development of solar energy system increase. It will be necessary to understand and evaluate the insolation data. The Korea Institute of Energy Research(KIER) has begun collecting horizontal global insolation data since May, 1982 and direct normal insolation data since December 1992 at 16 different locations in Korea. Because of a poor reliability of existing data, KIER's new data will be extensively used by solar energy system users as well as by research institutes. From the results, the yearly averaged horizontal global insolation was turned out 3.60kWh/$m^2$/day and a significant difference of horizontal global insolation is observed between 1982~1990 and 1991~1999, 2000~2008 through 16 different cities in Korea.

Non-linear Regression Model Between Solar Irradiation and PV Power Generation by Using Gompertz Curve (Gompertz 곡선을 이용한 비선형 일사량-태양광 발전량 회귀 모델)

  • Kim, Boyoung;Alba, Vilanova Cortezon;Kim, Chang Ki;Kang, Yong-Heack;Yun, Chang-Yeol;Kim, Hyung-Goo
    • 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.

Business Model of Renewable Energy Resource Map (신재생에너지 자원지도의 비즈니스 모델 개발)

  • Park, Nyun-Bae;Park, Sang Yong;Choi, Dong Gu;Kim, Hyun-Goo;Kang, Yong-Heack
    • Journal of the Korean Solar Energy Society
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    • v.36 no.1
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    • pp.39-47
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    • 2016
  • Geographic information system (GIS) based renewable energy resource map including potential analysis can play a crucial role not only to develop the national plan for renewable energy deployment but also to make strategic investment decision in the private sector. Korea Institute of Energy Research (KIER) has been developing domestic maps about several resources such as solar, wind, hydro, biomass, and geothermal, as well as conducting research on methodologies for potential analysis. Furthermore, the institute is trying to transfer related technologies and know-how to foreign countries, recently. In this context, the main purpose of this study is to introduce the business model of renewable energy resource map. From the value chain analysis, we focus on the government-side market in foreign countries, such as the development of the national level renewable energy resource map and the support of the national renewable energy plan. For about 180 countries, we segment the customers according to the consideration of economic capacity, renewable energy resource capacity, existence of renewable resource map, current portion of renewable energy facility capacity, and renewable energy policies, and we conclude that the target customers are non-Organization for Economic Co-operation and Development (non-OECD) countries or some OECD countries, their per capita GDP are under the average among OECD countries, that do not have renewable resource map yet. We segment the target customers into four groups, and suggest different strategies for market positioning and financing strategy based on Strengths, Weaknesses, Opportunities, Threats (SWOT) analysis. This study can help to develop the business strategy about the development of renewable energy resource map in foreign countries.

Variability of Future Wind and Solar Resource Over the Korean Peninsula Based on Climate Change Scenario (기후변화 시나리오에 근거한 한반도 미래 풍력·태양-기상자원 변동성)

  • Byon, Jae-Young;Kim, Yumi;Choi, Byoung-Choel
    • New & Renewable Energy
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    • v.10 no.2
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    • pp.29-39
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    • 2014
  • This study examines the future variability of surface wind speed and solar radiation based on climate change scenario over the Korean Peninsula. Climate change scenarios used in this study are RCP 4.5 and 8.5 with a 12.5 km horizontal resolution. Climate change scenario RCP 4.5 and 8.5 reproduce the general features of wind speed over the Korean Peninsula, such as strong wind speed during spring and winter and weak wind speed during summer. When compared with the values of wind speed and solar radiation of the future, they are expected to decrease current wind and solar resource map. Comparing the resource maps using RCP 4.5 and 8.5 scenarios, wind speed and solar radiation decrease with increasing greenhouse gas concentration. Meteorological resource maps of future wind and solar radiation should be improved with high resolution for the industrial application.

Analysis of Shadows Effect in Seoul Area for the Estimation of Roof-type PV Power Calculation (지붕형 태양광 발전량 산정을 위한 서울지역 그림자 효과 분석)

  • Yun, ChangYeol;Jung, BoRin;Kim, ShinYoung;Kim, ChangKi;Kim, JinYoung;Kim, HyunGoo;Kang, YongHeack;Kim, YongIl
    • 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.

Solar Power Generation Forecast Model Using Seasonal ARIMA (SARIMA 모형을 이용한 태양광 발전량 예보 모형 구축)

  • Lee, Dong-Hyun;Jung, Ahyun;Kim, Jin-Young;Kim, Chang Ki;Kim, Hyun-Goo;Lee, Yung-Seop
    • Journal of the Korean Solar Energy Society
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    • v.39 no.3
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    • pp.59-66
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    • 2019
  • New and renewable energy forecasts are key technology to reduce the annual operating cost of new and renewable facilities, and accuracy of forecasts is paramount. In this study, we intend to build a model for the prediction of short-term solar power generation for 1 hour to 3 hours. To this end, this study applied two time series technique, ARIMA model without considering seasonality and SARIMA model with considering seasonality, comparing which technique has better predictive accuracy. Comparing predicted errors by MAE measures of solar power generation for 1 hour to 3 hours at four locations, the solar power forecast model using ARIMA was better in terms of predictive accuracy than the solar power forecast model using SARIMA. On the other hand, a comparison of predicted error by RMSE measures resulted in a solar power forecast model using SARIMA being better in terms of predictive accuracy than a solar power forecast model using ARIMA.