• Title/Summary/Keyword: Weather risk

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Prediction of Dynamic Line Rating Based on Thermal Risk Probability by Time Series Weather Models (시계열 기상모델을 이용한 열적 위험확률 기반 동적 송전용량의 예측)

  • Kim, Dong-Min;Bae, In-Su;Cho, Jong-Man;Chang, Kyung;Kim, Jin-O
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.55 no.7
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    • pp.273-280
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    • 2006
  • This paper suggests the method that forecasts Dynamic Line Rating (DLR). Thermal Overload Risk Probability (TORP) of the next time is forecasted based on the present weather conditions and DLR value by Monte Carlo Simulation (MCS). To model weather elements of transmission line for MCS process, this paper will propose the use of statistical weather models that time series is applied. Also, through the case study, it is confirmed that the forecasted TORP can be utilized as a criterion that decides DLR of next time. In short, proposed method may be used usefully to keep security and reliability of transmission line by forecasting transmission capacity of the next time.

A Determining Contingency Ranking Using the Weather Effects of the Power System (날씨효과를 고려한 전력계통의 상정사고 순위 결정)

  • Kim, Kyoung-Young;Park, Jong-Jin;Kim, Jin-O;Kim, Tae-Gyun;Choo, Jin-Bu
    • Proceedings of the KIEE Conference
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    • 2003.11a
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    • pp.134-136
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    • 2003
  • The deregulated electricity market is operated with respect to theory of economical efficiency, and therefore, the system operator requires data with fast contingency ranking for security of the bulk power system. This paper compares the weather dependant probabilistic risk index(PRI) with the system performance index for power flow in the IEEE-RBTS. also, the system performance index for power flow presents the power system stability. The probabilistic risk index can be classified into normal weather and adverse weather. This paper proposes calculation method using the probabilistic risk index in determining contingency ranking requiring for security under the deregulated electricity market.

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Measuring the Weather Risk in Manufacturing and Service Sectors in Korea (제조업과 서비스 부문 기후 리스크 측정)

  • Oh, Hyungna
    • Environmental and Resource Economics Review
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    • v.24 no.3
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    • pp.551-572
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    • 2015
  • Given the presence of global warming, the economic impact of climate changes on output sales has been discussed in the literature, but rarely with empirical evidences. In this present study, a simple log-model was employed to identify the economic impacts of weather changes in manufacturing and service sectors in Korea. For this empirical exercise, weather variables including the CDD (cooling degree days) and HDD (heating degree days) were computed using the Korea's meteorological records covering the period 1970-2012. According to estimation results, 26.7% (144 over 539) and 27.9% (64 over 229) of the manufacturing and service sectors, respectively, are found to be weather-sensitive.

Implementation of a Weather Hazard Warning System at a Catchment Scale (집수역 규모 기상위험 경보체계 구축)

  • Park, Ju Hyun;Kim, Seong Kee;Shin, Yong Soon;Ahn, Mun Il;Han, Yong Kyu
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.16 no.4
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    • pp.389-395
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    • 2014
  • This technical note describes about the base stages of technology implementation for establishing "Early Warning System for Weather Hazard Management in Climate-smart Agriculture" to national onsite service. First of all, a special weather report service at catchment was represented sequential risk of 810 units of catchment by spatial statistical methods to existing 150 counties units special weather report released in KMA. The second, chronic hazard alarm service based on daily data of 76 Synoptic stations was monitor about 810 Catchment of mid-long term lapse weather and represented as a relative risk index chronic hazard risk of this time in preparation for the climatological normal conditions in the same period. Finally, we establish the foundation for delivering individually calculated field specific in hazard risk about volunteer farmer of early warning service demonstration area in seomjin downstream watershed. These three types of information were built a near real-time map service on the VWORLD background map of Ministry of Land as superposed layers nationwide catchment and demonstration areas within the farm unit weather hazard.

Development of a Maryblyt-based Forecasting Model for Kiwifruit Bacterial Blossom Blight (Maryblyt 기반 참다래 꽃썩음병 예측모형 개발)

  • Kim, Kwang-Hyung;Koh, Young Jin
    • Research in Plant Disease
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    • v.21 no.2
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    • pp.67-73
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    • 2015
  • Bacterial blossom blight of kiwifruit (Actinidia deliciosa) caused by Pseudomonas syringae pv. syringae is known to be largely affected by weather conditions during the blooming period. While there have been many studies that investigated scientific relations between weather conditions and the epidemics of bacterial blossom blight of kiwifruit, no forecasting models have been developed thus far. In this study, we collected all the relevant information on the epidemiology of the blossom blight in relation to weather variables, and developed the Pss-KBB Risk Model that is based on the Maryblyt model for the fire blight of apple and pear. Subsequent model validation was conducted using 10 years of ground truth data from kiwifruit orchards in Haenam, Korea. As a result, it was shown that the Pss-KBB Risk Model resulted in better performance in estimating the disease severity compared with other two simple models using either temperature or precipitation information only. Overall, we concluded that by utilizing the Pss-KBB Risk Model and weather forecast information, potential infection risk of the bacterial blossom blight of kiwifruit can be accurately predicted, which will eventually lead kiwifruit growers to utilize the best practices related to spraying chemicals at the most effective time.

Determining Contingency Ranking Using the Probabilistic Method of the Power System (확률적 방법을 이용한 전력계통의 상정사고 순위 결정)

  • Kim, Kyoung-Young;Lee, Seung-Hyuk;Kim, Jin-O;Kim, Tae-Kyun
    • Proceedings of the KIEE Conference
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    • 2003.07a
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    • pp.113-115
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    • 2003
  • The electric power industry throughout the world is undergoing considerable changes from the vertically integrated utility structure to the deregulated market. However, the deregulated electricity market is operated with respect to theory of economical efficiency, and therefore, the system operator requires data with fast contingency ranking for security of the bulk power system. This paper presents fast calculation method for determining contingency ranking using the weather dependant probabilistic risk index(PRI). The probabilistic risk index can be classified into normal weather and adverse weather. This paper proposes calculation method using the probabilistic risk index in determining contingency ranking requiring for security under the deregulated electricity market.

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Investigating risk of overheating for school buildings under extreme hot weather conditions

  • Lykartsis, Athanasios;B-Jahromi, Ali;Mylona, Anastasia
    • Advances in Energy Research
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    • v.5 no.4
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    • pp.277-287
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    • 2017
  • This study examines the risk of overheating of a school building, under extreme hot weather conditions, in 14 locations in the United Kingdom using the overheating criteria defined in Building Bulletin 101 (BB101). The building was modelled as naturally ventilated, mechanically ventilated and in mixed mode and was simulated both for the current and the projected weather conditions of the 2050s. Under the current weather conditions, results of the simulations show that when naturally ventilated, the school building fulfils the BB101 criteria only in the areas of Edinburgh and Glasgow. In the simulations of the building as mechanically ventilated and in mixed mode, mechanical cooling was provided in order for the building to comply with the overheating criteria. A comparison of the required cooling loads between the two scenarios shows that application of mixed mode ventilation results in less cooling loads.

Estimation of Physical Climate Risk for Private Companies (민간기업을 위한 물리적 기후리스크 추정 연구)

  • Yong-Sang Choi;Changhyun Yoo;Minjeong Kong;Minjeong Cho;Haesoo Jung;Yoon-Kyoung Lee;Seon Ki Park;Myoung-Hwan Ahn;Jaehak Hwang;Sung Ju Kim
    • Atmosphere
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    • v.34 no.1
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    • pp.1-21
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    • 2024
  • Private companies are increasingly required to take more substantial actions on climate change. This study introduces the principle and cases of climate (physical) risk estimation for 11 private companies in Korea. Climate risk is defined as the product of three major determinants: hazard, exposure, and vulnerability. Hazard is the intensity or frequency of weather phenomena that can cause disasters. Vulnerability can be reflected in the function that explains the relationship between past weather records and loss records. The final climate risk is calculated by multiplying the function by the exposure, which is defined as the area or value of the target area exposed to the climate. Future climate risk is estimated by applying future exposure to estimated future hazard using climate model scenarios or statistical trends based on weather data. The estimated climate risks are developed into three types according to the demand of private companies: i) climate risk for financial portfolio management, ii) climate risk for port logistics management, iii) climate risk for supply chain management. We hope that this study will contribute to the establishment of the climate risk management system in the Korean industrial sector as a whole.

Analyzing the Customers' Intentions of Purchasing Weather Index Insurance (지수형 날씨보험 가입의향에 대한 분석)

  • Park, Ki-Jun;Hwang, Jin-Tae;Cho, Jae-Rin;Kim, Baek-Jo;Kim, In-Gyum
    • Journal of Environmental Science International
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    • v.23 no.2
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    • pp.171-180
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    • 2014
  • This study provides the empirical results of the customers' necessity and intentions of purchasing weather index insurance using survey of asking the customers' recognition about weather insurance. In this article, we discovered that not only the customers' past experience of loss but also the extent of damage and the effects that change in weather would have on their firm are positively related to an intention to purchase weather index insurance. In addition, the level of premiums was significantly higher for the highly-intended group of willing to purchase weather index insurance than the comparison group.

ADAPTIVE NUMERICAL SOLUTIONS FOR THE BLACK-SCHOLES EQUATION

  • Park, H.W.;S.K. Chung
    • Journal of applied mathematics & informatics
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    • v.12 no.1_2
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    • pp.335-349
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    • 2003
  • Almost all business are affected by the weather so that weather derivatives has been traded to hedge weather risk. Since the weather itself is not an asset with a market price, some analysts believe that the Black-Scholes equation could not be used appropriately to price weather derivative options. But some weather derivatives can be considered as an Asian option, we revisit the Black-scholes model. Numerical solution of the Black-Scholes equation has a significant error at the money option or around the money option, it is necessary to adopt adaptive mesh near to the strike value. Here we propose a numerical method with an adaptive grid refinement.