• KEPCO Journal on Electric Power and Energy
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• 제7권1호
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• pp.115-123
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• 2021

Through machine learning-based load prediction, it is possible to prevent excessive power generation or unnecessary economic investment by estimating the appropriate amount of facility investment in consideration of the load that will increase in the future or providing basic data for policy establishment to distribute the maximum load. However, in order to secure the reliability of the developed load prediction model in the field, the performance comparison verification between the distribution line load prediction models must be preceded, but a comparative performance verification system between the distribution line load prediction models has not yet been established. As a result, it is not possible to accurately determine the performance excellence of the load prediction model because it is not possible to easily determine the likelihood between the load prediction models. In this paper, we developed a reliability verification system for load prediction models including a method of comparing and verifying the performance reliability between machine learning-based load prediction models that were not previously considered, verification process, and verification result visualization methods. Through the developed load prediction model reliability verification system, the objectivity of the load prediction model performance verification can be improved, and the field application utilization of an excellent load prediction model can be increased.

• 한국지능시스템학회논문지
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• 제10권6호
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• pp.616-628
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• 2000

In this paper, we present the modeling of the ozone prediction system using Neuro-Fuzzy approaches. The mechanism of ozone concentration is highly complex, nonlinear, and nonstationary, the modeling of ozone prediction system has many problems and the results of prediction is not a good performance so far. The Dynamic Polynomial Neural Network(DPNN) which employs a typical algorithm of GMDH(Group Method of Data Handling) is a useful method for data analysis, identification of nonlinear complex system, and prediction of a dynamical system. The structure of the final model is compact and the computation speed to produce an output is faster than other modeling methods. In addition to DPNN, this paper also includes a Fuzzy Logic Method for modeling of ozone prediction system. The results of each modeling method and the performance of ozone prediction are presented. The proposed method shows that the prediction to the ozone concentration based upon Neuro-Fuzzy approaches gives us a good performance for ozone prediction in high and low ozone concentration with the ability of superior data approximation and self organization.

• 대기
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• 제29권1호
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• pp.21-39
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• 2019

The conventional observations of the Korea Meteorological Administration (KMA) and National Centers for Environmental Prediction (NCEP) are compared in the numerical weather forecast system at the Korea Institute of Atmospheric Prediction Systems (KIAPS). The weather forecasting system used in this study is consists of Korea Integrated Model (KIM) as a global numerical weather prediction model, three-dimensional variational method as a data assimilation system, and KIAPS Package for Observation Processing (KPOP) as an observation pre-processing system. As a result, the forecast performance of NCEP observation was better while the number of observation is similar to the KMA observation. In addition, the sensitivity of forecast performance was investigated for each SONDE, SURFACE and AIRCRAFT observations. The differences in AIRCRAFT observation were not sensitive to forecast, but the use of NCEP SONDE and SURFACE observations have shown better forecast performance. It is found that the NCEP observations have more wind observations of the SONDE in the upper atmosphere and more surface pressure observations of the SURFACE in the ocean. The results suggest that evenly distributed observations can lead to improved forecast performance.

• 한국지능시스템학회논문지
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• 제26권4호
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• pp.286-294
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• 2016

초기설계 단계에서 시스템의 성능을 고려한 형상의 최적화가 필요하다. 하지만, 일반적으로 공학시스템의 성능예측은 많은 계산 시간이 요구되는 작업이다. 시스템 형상의 최적화를 위해서는 다양한 설계대안에 대한 성능의 평가가 요구되므로 초기 설계과정에서 많은 어려움이 있다. 이러한 문제를 해결하기 위해, 많은 연구자들은 응답표면방법을 이용한 성능예측에 관한 다양한 연구를 시도하고 있다. 하지만, 이 방법은 비선형성이 강한 문제에서 예측오차가 비교적 크게 발생하는 단점이 있다. 따라서 본 연구의 최종목표는 초기설계과정에서 성능예측을 위한 적절한 근사모델을 제시하고, 해양시스템 성능예측문제(부유식 해상발전기 하부구조물 최적화 문제, 유조선의 선저외판 최적화 문제)에 적용하여 제시된 근사모델을 검증하는 것이다.

• 한국정밀공학회지
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• 제33권6호
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• pp.499-508
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• 2016

This paper describes a study of performance prediction of an electric propulsion system for multirotor UAVs. The electric propulsion system consists of motors, propellers, batteries and speed controllers, and significantly affects performance characteristics of the platform. The performance of the electric propulsion system for multirotor UAVs was predicted using an analytical model derived from the characteristics of each component, operation experiments and statistical analyses. Ground performance tests and endurance flights were performed to verify the reliability of the proposed performance prediction method. A quadrotor platform was designed to demonstrate the parcel delivery service used in the endurance flight. From the result of verification tests, it was confirmed that the proposed method has a good agreement.

• 산업경영시스템학회지
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• 제38권4호
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• pp.142-148
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• 2015

Due to advancements in technology and manufacturing capability, it is not uncommon that life tests yield no or few failures at low stress levels. In these situations it is difficult to analyse lifetime data and make meaningful inferences about product or system reliability. For some products or systems whose performance characteristics degrade over time, a failure is said to have occurred when a performance characteristic crosses a critical threshold. The measurements of the degradation characteristic contain much useful and credible information about product or system reliability. Degradation measurements of the performance characteristics of an unfailed unit at different times can directly relate reliability measures to physical characteristics. Reliability prediction based on physical performance measures can be an efficient and alternative method to estimate for some highly reliable parts or systems. If the degradation process and the distance between the last measurement and a specified threshold can be established, the remaining useful life is predicted in advance. In turn, this prediction leads to just in time maintenance decision to protect systems. In this paper, we describe techniques for mapping product or system which has degrading performance parameter to the associated classical reliability measures in the performance domain. This paper described a general modeling and analysis procedure for reliability prediction based on one dominant degradation performance characteristic considering pseudo degradation performance life trend model. This pseudo degradation trend model is based on probability modeling of a failure mechanism degradation trend and comparison of a projected distribution to pre-defined critical soft failure point in time or cycle.

• 한국군사과학기술학회지
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• 제12권3호
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• pp.396-405
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• 2009

The experimental research was conducted to setup a performance prediction logic for the regenerative cooling system on a small scale liquid rocket engine using kerosene and LOX. Total heat flux of the combustion gas side was determined for the flow rate of the coolant, combustion pressure using the calorimeter thrust chamber. Based on the experimental investigation, a performance prediction scheme for the regenerative cooling system is setup in our own way. A performance prediction logic for the regenerative cooling system has been developed by the correction scheme of the combustion gas side. The key parameters determining the temperature limitation of the coolant are the mass flow rate of the coolant and the length of the combustion chamber and the nozzle. And the parameters to control the limitation of the usable wall temperature are the number of channels and wall thickness.

• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.1356-1362
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• 2015

The location of PV systems in distribution system has been increased as one of countermeasure for global environmental issues. As the operation efficiency of PV systems is getting decreased year by year due to the aging phenomenon and maintenance problems, the optimal algorithm for state diagnosis in PV systems is required in order to improve operation performance in PV systems. The existing output prediction algorithms considering various parameters and conditions of PV modules could have complicated calculation process and then their results may have a possibility of significant prediction error. To solve these problems, this paper proposes an optimal prediction algorithm of PV system by using least square methods of linear regression analysis. And also, this paper presents a performance evaluation algorithm in PV modules based on the proposed optimal prediction algorithm of PV system. The simulation results show that the proposed algorithm is a practical tool of the state diagnosis for performance improvement in PV systems.

• 한국연소학회:학술대회논문집
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• 한국연소학회 2012년도 제45회 KOSCO SYMPOSIUM 초록집
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• pp.119-122
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• 2012

Circulating fluided bed(CFB) furnace which can use a variety of low-grade fuels because of high heat capacity and good mixing characteristic in its furnace have turned out to be effective system. There is no many research to predict performance considering total boiler system with water-steam side. Most of performance prediction model have focused on hydrodynamics or chemical mechanism in furnace. so, This study is aimed to develop performance prediction model which consider water-steam side.

• 한국생산제조학회지
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• 제8권5호
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• pp.108-114
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• 1999

The thermal environmental chamber has been using in maintaining weather condition keeping thermal capacity under heating and cooling load fluctuation and for the performance testing of cooling system or air-conditioner on artificial envi-ronment. In ordder to make the various environmental conditions in the thermal environmental chamber the proper cooling system is necessary to eliminate the heating load produced inside the chamber and to maintain the designed environmental condition. For this reason the optimal design of cooling system and the prediction of performance is also required. This paper describes the prediction of performance of cooling system in the thermal environmental chamber with the capacity of 37,000kcal/hr which is developed for the test of performance in heating mode of heat pump system, In the results this paper is trying to develop simulation program on the base of mathematical models and which can be applied effectively to the optimal design of cooling system and prediction of performance to the inside and outside change of envi-ronmetal load.