• KIEAE Journal
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• v.14 no.2
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• pp.3-10
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• 2014

Impact by estimation error of hourly horizontal global solar radiation in a weather file on building energy performance was investigated in this study. There are a number of weather parameters in a given weather file, such as dry-bulb, wet-bulb, dew-point temperatures; wind speed and direction; station pressure; and solar radiation. Most of them except for solar radiation can be easily obtained from weather stations located on the sites worldwide. However, most weather stations, also including the ones in South Korea, do not measure solar radiation because the measuring equipment for solar radiation is expensive and difficult to maintain. For this reason, many researchers have studied solar radiation estimation models and suggested to apply them to predict solar radiation for different weather stations in South Korea, where the solar radiation is not measured. However, only a few studies have been conducted to identify the impact caused by estimation errors of various solar radiation models on building energy performance analysis. Therefore, four different weather files using different horizontal global solar radiation data, one using measured global solar radiation, and the other three using estimated global solar radiation models, which are Cloud-cover Radiation Model (CRM), Zhang and Huang Model (ZHM), and Meteorological Radiation Model (MRM) were packed into TRY formatted weather files in this study. These were then used for office building energy simulations to compare their energy consumptions, and the results showed that there were differences in the energy consumptions due to these four different solar radiation data. Additionally, it was found that using hourly solar radiation from the estimation models, which had a similar hourly tendency with the hourly measured solar radiation, was the most important key for precise building energy simulation analysis rather than using the solar models that had the best of the monthly or yearly statistical indices.

• ETRI Journal
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• v.30 no.1
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• pp.47-58
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• 2008

In sensor networks, analyzing power consumption before actual deployment is crucial for maximizing service lifetime. This paper proposes an instruction-level power estimator (IPEN) for sensor networks. IPEN is an accurate and fine grain power estimation tool, using an instruction-level simulator. It is independent of the operating system, so many different kinds of sensor node software can be simulated for estimation. We have developed the power model of a Micaz-compatible mote. The power consumption of the ATmega128L microcontroller is modeled with the base energy cost and the instruction overheads. The CC2420 communication component and other peripherals are modeled according to their operation states. The energy consumption estimation module profiles peripheral accesses and function calls while an application is running. IPEN has shown excellent power estimation accuracy, with less than 5% estimation error compared to real sensor network implementation. With IPEN's high precision instruction-level energy prediction, users can accurately estimate a sensor network's energy consumption and achieve fine-grained optimization of their software.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1342-1349
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• 2023

The planning accuracy of charged particle therapy (CPT) is subject to the accuracy of stopping power (SP) estimation. In this study, we propose a method of deriving a pseudo-triple-energy CT (pTECT) that can be achievable in the existing dual-energy CT (DECT) systems for better SP estimation. In order to remove the direct effect of errors in CT values, relative CT values according to three scanning voltage settings were used. CT values of each tissue substitute phantom were measured to show the non-linearity of the values thereby suggesting the absolute difference and ratio of CT values as parameters for SP estimation. Electron density, effective atomic number (EAN), mean excitation energy and SP were calculated based on these parameters. Two of conventional methods were implemented and compared to the proposed pTECT method in terms of residuals, absolute error and root-mean-square-error (RMSE). The proposed method outperformed the comparison methods in every evaluation metrics. Especially, the estimation error for EAN and mean excitation using pTECT were converging to zero. In this proof-of-concept study, we showed the feasibility of using three CT values for accurate SP estimation. Our suggested pTECT method indicates potential clinical utility of spectral CT imaging for CPT planning.

• Korean Management Science Review
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• v.30 no.2
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• pp.1-10
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• 2013

Case studies are made to investigate the relationship between the accuracy of energy production estimation and project feasibility indicators such as rate of return on equity (ROE) and debt service coverage ratio (DSCR) for three wind farm projects. It is found out that 1% improvement in the accuracy of energy production estimation may enhance the ROE by more than 0.5% in the case of P95, thanks to improved financing terms. AHP survey shows that MCP correlation of measured in situ wind data with long term wind speed distribution and hands-on experiences of flow analysis are more important than other factors for more precise annual energy production estimation.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.4 no.2
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• pp.171-178
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• 2006

Decommissioning cost estimation is a very important technique in designing and planning of nuclear facilities' decommissioning. Decommissioning cost estimation should be made according to the phases of decommissioning activities and installed components of nuclear facilities. In this paper, the basic framework necessary for decommissioning cost estimation is completed so that it could be used as a technique for decommissioning costs estimation by specifying cost items and group components and unit cost factors on which work time is calculated. Also, factors to be considered for decommissioning cost estimation of major activities and tasks are reviewed. Afterwards, these techniques will be utilized as a basic technology to establish methodology of decommissioning cost estimation and evaluation.

• Journal of IKEEE
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• v.26 no.1
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• pp.10-18
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• 2022

Accurate SOC estimation is an important indicator of battery operation strategies, and many studies have been conducted. The simulation method which was mainly used in previous studies, is difficult to conduct real-time SOC estimation like real BMS environment. Therefore, this paper aims to implement a real-time battery SOC estimation embedded system and analyze problems that can arise during the verification process. In environment consisting of two Raspberry Pi boards, SOC estimation with the EKF uses data measured by the Simscape battery model. Considering that the operating characteristics of the battery vary depend on the temperature, the results were analyzed at various ambient temperatures. It was confirmed that accurate SOC estimation was performed even when offset fault and packet loss occurred due to communication or sensing problems. This paper proposes a guide for embedded system strategies that enable real-time SOC estimation with errors within 5%.

• 한국태양에너지학회:학술대회논문집
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• 2012.03a
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• pp.506-510
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• 2012

This study suggested an improved algorithm of urban energy consumption estimation on the urban planning stage which concerns calculation accuracy. The results are as follows. (1) Urban energy consumption was estimated and managed per unit space using E-GIS DB which contains facility information per mesh. (2) Urban energy consumption was reflected by the urban facility classified and standardized by the characteristics of energy use. (3) Calculation accuracy of energy consumption was approached by separately suggested as summer algorithm reflecting urban heat island on summer energy use and winter algorithm reflecting heating system normally used in Korea.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.50 no.8
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• pp.374-383
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• 2001

This paper presents the torque estimation scheme by Energy Conversion Method (ECM) that can be applied to the torque control of switched reluctance motor. There are two types of torque estimation method by ECM. One is the method using mechanical output energy and another is that using co-energy. When the torque is estimated by ECM, the estimated flux linkage can be obtained by voltage equation and Luenberger observer. By comparing the torque estimated by ECM with that be FEM, we verify the feasibility of the proposed torque estimation by ECM.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.50-59
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• 1996

In this paper, a new hierarchical motion estiamtion scheme using the wavelet transformed multi-resolution image layers is proposed. Compared with the full search motion estimation method, the existing hierarchical methods remarkably reduce the amount of the computation but their efficiencies are depreciated by the local minima problem. In order to solve the local minima problem, the multi-resolution image layers are composed using the wavelet transform and the number of layers participated in the motion estimation for a block is determined by considering of its low band energy and higher band energy on the first wavelet transformed layer. The ratio between higher band energy and low band energy of each block is evaluated and in the case of the blocks which include relatively large higher band energy, the motion estimation is carried out in the high resolution layer. Otherwise, all layers are used. The final motion vectors are obtained in the first wavelet transformed layer. So less bits for motion vectors are transmitted, and the decomposition of received image using inverse wavelet transform decreases the blocking effect.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.177.1-177.1
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• 2010

Large offshore wind farms have actively been developed in order to meet the needs for wind energy since the land-based wind farms have almost been fully developed especially in Europe. The key problem for the construction of offshore wind farms may be on the high cost of energy compared to land-based ones. NREL (National Renewable Energy Laboratory) has developed a spreadsheet-based tool to estimate the cost of wind-generated electricity from both land-based and offshore wind turbines. Component formulas for various kinds and scales of wind turbines were made using available field data. Annual energy production has been estimated based on the Weibull probability distributions of wind. In this paper, this NREL estimation model is introduced and applied to the offshore wind turbines now under designing or in production in Korea, and the result is discussed.