• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2011년도 제42회 하계학술대회
• /
• pp.590-591
• /
• 2011

This paper proposes a short-term load forecasting by using a temperature and load pattern. The forecasting model that represents the relations between load and temperature which get a numeral expected temperature based on the past temperature was constructed. Case studies were applied to load forecasting for 2009 data, and the results show its appropriate accuracy.

• 전기학회논문지
• /
• 제63권2호
• /
• pp.217-223
• /
• 2014

Recently, various researches and projects about electric vehicles are in progress vigorously and continuously and it is expected to penetrate rapidly with the next a few years. This deployment will cause the change of load composition rate affecting on power system planning and operations. Therefore, a new load model should be developed integrating with electric vehicle loads. In this paper, the load composition rate of residential sectors is analyzed considering the deployment of this mobility load such as electric vehicles and a new diffusion model is proposed based on the classification of the replacement patterns. Additionally, electric vehicle charging loads are basically modeled by some individual load experiments to develop new load models for smart place and some new conceptual power systems such as micro grids.

• Tribology and Lubricants
• /
• 제31권4호
• /
• pp.141-147
• /
• 2015

Gas foil thrust bearings (GFTBs) have attractive advantages over rolling element bearings and oil film thrust bearings, such as oil-free operation, high speed stability, and high-temperature operation. However, GFTBs have lower load carrying capacity than the other two types of bearings owing to the inherent low gas viscosity. The load carrying capacity of GFTBs depends mainly on the compliance of the foil structure and the formed hydrodynamic wedge, where the gas pressure field is generated between the top foil and the thrust runner. The load carrying capacity of the GFTBs is very important for the suitable design of oil-free turbomachinery with high performance. The aim of the present study is to identify the characteristics of the load carrying performance of GFTBs. A new test rig for the experimental measurements is designed to provide static loads up to 800 N using a pneumatic cylinder. The maximum operating speed of the driving motor is 30,000 rpm. A series of experimental tests—lift-off test, static load performance test, and maximum load capacity test—estimate the performance of a six-pad GFTB, in terms of the static load, driving torque, and temperature. The maximum load capacity is determined by increasing the static load until the driving torque rises suddenly with a sharp peak. The test results show that the torque and temperature increase linearly with the static load. The estimated maximum load capacity per unit area is approximately 80.5 kPa at a rotor speed of 25,000 rpm. The test results can be used as a design guideline for GFTBs for realizing oil-free turbomachinery.

• 한국지반공학회:학술대회논문집
• /
• 한국지반공학회 2005년도 춘계 학술발표회 논문집
• /
• pp.677-686
• /
• 2005

The allowable bearing capacity of a pile, the most important factor in stability estimation, is determined by applying safety factor to the ultimate load or yield load. There are several but contradictory methods available in current design codes to estimate the allowable bearing capacity and the safety factor. This paper analyzes load-settlement curves obtained from 19 static load tests measured from 11 sites. At all tests, the load is applied until apparent failure is observed. The validity of the ultimate and yield load estimation method and load caculated from the settlement criterion is investigated through comparison with the measured data. In addition, a new procedure to estimate allowable load and safety factor is proposed. Additional data from field static load tests, such as those incorporated in this study, are needed to more reliably apply the proposed method in design practice.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
• /
• pp.594-597
• /
• 2007

We present in this paper a novel mid and long term power load prediction method using temporal pattern mining from AMR (Automatic Meter Reading) data. Since the power load patterns have time-varying characteristic and very different patterns according to the hour, time, day and week and so on, it gives rise to the uninformative results if only traditional data mining is used. Also, research on data mining for analyzing electric load patterns focused on cluster analysis and classification methods. However despite the usefulness of rules that include temporal dimension and the fact that the AMR data has temporal attribute, the above methods were limited in static pattern extraction and did not consider temporal attributes. Therefore, we propose a new classification method for predicting power load patterns. The main tasks include clustering method and temporal classification method. Cluster analysis is used to create load pattern classes and the representative load profiles for each class. Next, the classification method uses representative load profiles to build a classifier able to assign different load patterns to the existing classes. The proposed classification method is the Calendar-based temporal mining and it discovers electric load patterns in multiple time granularities. Lastly, we show that the proposed method used AMR data and discovered more interest patterns.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2000년도 하계학술대회 논문집 D
• /
• pp.2825-2827
• /
• 2000

In electric power industry. load balance has been one of the most fundamental and important management goals. Therefore. the strategy to achieve high quality load management now includes load balance besides the stabilization of electricity supply and quality management of electricity. Amongst many techniques of load management. direct load management has been actively studied and utilized to increase power facility and peak load suppression. Higher peak load situation is appeared during summer than during winter in Korea. and approximately 20% of the peak load is due to the load for air-conditioning. To cope with this peak load problem during summer KEPCO is performing a research project to develop a system to remotely control air-conditioning load using wireless communication. Currently, applicable facilities are limited to small-scale air-conditioning facility that has less than 2KW power capacity. This paper described the 1st year of efforts made in the study.

• 대한전기학회논문지:전력기술부문A
• /
• 제48권1호
• /
• pp.8-14
• /
• 1999

This paper presents the methods of short-term load forecasting Kohonen neural networks and back-propagation neural networks. First, historical load data is divided into 5 patterns for the each seasonal data using Kohonen neural networks and using these results, load forecasting neural network is used for next day hourly load forecasting. Next day hourly load of weekdays and weekend except holidays are forecasted. For load forecasting in summer, max-temperature and min-temperature data as well as historical hourly load date are used as inputs of load forecasting neural networks for a better forecasting accuracy. To show the possibility of the proposed method, it was tested with hourly load data of Korea Electric Power Corporation(1994-95).

• 한국안전학회지
• /
• 제24권4호
• /
• pp.53-58
• /
• 2009

The importance of process for repair and reinforcement of the bridge is increasing because of the lack of the fatigue load and stress, a lowering of the bridge load carrying capacity owing to impact and oscillation, deterioration on cultivation periods of the bridge, etc. Typically the experimenter values the bridge load carrying capacity by the real rating factor and response modification factor in bridge load rating through static load test and dynamic load test. But the error occurred in reliability of response modification factor in bridge load rating according to experience of experimenter. so tests of connecting probability theory and valuation of the bridge recently. The study is to compute the real load carrying capacity of the bridge and the rating factor and response modification factor on grade of the bridge, and calculate the probability of over-loaded truck load from Weigh In Motion(WIM) Data in FORTRAN programming applying to Monte-Carlo Simulation. At the result of this study, it is acquired that the new grade is computed for the probability of over-loaded truck load and surface inspection. The A grade is over 1.95, B grade is $1.55{\sim}1.94$, C grade is $1.26{\sim}1.54$, D grade is $1.14{\sim}1.25$, E grade is under 1.13 of rating factor, respectively.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2004년도 하계학술대회 논문집 D
• /
• pp.2668-2670
• /
• 2004

This paper presents an advanced load control method in Direct Load Control(DLC) system. It is important to aggregate a various demand side resource which is surely controllable at the peak power time for a successful DLC system. Because the DLC system use simple On/Off control that may cause a harmful effect on a plant to reduce a peak power load, there are some restriction on deriving a voluntary participation of demand side resource. So it needs a new approach to direct load control method, and this paper describes an advanced load control method using control logic which is based on load properties. This method is easy to take account of a various characteristic of load, it can be use as a dynamic control logic which is good for adaptive control. The suggested control logic method is verified by modeling a control logic for a turbo refrigerator which affects on peak power in summer season.

• 대한전기학회논문지:전력기술부문A
• /
• 제53권2호
• /
• pp.87-96
• /
• 2004

This paper summarizes the research results of the load management for pole transformers done in 1997-1998 and 2000-2002. The purpose of the research is to enhance the accuracy of peak load estimation in pole transformers. We concentrated our effort on the acquisition of massive actual load data for modifying the load regression coefficients, which related to the peak load estimation of lamp-use customers, and adjusting the demand-factor coefficients, which used for the peak load prediction of motor-use customers. To enhance the load regression equations, the 264 load data acquisition devices are equipped to the sample pole transformers. For the modification of demand factor coefficients, the peak load currents are measured in each customer and pole transformer for 13 KEPCO (Korea Electric Power Corporation) distribution branch offices. Case studies for 50 sample pole transformers show that the proposed coefficients could reduce estimating error of the peak load for pole transformers, compared with the conventional one.