• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1765-1773
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• 2012

The accuracy of load forecast is very important from the viewpoint of economical power system operation. In general, the weekdays' load demand pattern has the continuous time series characteristics. Therefore, the conventional methods expose stable performance for weekdays. In case of special days or weekends, the load demand pattern has the discontinuous time series characteristics, so forecasting error is relatively high. Especially, weekdays near the thanksgiving day and lunar new year's day have the mixed load profile characteristics of both weekdays and weekends. Therefore, it is difficult to forecast these days by using the existing algorithms. In this study, a new load forecasting method is proposed in order to enhance the accuracy of the forecast result considering the characteristics of weekdays and weekends. The proposed method was tested with these days during last decades, which shows that the suggested method considerably improves the accuracy of the load forecast results.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.4
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• pp.505-510
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• 2009

In this paper, building energy analysis and energy cost of power stand up and demand control over the power proposed to reduce power demand. Through analysis of the load power demand special day were able to apply the pattern. In addition, the existing rate of change of load forecasting to reduce the large errors were not previously available data. And daily schedules and special day for considering the exponential smoothing methods were used. Previous year's special day and the previous day due to the uncertainty of the load and the model components were considered. The maximum demand power control simulation using the fuzzy control of power does not exceed the contract. Through simulation, the benefits of the proposed energy-saving techniques were demonstrated.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.730-738
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• 1994

The major advantage of the short-term load forecasting technique using general exponential smoothing is high accuracy and operational simplicity, but it makes large forecasting error when the load changes repidly. The paper has presented new technique to improve those shortcomings, and according to forecasted the technique proved to be valid for two years. The structure of load model is time function which consists of daily-and temperature-deviation component. The average of standard percentage erro in daily forecasting for two years was 2.02%, and this forecasting technique has improved standard erro by 0.46%. As relative coefficient for daily and seasonal forecasting is 0.95 or more, this technique proved to be valid.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.447-449
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• 1996

This paper describes an algorithm for short term load forecasting using the Kohonen neural network. Single layer Kohonen neural network presents a lot of advantageous features for practical application. It takes less training time compared to other networks such as BP network, and moreover, its self organized feature can amend the distorted data. The originality of proposed approach is to use a Kohonen map toclassify data representing load patterns and to use directly the information stored in the weight vectors of the Kohonen map to pridict the load. Proposed method was tested with KEPCO hourly record(1993-1995) show better forecasting results compared with conventional exponential smoothing method.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.29-32
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• 1993

A technique computing short-term load foadcasting is essential for monitoring and controlling power system operation. This paper shows the use of general exponential smoothing to develop an adaptive forecasting system based on observed value of hourly demand. Forecasts of hourly load with lead times of one to twenty-four hours are computed at hourly intervals throughout the week. Standard error for lead times of one to twenty-four hour range from three to four percent average load. Studies are planned to investigate the use of weather influence to increase forecast accuracy.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.5
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• pp.372-377
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• 2007

This paper proposes a novel fault diagnosis method of a electrolytic capacitor used for DC-link voltage smoothing in adjustable speed drives. The equivalent series resistance (ESR) of the electrolytic capacitor is directly estimated from DC-link voltage and load currents and the status of the electrolytic capacitor is determined from the estimated ESR. To compensate the variation of the ESR owing to temperature variation, diodes are located on the same PCB near the capacitor and the temperature of the capacitor is sensed indirectly from the voltage drop of diodes. Simulation and experimental studies show the effectiveness of the proposed method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.3
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• pp.71-82
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• 2009

As a solution to spectrum under-utilization problem, Cognitive radio (CR) introduces a dynamic spectrum access technology. In the area, one of the most important problems is how secondary users (SUs) should choose between the available channels, which means how to achieve load balancing between channels. We consider spectrum load balancing problem for CR system in frequency domain and especially in time domain. Our objective is to balance the load among the channels and balance the occupied time length of slots for a fixed channel dynamically in order to obtain a user-optimal solution. In frequency domain, we refer to Dynamic Noncooperative Scheme with Communication (DNCOOPC) used in distributed system and a distributed Dynamic Spectrum Load Balancing algorithm (DSLB) is formed based on DNCOOPC. In time domain, Spectrum Load Balancing method with QoS support is proposed based on Dynamic Feed Back theory and Hash Table (SLBDH). The performance of DSLB and SLBDH are evaluated. In frequency domain, DSLB is more efficient compared with existing Compare_And_Balance (CAB) algorithm and gets more throughput compared with Spectrum Load Balancing (SLB) algorithm. Also, DSLB is a fair scheme for all devices. In time domain, SLBDH is an efficient and precise solution compared with Spectrum Load Smoothing (SLS) method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.6
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• pp.17-22
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• 2013

Fuzzy linear regression method has been used for short-term load forecasting of the special day in the previous researches. However, considerable load forecasting errors would be occurring if a special day is located on Saturday or Monday. In this paper, a new load forecasting method for the consecutive holidays is proposed with the consideration of the power demand variation rate. In the proposed method, a exponential smoothing model reflecting temperature is used to short-term load forecasting for Sunday during the consecutive holidays and then the loads of the special day during the consecutive holidays is calculated using the hourly power demand variation rate between the previous similar consecutive holidays. The proposed method is tested with 10 cases of the consecutive holidays from 2009 to 2012. Test results show that the average accuracy of the proposed method is improved about 2.96% by comparison with the fuzzy linear regression method.

• Journal of Information Processing Systems
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• v.9 no.3
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• pp.365-378
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• 2013

In Wireless Mesh Networks (WMNs), we usually deploy multiple Internet Gateways (IGWs) to improve the capacity of WMNs. As most of the traffic is oriented towards the Internet and may not be distributed evenly among different IGWs, some IGWs may suffer from bottleneck problem. To solve the IGW bottleneck problem, we propose an efficient scheme to balance the load among different IGWs within a WMN. Our proposed load-balancing scheme consists of two parts: a traffic load calculation module and a traffic load migration algorithm. The IGW can judge whether the congestion has occurred or will occur by using a linear smoothing forecasting method. When the IGW detects that the congestion has occurred or will occur, it will firstly select another available IGW that has the lightest traffic load as the secondary IGW and then inform some mesh routers (MPs) which have been selected by using the Knapsack Algorithm to change to the secondary IGW. The MPs can return to their primary IGW by using a regression algorithm. Our Qualnet 5.0 experiment results show that our proposed scheme gives up to 18% end-to-end delay improvement compared with the existing schemes.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1643-1645
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• 2005

A newly-built inverter has to undergo a series of stress tests in the final stage of production line. This can be achieved by connecting it to a dynamometer consisting of a three-phase machine joined by a rigid shaft to a DC load machine. The latter is controlled to create some specific load characteristic needed for the test. In this paper a test method is proposed, in which no mechanical equipment is needed. The suggested test stand consists only of a inverter to be tested and a simulator converter. Both devices are connected back- to-back on the AC-side via smoothing reactors. The simulator operates in real-time as an equivalent load circuit, so that the device under test will only notice the behaviour of a three-phase machine under consideration of the load. In odor to wove rightness of the suggested test method, the simulation and actural experiment rallied out emulation for a 2.2kW induction motor.