• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.6
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• pp.334-339
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• 2004

In this study, a new UC (Unit Commitment) algorithm is proposed to consider the uncertainty of a daily load profile. The proposed algorithm calculates the UC results with the lower load level than the one generated by the conventional load forecast and the more hourly reserve allocation. In case of the worse load forecast, the deviation of the conventional UC solution can be overcome with the proposed method. The proposed method is tested with sample systems, which shows that the new UC algorithm yields completely feasible solution even though the worse load forecast is applied. Also, the effects of the uncertain hourly load demand are statistically analyzed especially by the consideration of the average over generation and the average under generation. Finally, it is shown that independent power producers participating in electricity spot-markets can establish bidding strategies by means of the statistical analysis. Therefore, it is expected that the proposed method can be used as the basic guideline for establishing bidding strategies under the deregulation power pool.

• IE interfaces
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• v.16 no.1
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• pp.16-26
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• 2003

In Korea, cooling power load, which occupies about 20% of peak load in 2000 and fluctuates depending on the popular usage of air conditioning systems, has been recently the focus of the load management. The first work of KEPCO (Korea Electric Power Corporation) to regulate cooling load as low as possible was to estimate its approximate scale and to develop the indirect methods to estimate it from the available time series data for the average hourly loads. However, KEPCO would like to have their methods improved both theoretically and practically. In this paper, we analyze their current indirect methods and detect their faults to design better indirect estimation methods. Under one of the assumptions of "no cooling load in April or May", the linear relationship between basic loads and GDP's, and the normalized seasonal factors of the Winters' multiplicative seasonal model, we provide ten indirect estimation methods in total and suggest the estimated cooling load(1988-1999) based on our various indirect methods.

• KIEE International Transactions on Power Engineering
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• v.5A no.1
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• pp.16-21
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• 2005

In this study, a new Unit Commitment (UC) algorithm is proposed to consider the uncertainty of a daily load profile. The proposed algorithm calculates the UC results with a lower load level than that generated by the conventional load forecast method and the greater hourly reserve allocation. In case of the worst load forecast, the deviation of the conventional UC solution can be overcome with the proposed method. The proposed method is tested with sample systems, which indicates that the new UC algorithm yields a completely feasible solution even when the worst load forecast is applied. Also, the effects of the uncertain hourly load demand are statistically analyzed, particularly by the consideration of the average over generation and the average under generation. Finally, it is shown that independent power producers participating in electricity spot-markets can establish bidding strategies by means of the statistical analysis. Therefore, it is expected that the proposed method can be used as the basic guideline for establishing bidding strategies under the deregulation power pool.

• Electrical & Electronic Materials
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• v.7 no.3
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• pp.200-205
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• 1994

The FEM technique was applied to simulate the change of stress characteristics for various structural parameters and loading positions of the load cell. The output voltage of the load cell was then computed to compare with the manufactured load cell. The tendency of the stress variations of the load cell was well agreed with the basic formula of the single fixed. beam. Also, the stress characteristics according to the change of loading positions showed respective featured results as different structure. The calculated output voltages of the load cell were very close to those of the real manufactured ones.

• Journal of Ocean Engineering and Technology
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• v.33 no.5
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• pp.447-453
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• 2019

Recently, environmental regulations have been strengthened for SOX, NOX, and CO2, which are ship exhaust gases. In addition, according to the 4th Industrial Revolution, research on autonomous ship technology has become active and interest in electric propulsion systems is increasing. This paper analyzes the power load characteristics of an electric propulsion ship, which is the basic technology for an autonomous ship, in terms of energy management. For the load analysis, data were collected for a 6,800 TEU container ship with a mechanical propulsion system, and the propulsion load was converted to an electric power load and clustered according to the characteristics using a SOM (Self-Organizing Map). As a result of the load analysis, it was confirmed that the load characteristics of the ship could be explained by the operation mode of the ship.

• KEPCO Journal on Electric Power and Energy
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• v.7 no.1
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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.

• Journal of Electrical Engineering and Technology
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• v.2 no.3
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• pp.329-334
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• 2007

In this paper, a new load flow algorithm is proposed on the basis of distributed load modeling in radial distribution networks. Since the correct state data in the distribution power networks is basic for all distribution automation algorithms in the Distribution Automation System (DAS), the distribution networks load flow is essential to obtain the state data. DAS Feeder Remote Terminal Units (FRTUs) are used to measure and acquire the necessary data for load flow calculations. In case studies, the proposed algorithm has been proven to be more accurate than a conventional algorithm; and it has also been tested in a simple radial distribution system.

• Journal of Mechanical Science and Technology
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• v.18 no.6
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• pp.946-954
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• 2004

A model in the form of a Bearing Load Distribution (BLD) matrix in the Multi Bearing Rotor System (MBRS) is established by a transfer matrix equation with the consideration of a bearing load, elevation and uniform load distribution. The concept of Bearing Load Sensitivity (BLS) is proposed and matrices for load and elevation sensitivity are obtained. In order to share MBRS design resources on the Internet with remote customers, the basic principle of Remote Computing (RC) based on the Internet is introduced ; the RC of the BLD and BLS is achieved by Microsoft Active Server Pages (ASP) technology.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.19 no.6
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• pp.427-433
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• 2007

Generally, H.V.A.C load capacity in early planning phase can presume with maximum thermal load. Basic data can prove by air conditioning equipment system data analysis at existing building. There are poor and not reliable alternative presentation. In this paper, measured data after use H.V.A.C load calculation K-load program reply choosing standard building and variables simulation. And I founded peak load correlation graph and mode for several kinds of variable and contents of size. I wish that equipment designer is beaconed to produce optimum capacity at building as quantitative through this result.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.246-250
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• 1989

Owing to the rapid development of economy and the higher living standard of people, electricity demands have growth and the peak load has been increased rapidly. To cope with this impacts and to reduce the cost of service,utilities are conserned about power load management program. This paper shows a scheme of power load control and the basic structure of direct load control system. And also radio control method using the public pager which is one of the best economical and serviceable method in techniques will be introduced briefly.