• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.6
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• pp.852-856
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• 2015

Demand side management (DSM) program has been frequently used for reducing the system peak load because it gives utilities and independent system operator (ISO) a convenient way to control and change amount of electric usage of end-use customer. Planning and operating methods are needed to efficiently manage a DSM program. This paper presents a planning method for DSM program. A planning method for DSM program should include an electric load forecasting, because this is the most important factor in determining how much to reduce electric load. In this paper, load forecasting with the temperature stochastic modeling and the sensitivity to temperature of the electric load is used for improving load forecasting accuracy. The proposed planning method can also estimate the required day, hour and total capacity of DSM program using Monte-Carlo simulation. The results of case studies are presented to show the effectiveness of the proposed planning method.

• Journal of Electrical Engineering and Technology
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• v.2 no.2
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• pp.145-151
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• 2007

Electric load components have different characteristics according to the variation of voltage and frequency. This paper presents the load modeling of an electric locomotive by the parameter identification method. The proposed method for load modeling is very simple and easy for application. The proposed load model of the electric locomotive is represented by the combination of the loads that have static and dynamic characteristics. This load modeling is applied to the KTX in Korea to verify the effectiveness of the proposed method. The results of proposed load modeling by the parameter identification follow the field measurements very exactly.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1384-1386
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• 2005

This paper focuses on development of load test simulator of a steam turbine-generator in a nuclear power plant. When load is taken off from electrical power network, it is very difficult to effectively control the steam flow to turbine of the nuclear turbine-generator, because of disturbances, such as electrical load and network unbalance on electrical network. Up to the present time, the conventional control system has been used for the load control on nuclear steam generator, owing to the easy control algorithms and the advantage which have been proven on the nuclear power plant. However, since there are problems with stability control during low power and start-up, only a highly experienced operator can operate during those procedures. Also, a great deal of time and an expensive simulator is needed for the training of an operator. The KEPRI is developed simulator for 600MW nuclear power plant to take a test of generator load rejection, throttle valve, and turbine load control. Total load test is implemented before start up.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1497-1502
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• 2014

Electric load forecasting is essential for stable electric power supply, efficient operation and management of power systems, and safe operation of power generation systems. The results are utilized in generator preventive maintenance planning and the systemization of power reserve management. Development and improvement of electric load forecasting model is necessary for power system maintenance and operation. This paper proposes daily maximum electric load forecasting methods for the next 4 weeks with a seasonal autoregressive integrated moving average model and an exponential smoothing model. According to the results of forecasting of daily maximum electric load forecasting for the next 4 weeks of March, April, November 2010~2012 using the constructed forecasting models, the seasonal autoregressive integrated moving average model showed an average error rate of 6,66%, 5.26%, 3.61% respectively and the exponential smoothing model showed an average error rate of 3.82%, 4.07%, 3.59% respectively.

• Journal of Advanced Marine Engineering and Technology
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• v.26 no.3
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• pp.313-319
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• 2002

Since the oil crisis in 1970, a great deal of effort has been made to develop automatic electric load sharing systems as a part of the efforts to save energy. A large scale electric generating system composes more than two generators whose characteristics may be different. When such a system is operated individually or in parallel, the lagrange multiplier's method has difficulty in achieving optimal load distribution because generators usually have the limitations of the operating range with inequality constraints. Therefore, a suitable operating mode of generators has to be decided according to the selection of the generators to meet electric power requirements at the minimum cost. In this study, a method which solves the optimal electric load distribution problem using the dynamic programming technique is proposed. This study also shows that the dynamic programming method has an advantage in dealing with the optimal load distribution problem under the limitations of the operating range with inequality constraints including generator operation mode. In this study, generator operating cost curve of second order equation by shop trial test results of diesel generators are used. The results indicate that the proposed method can be applied to the ship's electric generating system.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.4
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• pp.403-408
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• 2014

Lots of electric power has been wasted through the load bank usually in the container boxes during the generator load test of the ship and offshore plant in the new ship building. Therefore in this research, the quantity of wasted electric power through generator load test under construction was investigated on big shipbuilding yard and quantity of electric power that can be recovered is analyzed when produced electric power during the generator load test is connected to KEPCO Grid, according to laboratory's experiment result where recovers electric power produced from small generator connected to KEPCO Grid.

• KEPCO Journal on Electric Power and Energy
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• v.5 no.1
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• pp.17-24
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• 2019

In this paper, we analyzed the effect of power system load model on the short-term voltage stability analysis results. First, we introduced common load models. We also confirmed that some load models can not represent actual system phenomena even if the model parameters are optimized. Also, we studied about the influences of load parameters and regional characteristics of load model on the sort-term voltage stability of KEPCO power system considering the contingency. The results showed that the importance of selecting a load model was confirmed again. And we recognized about it can be understood that it should reflect the load characteristics of the area near the assumed contingency more accurately.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2825-2827
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• 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.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.1
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• pp.61-69
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• 2016

Understanding load patterns and customer classification is a basic step in analyzing the behavior of electricity consumers. To achieve that, there have been many researches about clustering customers' daily load data. Nowadays, the deployment of advanced metering infrastructure (AMI) and big-data technologies make it easier to study customers' load data. In this paper, we study load clustering from the view point of yearly and daily load pattern. We compare four clustering methods; K-means clustering, hierarchical clustering (average & Ward's method) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise). We also discuss the relationship between clustering results and Korean Standard Industrial Classification that is one of possible labels for customers' load data. We find that hierarchical clustering with Ward's method is suitable for clustering load data and KSIC can be well characterized by daily load pattern, but not quite well by yearly load pattern.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.11
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• pp.1590-1597
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• 2013

Electric power is an important part in economic development. Moreover, an accurate load forecast can make a financing planning, power supply strategy and market research planned effectively. This paper used the fuzzy logic system to predict the regional electric power load. To design the fuzzy prediction system, the correlation-based clustering algorithm and TSK fuzzy model were used. Also, to improve the prediction system's capability, the moving average technique and relative increasing rate were used in the preprocessing procedure. Finally, using four regional electric power load in Taiwan, this paper verified the performance of the proposed system and demonstrated its effectiveness and usefulness.