• Journal of international Conference on Electrical Machines and Systems
• /
• v.2 no.1
• /
• pp.104-110
• /
• 2013

In this paper an application of centralized pitch angle controller for fixed speed wind turbines based wind farm to mitigate load frequency fluctuation is presented. Reference signal for the pitch angle of each wind turbine is calculated by using proposed centralized control system based on wind speed information. The wind farm in the model system is connected to a multi machine power system which is composed of 4 synchronous generators and a load. Simulation analyses have been carried out to investigate the performance of the controller using real wind speed data. It is concluded that the load frequency of the system can be controlled smoothly.

• KEPCO Journal on Electric Power and Energy
• /
• v.2 no.1
• /
• pp.33-41
• /
• 2016

To verify that the friction damper used to high buildings as a kind of control technology of wind vibration can reduce dynamic behaviors of PTTs effectively, slip dampers in this paper are proposed to absorb the energy through relatively frictional movement of slip dampers applied to main post of a PTT (Power Transmission Tower) when dynamic displacement of a PTT occurs. The result of dynamic analysis is presented to determine the capacity of the damper system by controlling damping ratio on the resonance condition. It is observed that by installing slip dampers at a PTT the strain amplitudes of the main post caused by wind load are effectively reduced. Therefore it is shown that the proposed damper satisfies the strengthened wind-load design standards, and its efficacy was also validated experimentally by field testing.

• Proceedings of the KIEE Conference
• /
• 2005.07a
• /
• pp.359-361
• /
• 2005

This paper presents the method of countermeasures before voltage collapse by load encroachment(impedance of load ability on R-X locus decrease toward zero point) and describes a study of impedance relay(zone-3) operation and voltage instability caused by over load of neighborhood line at contingency of heavy load line.

• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.749-751
• /
• 1999

We acquired operating data in an existing steam turbine power plant using analog control system to investigate operation characteristics. We analyzed a load control logic to develop a digital turbine control system. The load control logic is constituted of load target, load reference, loading rate, load limit and admission mode transfer of valve. The result of this paper is utilized to implement a digital turbine control system.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.6
• /
• pp.934-939
• /
• 2016

This paper made short-term electric load forecasting by using temperature data at three-hour intervals (9am, 12pm, 3pm, and 6pm) provided by the Korea Meteorological Administration (KMA). In addition, the electric power pattern was created using existing electric power data, and temperature sensitivity was derived using temperature and electric power data. We made power load forecasting program using LabVIEW, a graphic language.

• Proceedings of the KIEE Conference
• /
• summer
• /
• pp.298-300
• /
• 2004

Arc-furnace facilities consume 9,895,165(MWh) which is about 69.6 Percent of electronic furnace power consumption. and interior of a country demand power have inclosed annual. but becaused of the problem of cost, power plant location, and environment have faced difficulty to electric power supply. In this paper, Examining Load cutting of Arc-furnace that is dominating high weight of industry electric power use. and it is expected to solve easily electric power supply and demand problem by highest Priority load cutting examination of Arc-furnace when electric power supply and demand problem happens to area electric power system when is urgent.

• Proceedings of the KIEE Conference
• /
• 2001.05a
• /
• pp.201-205
• /
• 2001

This paper presents the load modeling process and bus load models for KEPCO power system. At first, load devices commonly used in KEPCO power systems were selected, and tested for measuring the voltage and frequency sensitivity of active and reactive power. From this test, about 40 voltage and frequency dependent load models have been obtained. The bus load composition rate for KEPCO power system has been determined using the various recent surveys and papers in order to develop the load model for a power system bus. To verify the accuracy of developed bus load models, the field test for measuring active and reactive power according to artificial variation of the bus voltage was performed at 8 substations for spring summer, autumn, winter cases. With data of this seasonal field test, more reliable bus load models for KEPCO power systems were developed.

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

• KEPCO Journal on Electric Power and Energy
• /
• v.7 no.1
• /
• pp.125-128
• /
• 2021

This paper presents the root cause failure analysis of the circulating water pump in the 560 MW thermal power plant. A fractured austenitic stainless-steel shaft operated for 24 years was examined. Fracture morphology was investigated by micro and macro-fractographic analysis. The metallurgical analyses including chemical analysis, metallography and hardness testing were performed. The analysis reveals that the pump shaft was fractured due to the reverse bending load with combination of rotating bending load. Corrective actions for plant operator was recommended based on the analysis.

• KIPS Transactions on Computer and Communication Systems
• /
• v.5 no.10
• /
• pp.293-302
• /
• 2016

Since the electricity is produced and consumed simultaneously, predicting the electric load and securing affordable electric power are necessary for reliable electric power supply. In particular, a university campus is one of the highest power consuming institutions and tends to have a wide variation of electric load depending on time and environment. For these reasons, an accurate electric load forecasting method that can predict power consumption in real-time is required for efficient power supply and management. Even though various influencing factors of power consumption have been discovered for the educational institutions by analyzing power consumption patterns and usage cases, further studies are required for the quantitative prediction of electric load. In this paper, we build an electric load forecasting model by implementing and evaluating various machine learning algorithms. To do that, we consider three building clusters in a campus and collect their power consumption every 15 minutes for more than one year. In the preprocessing, features are represented by considering periodic characteristic of the data and principal component analysis is performed for the features. In order to train the electric load forecasting model, we employ both artificial neural network and support vector machine. We evaluate the prediction performance of each forecasting model by 5-fold cross-validation and compare the prediction result to real electric load.