• Journal of the Korean Professional Engineers Association
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• v.44 no.2
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• pp.29-33
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• 2011

In recent years, maximum electric power demand has been increasing steadily. But, Electric Power Supply & Demand problem is occurring due to lack of electric power reserve ratio caused by electric power peak. For this reason, I investigated the current status of the Electric Power Supply & Demand and established Electric Power Supply & Demand and established Electric Power Supply & Demand measures. I will expect that this paper will be contributed balanced and stable Electric Power Supply & Demand management.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1427-1434
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• 2017

Since the late 2000s, there has been growing preparation in South Korea for a sudden reunification of South and North Korea. Particularly in the power industry field, thorough preparations for the construction of a power infrastructure after reunification are necessary. The first step is to estimate the peak load demand. In this paper, we suggest a new peak demand estimation methodology by integrating existing correlation analysis methods between economic indicators and power generation quantities with a power supply interruption model in consideration of power consumption patterns. Through this, the potential peak demand and actual peak demand of the Nation, which experiences power supply interruption can be estimated. For case studies on North Korea after reunification, the potential peak demand in 2015 was estimated at 5,189 MW, while the actual peak demand within the same year was recorded as 2,461 MW. The estimated potential peak demand can be utilized as an important factor when planning the construction of power system facilities in preparation for reunification.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.10
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• pp.389-398
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• 1985

Recently maximum power demand of our country has become to be under the great in fluence of electric cooling and air conditioning demand which are sensitive to weather conditions. This paper presents the technique and algorithm to forecast the long-term maximum power demand considering the characteristics of electric power and weather variable. By introducing a weather load model for forecasting long-term maximum power demand with the recent statistic data of power demand, annual maximum power demand is separated into two parts such as the base load component, affected little by weather, and the weather sensitive load component by means of multi-regression analysis method. And we derive the growth trend regression equations of above two components and their individual coefficients, the maximum power demand of each forecasting year can be forecasted with the sum of above two components. In this case we use the coincident dry bulb temperature as the weather variable at the occurence of one-day maximum power demand. As the growth trend regression equation we choose an exponential trend curve for the base load component, and real quadratic curve for the weather sensitive load component. The validity of the forecasting technique and algorithm proposed in this paper is proved by the case study for the present Korean power system.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1067-1070
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• 2002

The maximum demand power management system(the demand controller) is an equipment for demand management. If the pre-estimated load is over the preset power, the demand controller make warnings and break the load circuit according to predefined priority. Then consumption power is maintained below the maximum demand power level. The DTU receives the control commands from demand controller, and then controls loads. In this paper, the power line cables are used for communication between the demand controller and DTUs and monitoring PC. The experiments show that the proposed system is compatible with the conventional system, and feasible for new or remodeling plant.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.3
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• pp.44-50
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• 2014

This paper describes reasonable methods by considering change of outdoor temperature into Customer Baseline Load(CBL) of Demand Resources in Smart Demand Resource Market, which controls peak power demand and maintains reliability of power system. The Smart Demand Resouce Market, which KPX(Korea Power Exchange) implement, is explained and then effects for CBL calculated by considering temperature correction factor are established. Finally, four methods for calculation of CBL are proposed and those results are compared and analyzed.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.149-151
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• 2005

Recently, power supply-demand instability due to the dramatic increase in power usage suchas air-conditioning load at summertime has brought forecasts of decrease in power supply capability. Therefore improving the load factor through systematic load management, in other words, Direct Load Control became necessary. Direct Load Control(DLC) system is kind of a load management program for stabilization of electric power supply-demand. It's purpose is limiting the demand of the demand side selected at peak load or other time periods. The paper presented a Design of Direct Load Controller for control the amount of power demand in demand side. The proposed Controller is cheaper and has ability of storing more power data than pre-existing device.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.4
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• pp.169-174
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• 2013

Due to the increase of power consumption, it is difficult to construct an accurate prediction model for daily peak power demand. It is very important work to know power demand in next day to manage and control power system. In this research, we develop a daily peak power demand prediction method based on Extreme Learning Machine(ELM) with fast learning procedure. Using data sets between 2006 and 2010 in Korea, the proposed method has been intensively tested. As the prediction results, we confirm that the proposed method makes it possible to effective estimate daily peak power demand than conventional methods.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.66 no.1
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• pp.7-14
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• 2017

Recently, the power consumption of industrial consumer has increased rapidly, causing problems such as lack of power reserve margin in summer and winter, and therefore there is a growing need for maximum demand power management to consumers. In this paper, we studied small microgrid system consisting of battery ESS and photovoltaic power system, applied to small and medium sized factories to reduce the maximum demand power of daily industrial power load. To verify the validity of the study, we simulated a small microgrid system using Matlab/Simulink software. As a result of applying the simulation to small and medium sized plants that consume a lot of power, it is confirmed that there is a 13% reduction in demand compared to the existing maximum demand power. This result is expected to contribute to the improvement of the power reserve margin.

• Transactions of the Korean hydrogen and new energy society
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• v.33 no.5
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• pp.591-597
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• 2022

Recently, technologies for efficient power grid operation have become important due to climate change. For this reason, predicting power demand using deep learning is being considered, and it is necessary to understand the influence of characteristics of each region, industrial structure, and climate. This study analyzed the power demand of New Jersey in US, with a high urbanization rate and a large service industry, and West Virginia in US, a low urbanization rate and a large coal, energy, and chemical industries. Using recurrent neural network algorithm, the power demand from January 2020 to August 2022 was learned, and the daily and weekly power demand was predicted. In addition, the power grid operation based on the power demand forecast was discussed. Unlike previous studies that have focused on the deep learning algorithm itself, this study analyzes the regional power demand characteristics and deep learning algorithm application, and power grid operation strategy.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1993.10a
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• pp.107-110
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• 1993

This paper presents the technical requirements and configuration of power demand control system in office building Generally, the peak power demand is occurred in cooling period. For power demand control in existing building, the most effective control points are the motors for air handling units.