• 한국지열·수열에너지학회논문집
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• 제8권4호
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• pp.1-7
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• 2012

In this study, computer simulation for demand control strategies to save the electric energy and power price in the building central cooling system is done. The demand control and outdoor reset control algorithms are applied by consideration the electric energy and power price according to the energy consumption characteristics. The suggested control methods show better responses in the power price and energy consumption in comparison with the conventional one.

• 산업경영시스템학회지
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• 제35권1호
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• pp.24-31
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• 2012

This study is designed to predict the overall electric power load, to apply the method of time sharing and to reduce simultaneous load factor of electric power when authorized by user entering demand plans and using schedules into the user's interface for a certain period of time. This is about smart grid, which reduces electric power load through simultaneous load factor of electric power reduction system supervision agent. Also, this study has the following characteristics. First, it is the user interface which enables authorized users to enter and send/receive such data as demand plan and using schedule for a certain period of time. Second, it is the database server, which collects, classifies, analyzes, saves and manages demand forecast data for a certain period of time. Third, is the simultaneous load factor of electric power control agent, which controls usage of electric power by getting control signal, which is intended to reduce the simultaneous load factor of electric power by the use of the time sharing control system, form the user interface, which also integrate and compare the data which were gained from the interface and the demand forecast data of the certain period of time.

• 조명전기설비학회논문지
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• 제28권8호
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• pp.98-105
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• 2014

In this paper, we have analyzed the power consumption property of EVs(Electric Vehicles) chargers established in a public place, proposed reasonable demand factors by the number of established EV chargers and its control method in apartments. The optimization of power system and the suppression of the peak load can be controlled through the proposed demand factors and charging scheduling control algorithm. In this paper, electrical design and an case analysis were carried out on a sample apartment complex to prove the effectiveness of the power system. As a result, emergency power transformer capacity has been reduced by approximately 25%, and we have confirmed that the electric rates saving and the control of peak load value is possible.

• Journal of Electrical Engineering and Technology
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• 제11권2호
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• pp.300-308
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• 2016

Application of demand-side resources to automatic generation control (AGC) has a great significance for improving the dynamic control performance of power system frequency regulation. This paper investigates the possibility of providing regulation services by demand-side energy storage in electric vehicle battery swapping stations (BSS). An interaction framework, namely station-to-grid (S2G), is presented to integrate BSS energy storage into power grid for giving benefits to frequency regulation. The BSS can be regarded as a lumped battery energy storage station through S2G framework. A supplementary AGC method using demand-side BSS energy storage is developed considering the vehicle user demand of battery swapping. The effects to the AGC performance are evaluated through simulations by using a two-area interconnected power grid model with step and random load disturbance. The results show that the demand-side BSS can significantly suppress the frequency deviation and tie-line power fluctuations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.104.1-104
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• 2001

This paper presents a technique to development load control and management system in order to limits a maximum load demand and saves electric energy consumption. The computer programming proper load forecasting algorithm associated with programmable logic control and digital power meter through inform of multidrop network RS 485 over the twisted pair, over all are contained in this system. The digital power meter can measure a load data such as V, I, pf, P, Q, kWh, kVarh, etc., to be collected in statistics data convey to data base system on microcomputer and then analyzed a moving linear regression of load to forecast load demand Eventually, the result by forecasting are used for compost of load management and shedding for demand monitoring, Cycling on/off load control, Timer control, and Direct control. In this case can effectively reduce the electric energy consumption cost for 10% ...

• 대한전기학회:학술대회논문집
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• 대한전기학회 1994년도 하계학술대회 논문집 A
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• pp.106-109
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• 1994

The object of this study is to propose the simplified power demand control system which is appliable to existing buildings or new buildings. Through the technical survey and power demand analysis in office buildings, the electric facilities which can be controlled are selected. Power demand control program can be controlled the electric facilities in order, and displayed the facility operation state. The proposed power demand control system is cost-effective and flexibly adoptable in system upgrade or retrofit.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2008년도 추계학술대회 논문집
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• pp.285-287
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• 2008

This paper represents the electric power load leveling effect of the Light Control System(LCS). The lighting of typical mid-large commercial buildings is the major factor of daytime electric power consumption. Since the national peak power demand occurs in between 11:00 and 16:00, the dimming control of light can contribute the decrease of the power demand We will discuss the load leveling effect of dimming control with LCS.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전력기술부문
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• pp.161-163
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• 2006

This paper introduce the technology of peak demand reduction using automatic water tank pumping system on the apartment. That systems on the apartments installed water tank can control pumping(electricity) demand. Generally, system peak demand is occurred at the same time on workday and many water pumps consume electric power randomly. At this point, shift of operating time of water pump can reduce peak demand using automatic water tank pumping system. We were operating this system on some apartments for test of effect of peak demand reduction. and we represent result of demand shift. This result suggests that spread of the automatic water pumping system can contribute to reduce system peak demand and reduce system operation cost.

• 제어로봇시스템학회논문지
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• 제12권7호
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• pp.631-636
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• 2006

In this paper, an algorithm of time series function forecasting using GMDH(group method of data handling) algorithm that gives more weight to the recent data is proposed. Traditional methods of GMDH forecasting gives same weights to the old and recent data, but by the point of view that the recent data is more important than the old data to forecast the future, an algorithm that makes the recent data contribute more to training is proposed for more accurate forecasting. The average error rate of electric power demand forecasting by the traditional GMDH algorithm which does not use data weighting algorithm is 0.9862 %, but as the result of applying the data weighting GMDH algorithm proposed in this paper to electric power forecasting demand the average error rate by the algorithm which uses data weighting algorithm and chooses the best data weighting rate is 0.688 %. Accordingly in forecasting the electric power demand by GMDH the proposed method can acquire the reduced error rate of 30.2 % compared to the traditional method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1379-1383
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• 2005

Introducing the market into the electricity industry lets the multiple participants get into new competition. These multiple participants of the market need new business strategies for providing value added services to customer. Therefore they need the accurate customer information about the electricity demand. Demand characteristic is the most important one for analyzing customer information. In this study load profile data, which can be collected through the Automatic Meter Reading System, are analyzed for getting demand patterns of customer. The load profile data include electricity demand in 15 minutes interval. An algorithm for clustering similar demand patterns is developed using the load profile data. As results of classification, customers are separated into several groups. And the representative curves for the groups are generated. The number of groups is automatically generated. And it depends on the threshold value for distance to separate groups. The demand characteristics of the groups are discussed. Also, the compositions of demand contracts and standard industrial classification in each group are presented. It is expected that the classified curves will be used for tariff design, load forecasting, load management and so on. Also it will be a good infrastructure for making a value added service related to electricity.