• 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.

• 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.

• Journal of Electrical Engineering and Technology
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• 제8권6호
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• pp.1296-1304
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• 2013

This study performed an analysis on power demand reduction effects exhibited by demand response programs, which are advanced from traditional demand-side management programs, in the smart grid environment. The target demand response systems for the analysis included incentive-based load control systems (2 month-ahead demand control system, 1~5 days ahead demand control system, and demand bidding system), which are currently implemented in Korea, and price-based demand response systems (mainly critical peak pricing system or real-time pricing system, currently not implemented, but representative demand response systems). Firstly, the status of the above systems at home and abroad was briefly examined. Next, energy saving effects and peak demand reduction effects of implementing the critical peak or real-time pricing systems, which are price-based demand response systems, and the existing incentive-based load control systems were estimated.

• 산업경영시스템학회지
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• 제39권1호
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• 전기학회논문지
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• 제58권1호
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• pp.1-6
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• 2009

The traditional demand prediction was based on the technique wherein electric power corporations made monthly or seasonal estimation of electric power consumption for each area and subscription type for the next one or two years to consider both seasonally generated and local consumed amounts. Note, however, that techniques such as pricing, power generation plan, or sales strategy establishment were used by corporations without considering the production, comparison, and analysis techniques of the predicted consumption to enable efficient power consumption on the actual demand side. In this paper, to calculate the predicted value of electric power consumption on a short-term basis (15 minutes) according to the amount of electric power actually consumed for 15 minutes on the demand side, we performed comparison and analysis by applying a 15-minute interval prediction technique to the average and that to the time series analysis to show how they were made and what we obtained from the simulations.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2003년도 학술대회논문집
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• pp.77-79
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• 2003

For the management of maximum demand power, power control system that is consist of CCMS(Central Control and Management System) and MCCS(Minimum Cost Control and management Software) is proposed. MCCS has the basic functions of the set of target power and the enrollment of load control logic. And also MCCS give the simulation of Power rate that help more effective Demand Control.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.902-904
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• 1996

In this paper, we proposed the reasonable design standard and countermeasures of Demand Factor for large office buildings, that was made by the statistical way considering actual conditions, such as investicated electric equipment capacity, electric power consumption, etc. So as to save electric equipment investment, the decrease of power loss, the improvement of facilities utilization and the decrease of electric rates, we can be contributed by the application of the design standard. The result of saving effect is showed to confirm the practical use of the proposed Demand Factor, and also, it is believed that this proposed Demand Factor will be useful in electric equipment operation and planning.

• 제어로봇시스템학회논문지
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• 제22권12호
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• pp.991-994
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• 2016

This paper presents a load management method based on OpenADR of smart grid. Previous demand side algorithm is restricted on reducing peak power. But, in this paper we suggest a method of performing the energy-saving control according to the power price utilizing building automatic control system installed on the customer side in the case of hourly differential pricing signal is transmitted to the open automated demand response system. And, we showed the integrated demand management software for 3 buildings.

• 전기학회논문지
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• 제60권6호
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• pp.1225-1228
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• 2011

This paper presents an advanced energy saving algorithm in building. It is important to aggregate a various demand side resource which is controllable on demand response environment. Previous demand side algorithm for building is restricted on peak power. In this paper, we suggest duty cycle algorithm for AHU on demand response to reduce the quantity of building power consumption. The test results show that the proposed algorithm is very effective.

• 한국위성정보통신학회논문지
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• 제8권2호
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• pp.56-61
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• 2013

최근 들어 급격하게 증가하는 전력 수요와 더불어, 전력의 효율적인 소모를 위한 다양한 방법이 제시되고 있다. 그 중 가장 대표적인 예가 바로 스마트 그리드에 기반 한 수요반응 시스템이다. 이는 기존의 수동적이고 일방적인 전력 수요가 아닌, 서비스 공급자와 소비자의 통신을 통한 효율적인 전력 소모가 가능한 시스템이다. 이러한 수요반응 시스템은 대부분 이더넷, TCP/IP 기반의 HTTP통신을 활용하며, 현재는 하나로 정의되어 있지 않은 다양한 통신 응용 프로토콜이 존재한다. 본 논문에서는 이러한 수요반응에서 응용할 수 있는 프로토콜들의 종류와 그 응용에 관한 내용에 대하여 분석한다.