• 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.

• Industrial Engineering and Management Systems
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• 제3권2호
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• pp.129-133
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• 2004

Studies on the optimal location of retail store have been made in case of no obstacle(Minagawa etal. 1999). This paper deals with the location problem of retail store considering obstacles (e.g. rivers, railways, highways, etc.) and obstacle-overcoming points (e.g. bridges, railway crossings, zebra crossings, overpasses, etc.). We assume that (1) commercial goods dealt here are typically convenience goods, (2) the population is granted as potential demand, (3) the apparent demand is a function of the maximum migration length and the distance from the store to customers, (4) the scale of a store is same in every place and (5) there is no competitor. First, we construct the basic model of customers' behavior considering obstacles and obstacle-overcoming points. Analyzing the two dimensional model, the arbitrary force attracting customers is represented as a height of a cone where the retail store is located on the center. Second, we formulate the total demand of customers and determine the optimal location that maximizes the total demand. Finally, the properties of the optimal location are investigated by simulation.

• 설비공학논문집
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• 제21권10호
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• pp.553-558
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• 2009

Energy demand characteristics of hotel, hospital, and office building are compared to provide guidelines for combining building in community energy system design. The annual, monthly, and daily energy demand patterns for electricity, heating, hot water and cooling are qualitatively compared and important features are delineated based on the energy demand models. Key statistical values such as the mean, the maximum are also provided. Important features of the hourly demand patterns are summarized for weekdays and weekends. Substantial variations in both magnitudes and patterns are observed among the 3 building types and smart grouping or combination of building type and size is essential for a successive energy supply.

• 산업경영시스템학회지
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• 제17권31호
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• pp.59-72
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• 1994

This paper deals with ordering policies of consumable goods which have large demand rates in a multi-level distribution system. The system we are concerned consists of one Central Distribution Center(CDC) and N non-identical Regional Distribution Centers(RDCs) which have different demand rates, minimum fillrates, leadtimes, etc. The customer demand on the RDC is stationary poisson and the RDCs demand on the CDC is superposition of Q-stage Erlang distributions. We approximate the RDCs and CDC demand distribution to nomal in order to enhance the efficiency of algorithm. The relevant costs include a fixed ordering cost and inventory holding cost, and backorder cost. The objective is to find a continuous-review ordering policy that minimizes the expected average costs under constraints of minimum fill rates of RDCs and maximum allowable mean delay of CDC. We developed an algorithm for determining the optimal ordering policies of the CDC and the RDCs. We verified and compared the performance of the algorithm through the simulation using the algorithm result as the input parameters.

• 전기학회논문지
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• 제65권7호
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• pp.1128-1134
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• 2016

Demand response provides customer load reductions based on high market prices or system reliability conditions. One type of demand response, price-based program, induces customers to respond to changes in product rates. However, there are large-scale general and industrial customers that have difficulty changing their energy consumption patterns, even with rate changes, due to their electricity demands being commercial and industrial. This study proposes an in-house pricing model for large-scale general and industrial customers, particularly those with multiple business facilities, for self-regulating demand-side management and cost reduction. The in-house pricing model charges higher rates to customers with lower load factors by employing peak to off-peak ratios in order to reduce maximum demand at each facility. The proposed scheme has been applied to real world and its benefits are demonstrated through an example.

• Earthquakes and Structures
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• 제14권3호
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• pp.203-214
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• 2018

Predictive demand and collapse fragility functions are two essential components of the probabilistic seismic demand analysis that are commonly developed based on statistics with enormous, costly and time consuming data gathering. Although this approach might be justified for research purposes, it is not appealing for practical applications because of its computational cost. Thus, in this paper, Bayesian regression-based demand and collapse models are proposed to eliminate the need of time-consuming analyses. The demand model developed in the form of linear equation predicts overall maximum inter-story drift of the lowto mid-rise regular steel moment resisting frames (SMRFs), while the collapse model mathematically expressed by lognormal cumulative distribution function provides collapse occurrence probability for a given spectral acceleration at the fundamental period of the structure. Next, as an application, the proposed demand and collapse functions are implemented in a seismic fragility analysis to develop fragility and consequently seismic demand curves of three example buildings. The accuracy provided by utilization of the proposed models, with considering computation reduction, are compared with those directly obtained from Incremental Dynamic analysis, which is a computer-intensive procedure.

• 한국빅데이터학회지
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• 제5권1호
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• pp.227-239
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• 2020

본 논문에서는 산업현장에서 통신 오류에도 불구하고 최대전력수요를 예측하는 방법을 소개한다. 최근 국내의 탈원전 정책으로 전력가격상승은 불가피하며, 이에 따른 전력수요 관리를 위한 전력사용량과 최대부하관리는 중요한 문제로 부상하고 있다. 이에 따라, 피크전력을 예측하고 관리하는 것이 중요하다. 하지만 실제 산업현장에서는 각종 설비 및 센서에서 발생하는 노이즈 등으로 인해 측정된 전력데이터의 손실 및 변조 등의 문제가 발생한다. 측정된 유효전력 데이터가 손실된 경우 정확한 값을 예측하기 어렵다. 이 연구는 측정된 유효전력 데이터가 손실될 경우 이상 징후와 결측값을 예측하고 수정하는 모델을 제시한다. 본 연구에 사용된 모델은 산업현장에서 통신 오류가 발생할 경우 최대 전력수요를 예측하는 데 유용할 것으로 예상한다.

• 전기저널
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• 1호통권145호
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• pp.39-43
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• 1989

• 전기학회논문지P
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• 제58권4호
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• pp.505-510
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• 2009

In this paper, building energy analysis and energy cost of power stand up and demand control over the power proposed to reduce power demand. Through analysis of the load power demand special day were able to apply the pattern. In addition, the existing rate of change of load forecasting to reduce the large errors were not previously available data. And daily schedules and special day for considering the exponential smoothing methods were used. Previous year's special day and the previous day due to the uncertainty of the load and the model components were considered. The maximum demand power control simulation using the fuzzy control of power does not exceed the contract. Through simulation, the benefits of the proposed energy-saving techniques were demonstrated.

• 자원ㆍ환경경제연구
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• 제16권4호
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• pp.901-922
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• 2007

본 연구는 하계냉방수요가 기온관련변수의 변화에 대해 어떤 반응을 보이는가, 또 어떤 종류의 기온관련변수가 하계냉방수요에 대한 설명변수로 더 적절한가를 보기 위해 일반적인 선형모형은 물론 각기 다른 특성을 가지고 있는 지수모형과 파워모형, S곡선모형 등 비선형모형을 이용하여 2004년부터 2007년까지 최근 4년간 자료를 분석하였다. 실증분석결과 본 연구에서는 기온관련변수들 가운데 불쾌지수가 일최고기온에 비해 설명력이 우수하다는 사실과 함께 하계냉방전력수요가 전체 4개년도 중 2006년을 제외한 다른 모든 연도들에 대해 지수모형을 따라 기온관련변수의 변화에 대응하고 있는 사실을 규명하였다. 또 소득수준의 향상을 반영하는 비냉방전력수요의 꾸준한 증가와 함께 냉방전력수요도 기온관련변수에 매년 더욱 민감하게 반응하고 있는 사실도 발견하였다.