• 한국산학기술학회논문지
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• 제16권12호
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• pp.8576-8584
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• 2015

전력수요의 예측은 안정적인 전력공급을 위한 수급계획수립을 위해서 그리고 전력계통의 최적운영계획수립을 위해서도 필요하다. 특히 안정적인 전력수급확보를 위해서는 중장기 전력수요예측이 중요하고 공급안정성 강화를 위해서는 지역별 전력수요예측이 중요하다. 지역별 전력수요예측은 지역에 소요되는 부하를 충족시킬 수 있도록 송전선로 및 변전소 등의 계통망의 최적상태 구성 및 유지를 위한 필수적인 과정으로 알려져 있다. 따라서 본 논문은 12개월(중장기)동안 대한민국 시도별 16개 지역의 전력사용량을 SARIMA 모형을 이용하여 예측하는 방법을 제안한다.

• 한국조명전기설비학회지:조명전기설비
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• 제9권5호
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• pp.37-40
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• 1995

In this paper, we investigate the daily load curve and yearly lighting hours of general and industrial Korean lighting apparatus. The daily load curve of lighting apparatus shows the peak use at 8 p.m. in general and 10 a.m. in industrial building. The yearly lighting hours are 2,948 hours in general and 4,066 hors in industrial building.

• 한국기계가공학회지
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• 제19권11호
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• pp.78-86
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• 2020

A stress analysis was performed to verify the stability of the digging part of a garlic harvester. A finite element analysis was performed to examine the distribution and concentrated loads on the digging part of the blade and contact plate. Moreover, the stability and maximum deformation of the digging part were determined. Under a distributed load, the maximum principal stress, total deformation, and minimum safety factor ranged from 64-128 MPa, 0.35-0.70 mm, and 2.9-5.7, respectively. The analysis results for the distribution load indicated that the maximum stress occurred at the center of the blade. In contrast, under the concentrated load, the maximum principal stress, total deformation, and minimum safety factor ranged from 66-247 MPa, 0.35-0.79 mm, 1.48-5.53, respectively. The analysis results for the concentrated load indicated that stress and deformation were larger toward the edge and center, respectively.

• 대한산업공학회지
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• 제22권2호
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• pp.303-311
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• 1996

The Self Healing Ring (SHR) is one of the most Intriguing schemes which provide survivability for telecommunication networks. To design a cost effective SONET ring it is necessary to consider load balancing problems by which the link capacity is determined. The load balancing problem in SONET ring when demand splitting is not allowed is considered in this paper. An efficient algorithm is presented which provides the best solution starting from various Initial solutions. The initial solution is obtained by routing ell demands such that no demands pass through an are In the ring. The proposed algorithm iteratively improves the Initial solution by examining each demand and selecting the maximum load are in its path. The demand whose maximum arc load is biggest is selected to be routed in opposite direction. Computational results show that the proposed algorithm is excellent both in the solution quality and in the computational time requirement. The average error bound of the algorithm is 0.11% of the optimum and compared to dual-ascent approach which has good computational results than other heuristics.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국제학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.869-874
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• 1988

The operational control of the rotary snowplow is considered to improve its working efficiency. The speed of the rotary snowplow is controlled, so that the load to the rotary snowplow is kept constant. As the load can not directly be detected, some items considered for the controlled variable are, for example, the engine revolution, the load pressure and etc. In order to examine these, the working simulation of the rotary snowplow was considered by introducing the experimental equation of the load. The control methods were examined by means of the simple digital control using the personal computer. These control methods were compared with simulations and experiments. Consequently, the working efficiency is improved about 20% than the manual operation.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.301-303
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• 2000

This paper presents Kohonen neural network and wavelet transform analysis based technique for industrial peak load forecasting for the purpose of peak demand control. Firstly, one year of historical load data were sorted and clustered into several groups using Kohonen neural network and then wavelet transforms are adopted using the Biorthogonal mother wavelet in order to forecast the peak load of one hour ahead. The 5-level decomposition of the daily industrial load curve is implemented to consider the weather sensitive component of loads effectively. The wavelet coefficients associated with certain frequency and time localization is adjusted using the conventional multiple regression method and the components are reconstructed to predict the final loads through a six-scale synthesis technique.

• 전기학회논문지
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• 제65권6호
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• pp.946-954
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• 2016

Energy industry is undergoing a paradigm shift in customer participation in the smartgrid. Customers traditionally consume electrical power. But nowadays not only do they generate electricity from private distributed generations, they can participate in demand response programs with their negawatt power which means a theoretical unit of power representing an amount of energy saved. Therefore development of decision-making criteria for electric load aggregation becomes a greater consideration as an amount of energy saved from demand response resources increases. This paper proposes load aggregators' decision-making criteria in the industrial sector where it made up the largest portion in demand response portfolio in order to assure reliability performance for demand response resources.

• 설비공학논문집
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• 제25권1호
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• pp.1-6
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• 2013

This study aims to reduce cooling energy by grasping kinds of heating load in building in order to decrease cooling energy in summer and eliminate efficiently heating load. Lighting heating value was confirmed through examination and experiment concerning lighting heating and reducible exhaustion value was extracted lighting apparatus. The optimal exhaust system by air conditioning type was suggested for applying lighting heat exhaust system and the method contributing to promotion supplying low energy architecture was suggested by predicting reduced cooling load.

• 전기학회논문지P
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• 제53권3호
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• pp.103-109
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• 2004

This paper has presented, taking an example of a gas separation plant, dynamic analysis on frequency decline caused by the over-loading at the generator and the knee point causing voltage instability due to reactive power required by re-acceleration of large induction motors, resulting in phenomena of failure in the conventional frequency load shedding. In order to resolve the voltage instability problem, a design of load shedding system employing under-voltage relays has been proposed to the industrial power system containing large induction motors in addition to the conventional load shedding employing frequency relays. For the purpose of dynamic analysis, models of gas turbine and governor, synchronous generator, brushless exciter, and induction motor are introduced.

• Journal of information and communication convergence engineering
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• 제20권4호
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• pp.295-302
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• 2022

This paper contains the development of a smart power device designed to collect load power data from industrial manufacturing machines, predict future variations in load power data, and detect abnormal data in advance by applying a machine learning-based prediction algorithm. The proposed load power data prediction model is implemented using a Long Short-Term Memory (LSTM) algorithm with high accuracy and relatively low complexity. The Flask and REST API are used to provide prediction results to users in a graphical interface. In addition, we present the results of experiments conducted to evaluate the performance of the proposed approach, which show that our model exhibited the highest accuracy compared with Multilayer Perceptron (MLP), Random Forest (RF), and Support Vector Machine (SVM) models. Moreover, we expect our method's accuracy could be improved by further optimizing the hyperparameter values and training the model for a longer period of time using a larger amount of data.