• Korean Journal of Construction Engineering and Management
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• v.20 no.3
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• pp.105-112
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• 2019

Due to abnormal high temperature, electric power demand has exceeded the backup power reserved for emergency case, hence, resulting in a major power outage. In today's overcrowded cities, the unexpected disruption in energy supply and demand is a major threat to the enormous economic damage and urban malfunctions. Existing methods for estimating the demand of the emergency power source do not lend themselves to predict the actual demand in the spatial dimension of the city. In addition, the reserve power is arbitrarily distributed in the case of emergency. This paper presents a method that predicts the emergency power demand using the spatial distribution of emergency power demand by applying the daily energy consumption intensity and emergency power demand according to urban spatial information and building use.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.6
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• pp.440-448
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• 2022

Recently, due to the introduction of distributed energy resources, the optimal resource allocation problem of the power network is more and more important, and the distributed resource allocation method is required to process huge amount of data in large-scale power networks. In the optimal resource allocation problem, many studies have been conducted on the case when the supply-demand balance is satisfied due to the limitation of the generation capacity of each generator, but the studies considering the supply-demand imbalance, that total demand exceeds the maximum generation capacity, have rarely been considered. In this paper, we propose the consensus-based distributed algorithm for the optimal resource allocation of power network considering the supply-demand imbalance condition as well as the supply-demand balance condition. The proposed distributed algorithm is designed to allocate the optimal resources when the supply-demand balance condition is satisfied, and to measure the amount of required resources when the supply-demand is imbalanced. Finally, we conduct the simulations to verify the performance of the proposed algorithm.

• The Journal of Information Systems
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• v.24 no.2
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• pp.73-96
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• 2015

Purpose Information security industry is rapidly growing, but has been confronted with many challenges in a business environment. One of them is the imbalance between supply and demand of information security manpower, which has caused an insecure market situation. Therefore, this study has derived factors of promoting and hindering information security manpower from governance, academics, corporations, and workforce perspectives, and has analyzed a sequence of cause and effect of each factor. Design/methodology/approach This study is an exploratory research based on the interviews. The causal loop diagram (CLD) was developed to deduce key issues and propose alternatives. Findings The result of this study is expected to help the development of information security manpower in Korea, by minimizing the potential negative effects as well as maximizing the positive effects. This study found out the dynamic causes and effects of the security manpower system in each stakeholder's perspective. The cause-and-effect relationships between the stakeholders will be able to contribute to solve the imbalance of supply and demand in security manpower system.

• Journal of Information Technology Services
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• v.10 no.3
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• pp.265-284
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• 2011

The purpose of this study is to analyze the demand for telemedicine and telehealthmanagement services, which are key elements of home based u-health. The conjoint analysis, which is a conventional method for demand analysis for newly introduced products, is employed, utilizing the survey data on 500 seoul citizens. Further, multivariate probit model is used to estimate the demand. The result shows that the demand for telemedicine services is greater than that of telehealthmanagement services. Further, home-based u-health services will play a role as a complementary for face-to-face medical treatments, rather than a substitute. Meanwhile, the demand for home-based u-health services is found to be very sensitive to price.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.10
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• pp.43-48
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• 2014

With the energy paradigm shift from supply side management to demand side management, many researches have been done on demand side resource management and demand response. At the same time, Obix, BacNet-WS and OPC-UA are popularly used in buildings and industry energy management system. However, it is not easy to interchange the data and information among the systems cause a variety of protocols are used in buildings and factories. Therefore, in this paper, we are proposing an open business platform not only to integrate and manage the demand resources using various protocols and standards, but also to allow to plug-ins a new business service on top of the platform.

• Management Science and Financial Engineering
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• v.11 no.3
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• pp.125-136
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• 2005

As the importance of time-based competition is increasing, information systems for supporting the immediate decision making is strongly required. Especially high -tech product firms are under extreme pressure of rapid response to the demand side due to relatively short life cycle of the product. Therefore, the objective of our research is proposing a framework of estimating demand curve based on e-auction data, which is extremely easy to access and well reflect the limited demand curve in that channel. Firstly, we identify the advantages of using e-auction data for full demand curve estimation and then verify it using Agent-Eased-Modeling and Tobin's censored regression model.

• Journal of Information Technology Applications and Management
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• v.24 no.2
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• pp.81-96
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• 2017

Forecasting long-term mobile service demand is inevitable to establish an effective frequency management policy despite the lack of reliability of forecast results. The statistical forecasting method has limitations in analyzing how the forecasting result changes when the scenario for various drivers such as consumer usage pattern or market structure for mobile communication service is changed. In this study, we propose a dynamic model of the mobile communication service market using system dynamics technique and forecast the future demand for long-term mobile communication subscriber based on the dynamic model, and also experiment on the change pattern of subscriber demand under various scenarios.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.1956-1963
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• 2010

Studies on the development of various energy management programs and real-time bidirectional information infrastructures have been actively conducted to promote the reduction of power demands and CO2 emissions effectively. In the conventional energy management programs, the demand response program that can transition or transfer the power use spontaneously for power prices and other signals has been largely used throughout the inside and outside of the country. For measuring the effect of such demand response program, it is necessary to exactly estimate short-term loads. In this study, the power consumption patterns in both individual and group consumers were analyzed to estimate the exact short-term loads, and the relationship between the actual power consumption and seasonal factors was also analyzed.

• Journal of Information Technology Applications and Management
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• v.26 no.2
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• pp.61-73
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• 2019

In 2019, 5G mobile communication technology will be commercialized. From the viewpoint of technological innovation, 5G service can be applied to other industries or developed further. Therefore, it is important to measure the demand of the Internet of things (IoT) because it is predicted to be commercialized widely in the 5G era and its demand hugely effects on the economic value of 5G industry. In this paper, we applied Bayesian method on regression model to find out the demand of 5G IoT service, wearable service in particular. As a result, we confirmed that the Bayesian regression model is closer to the actual value than the existing regression model. These findings can be utilized for predicting future demand of new industries.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.41-46
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• 2014

Bus service is easily adjusted to accommodate the changed demand. Despite the flexibility of that, its relocation should overcome the following problems: first, Bus line rearrangement should consider the balance between the demand and the supply to enhance the transit equity among the users scattered around the area that supply against demand imbalances. Second, the existing demand analysed is to crude since the demand was analysed based on TAZ. mainly based on the Dong unit. Utilization of the GWR and GIS-T data can resolve the problem. In this paper, the limitation of the conventional transit demand analysis model is overcome by deploying the GWR model which identifies the transit demand based on the geographic relation between the service location and those of the users. GWR model considers the spatial effect of the bus demand in accordance with the distance to the each bus stops using SCD(Smart Card Data) and BIS(Bus Information System). This demand map was then superimposes with the existing bus route which identified the areas where the balance between demand and supply is severly skewed. since the analysis was computed with SCD and BIS at every bus stops. the shortage and surplus of bus service of entire study area could computed. Further. based on this computational result and considering the entire bus service capacity data. Bus routes optimization from the oversupplied areas to the undersupplied area was illustrated thus this study clearly compared the benefits the GIS.