• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.10
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• pp.389-398
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• 1985

Recently maximum power demand of our country has become to be under the great in fluence of electric cooling and air conditioning demand which are sensitive to weather conditions. This paper presents the technique and algorithm to forecast the long-term maximum power demand considering the characteristics of electric power and weather variable. By introducing a weather load model for forecasting long-term maximum power demand with the recent statistic data of power demand, annual maximum power demand is separated into two parts such as the base load component, affected little by weather, and the weather sensitive load component by means of multi-regression analysis method. And we derive the growth trend regression equations of above two components and their individual coefficients, the maximum power demand of each forecasting year can be forecasted with the sum of above two components. In this case we use the coincident dry bulb temperature as the weather variable at the occurence of one-day maximum power demand. As the growth trend regression equation we choose an exponential trend curve for the base load component, and real quadratic curve for the weather sensitive load component. The validity of the forecasting technique and algorithm proposed in this paper is proved by the case study for the present Korean power system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.6D
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• pp.673-678
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• 2012

Accurate demand estimating process in the construction of urban railway is very important, and precise validation is required. Existing model formula in the 4 phase model is limited in the estimation of the demand the administrative boundary-based zone system reflects no spatial railway demand characteristics around railway stations. The purpose of this study is improving the accuracy of urban rail demand estimation through segmentations of station influence areas and modal split characteristics within the areas. According to the case analysis, it is possible to set up the ststion influence area with a radius of 500m in the urban region and 1,000m in the suburban. And eastablishing proper segmentations of the ststion influence area shows more accurate results to the real demand of railway stations.

• Journal of Korean Society for Quality Management
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• v.50 no.3
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• pp.349-371
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• 2022

Purpose: Compared to the rapid growth rate of the domestic automotive LED industry so far, the predictive analysis method for demand forecasting or market outlook was insufficient. Accordingly, product characteristics are analyzed through the life trend of LEDs for automotive exterior lamps and the relative strengths of p and q using the Bass model. Also, future demands are predicted. Methods: We used sales data of a leading company in domestic market of automotive LEDs. Considering the autocorrelation error term of this data, parameters m, p, and q were estimated through the modified estimation method of OLS and the NLS(Nonlinear Least Squares) method, and the optimal method was selected by comparing prediction error performance such as RMSE. Future annual demands and cumulative demands were predicted through the growth curve obtained from Bass-NLS model. In addition, various nonlinear growth curve models were applied to the data to compare the Bass-NLS model with potential market demand, and an optimal model was derived. Results: From the analysis, the parameter estimation results by Bass-NLS obtained m=1338.13, p=0.0026, q=0.3003. If the current trend continues, domestic automotive LED market is predicted to reach its maximum peak in 2021 and the maximum demand is $102.23M. Potential market demand was $1338.13M. In the nonlinear growth curve model analysis, the Gompertz model was selected as the optimal model, and the potential market size was $2864.018M. Conclusion: It is expected that the Bass-NLS method will be applied to LED sales data for automotive to find out the characteristics of the relative strength of q/p of products and to be used to predict current demand and future cumulative demand.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.69-76
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• 2003

Near-field ground motions exhibit special characteristics that are different from ordinary far-field ground motions. This paper first briefly examines the characteristics of near-field ground motions associated with fault directivity and fling-step effects. Then evaluation of near-field ground motions by inelatstic response spectrum analysis is performed and analyzed. As a result, ductility demand in near-field ground motions is larger in hanging wall than in foot wall in long period regions. Also in long period regions ductility demand in soil site is larger than that in rock site.

• Korean Journal of Agricultural Science
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• v.25 no.1
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• pp.41-51
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• 1998

This study not only carried out to grasp about the sununarized characteristics of the relationship between international timber market and production trend of wood products, but also focused on the analysis of korean wood demand and the long-term forecast with econometric analysis. The result of regression analysis for wood demand in Korea is that coniferous roundwood demand(CIWD) is explained by coniferous foreign roundwood price(CWRI), Gross domestic product(GDP), a dummy variable. Non-coniferous roundwood demand(NCIWD)is explained by non-coniferous roundwood price(NCWRI), coniferous roundwood price(CWRI), a dummy variable. As the result of long-term forecast by base case, the total roundwood demand was forecasted $11,107,000m^3$ in the year 2000, $11,781,000m^3$ in 2005, $12,565,000m^3$ in 2010. As the result of scenario 1, total roundwood demand was forecasted $11,027,000m^3$ in 2000, $11,435,000m^3$ in 2005, $11,952,000m^3$ in 2010. And as the result by scenario 2, total roundwood demand was forecasted $11,341,000m^3$ in 2000, $12,208,000m^3$ in 2005 $13,257,000m^3$ in 2010.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.8
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• pp.1154-1160
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• 2015

This paper describes the thermal characteristics of underground power cable system terminations according to the change of ambient temperature as well as operating temperature. Recently, the failure has been gradually increasing in outdoor termination during winter season because the power demand was increased by electricity heating system. The power demand and outdoor temperature is difference between day time and night time. The temperature difference has an influence on conductor extension and shrinkage due to conductor force as well as thermal mechanical characteristics. These phenomena have daily repeated during heating and cooling period of conductors. In these cases, the insulation of outdoor terminations might be degraded by the reduced interface pressure surrounding stress relief cone. Therefore, in this paper, the thermal characteristics are variously analysed by simulation considering power demand and ambient temperature condition during winter season at epoxy type termination as well as slip-on type termination

• 공원문화
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• s.26
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• pp.26-32
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• 1984

There have been few researches on the factors affecting forest recreation demand and demand for and value of forest recreation in Korea. This study has three main objectives as follows; First, to introduce the nature of recreation demand, the factors affecting forest recreation demand, and the methods of measuring demand for and benefits from forest recreation by reviewing related literatures. Secondly, to investigate the visitors' characteristics, patterns of recreation activities, and their attitudes for the recreation environments at the Deogyu National Park through interviewing them with the questionaire. Thirdly, to estimate the demand for and benefits of forest recreation at the National Park by Travel Cost Method. The survey was dealt by three trained interviewers at the enterance of the park for 5 days from September 26 to October 10, 1982. The 430 respondents were sampled randomly among 9,391 visitors with 4.6% of sampling rate. As the results, the study revealed that most of visitors to Deogyu National Park were from urban areas and belonged to the intermediate-upper income classes, and that most of them traveled more than 250 km or 4 hours to the site from their origins. And more respondents answered that the recreation environments of the cite were more or less better than other recreation areas. From the date of travel distances and participation rates of 13 cities or counties, the demand schedule of forest recreation at the National Park was established. The estimated equation of total experience demand curve is; Log $VR_i$ 2.6353 – 1.021 Log $D_i$ $R^2=0.9451$ where, $VR_i$ $(%\times1000)$ = Participation rate of the ith origin $D_i$ (km) = Travel distance from the ith origin From the total experience demand curve, the demand curve of recreation resources was built by adding travel cost in distance (km). The regression equation of the recreation resources at the Nation park is; Log V = 4.0304 – 0.8167 Log D $R^2=0.9060$ From the demand schedule of recreation resources, the recreational bendfits of Deogyu National Park was estimated. The estimated bendfits to a visitor from the forest is equivalent to the travel cost of 2,372 km. The study also found out that the demand for recreation resources was less elastic than the demand for the total recreation experience at the Deogyu National Park.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.4
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• pp.172-178
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• 2006

In this paper, an advanced demand clustering algorithm which can explore the planned maintenance outage of generators in changed electricity industry is proposed. The major contribution of this paper can be captured in the development of the long-term estimates for the generation availability considering planned maintenance outage. Two conflicting viewpoints, one of which is reliability-focused and the other is economy-focused, are incorporated in the development of estimates of maintenance outage based on the advanced demand clustering algorithm. Based on the advanced clustering algorithm, in each demand cluster, conventional effective outage of generators which conceptually capture maintenance and forced outage of generators, are newly defined in order to properly address the characteristic of the planned maintenance outage in changed electricity markets. First, initial market demand is classified into multiple demand clusters, which are defined by the effective outage rates of generators and by the inherent characteristic of the initial demand. Then, based on the advanced demand clustering algorithm, the planned maintenance outages and corresponding effective outages of generators are reevaluated. Finally, the conventional demand clusters are newly classified in order to reflect the improved effective outages of generation markets. We have found that the revision of the demand clusters can change the number of the initial demand clusters, which cannot be captured in the conventional demand clustering process. Therefore, it can be seen that electricity market situations, which can also be classified into several groups which show similar patterns, can be more accurately clustered. From this the fundamental characteristics of power systems can be more efficiently analyzed, for this advanced classification can be widely applicable to other technical problems in power systems such as generation scheduling, power flow analysis, price forecasts, and so on.

• Journal of Preventive Medicine and Public Health
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• v.36 no.1
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• pp.71-76
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• 2003

Objectives : New organizational work systems, and their impact on the mental health of employees, are considered to beone of the most important topics in the area of industrial health. This study was conducted to compare job characteristics (job demand and decision latitude) levels, and psychosocial distress of workers in acompany introducing to new organizational work systems, to those of workers managed by traditional work systems. Methods ; A study sample of 627 shipbuilding workers (446the new work organizational system and 181 the traditional system) were recruited for this study. A structured-questionnaire was used to assess general characteristics, job characteristics(work demand, decision latitude), and psychosocial distress. Results : The decision latitude was not significantly higher in the new work system compared to the traditional system. However, the job demand was significantly higher in the new work system than in the traditional system. The psychosocial distress was higher within the new work system than the traditional system, but no significant relationships were found. The proportion of increased strain was significantly greater with the new system than the traditional system. Conclusion : These results suggest that increases in the decision latitude did not sufficiently compensate for higher job strain or increased work intensity. If the increase in the decision latitude was temporary, with the typical job demand remaining high, such work can be still be considered to have a job strain Futureresearch should consider psychosocial distress and fatigue as importantproblems caused by new work organizational systems, and should be performed to assess their impact through out industry.

• Journal of Energy Engineering
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• v.11 no.2
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• pp.142-148
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• 2002

The variations of real time electric price in competitive electricity markets have influence on electric power demands of the consumers. Residential, commercial, and industrial consumers with different characteristics cause the different price elasticity of the demand due to changing the pattern of consumption. Therefore, this paper analyze the effects of spot pricing for the change of the electric power demand based on the demand elasticity of each loads in competitive electricity market.