• Journal of Korea Technology Innovation Society
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• v.14 no.4
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• pp.736-760
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• 2011

The importance of new renewable energy is emphasized not only new growth engine but also the key solution for the exhaustion problem of fossil energy and environment problem. For the steady growth of new renewable energy industry, securing related labor force is an essential factor. In this study, the status on labor force of new renewable energy industry was identified and forecasted the labor force demand of new renewable energy in 2015 by reflecting the industrial growth outlook on the new renewable energy. For the quantitative analysis methodology, the stock approach of Bureau of Labor Statistics (BLS) of the United States was applied. Also by performing survey on the experts, the opinions of experts on supply and demand of new renewable energy labor force or worker training programs have been gathered. As a result of study, it has been analyzed that nearly 20% annual growth rate will be shown as the labor force demand in the field of new renewable energy industry increases from 14,100 people in 2010 to 33,200 people in 2015. In the survey on experts, we could find that a plan for supplying labor force must be prepared promptly in order to accomplish new renewable energy supply objectives and industrial growth objectives by our country in the future as the supply of new renewable energy labor force is currently insufficient. Also, it has been analyzed that the effort for deciding the proper new renewable energy labor force training program standard will be necessary. This study result could be used as a material of labor force training plan for the steady growth of new renewable energy industry in the future.

• Journal of the Korean Solar Energy Society
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• v.39 no.5
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• pp.11-28
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• 2019

Governments are increasing energy efficiency in buildings through various policies to reduce building energy consumption. In 2002, the European Union adopted a building energy performance guideline to set minimum efficiency standards for residential and commercial buildings. Starting in 2020, all EU member states should ensure that all buildings are Near-Zero Energy Buildings (NZEB). In Korea, the government issued a zero-energy certification system. Since 2020, public buildings are required to cover energy consumption with the energy produced in buildings. As the demand for building energy simulation has increased to increase the energy efficiency of these buildings, the International Standard Organization (ISO) has created a standard for calculating building energy requirements called ISO 13790. This standard was revised to ISO 52016 in 2017. In this research, ISO 13790, which calculates the energy needs of existing buildings, and ISO 52016, which replaces them, are compared and analyzed, and applied to the calculation of heating energy needs of buildings. For models without thermal zoning(Case A), the difference in annual heating energy needs calculated from each criterion is $1.08kWh/m^2$, which is about 2% higher in ISO 52016. In the case of the thermal zoning model(Case B), the difference in annual heating energy needs calculated by each standard was $0.97kWh/m^2$, which was about 2% higher than ISO 52016. The heating energy needs model without thermal zoning has a higher energy needs than the heating energy needs model with thermal zoning. It is about 16% energy at $8.58kWh/m^2$ for ISO 13790 and $8.69kWh/m^2$ for ISO 52016.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2006.11a
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• pp.484-487
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• 2006

Today, the age of high oil prices is continued, due to the energy demand is on the increase and human principlal energy sorce, fossil fuel. As an alternative plan of energy saving, co-generation system that produces power and thermal energy at the same time has actively developed. In 1960s, co-generation system was introduced to Korea and since 2000 it has diffused throughout the apartment house. Therefore, objectives of this study are to analyze the energy reduction effects in the region 4 apartment houses of Daegu and Kyungbuk regionand set up a plan for its expansion in the future.

• KDI Journal of Economic Policy
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• v.41 no.1
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• pp.43-58
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• 2019

Since 2009, electricity consumption has developed a unique seasonal pattern in South Korea. Winter loads have sharply increased, and they eventually exceeded summer peaks. This trend reversal distinguishes these load patterns from those in the USA and the EU, where annual peaks are observed during the summer months. Using Levene's test, we show statistical evidence of a rise in temperature but a decrease in variance over time regardless of the season. Despite the overall increase in the temperature, regardless of the season there should be another cause of the increased demand for electricity in winter. With the present study using data from 1991 to 2012, we provide empirical evidence that relatively low electricity prices regulated by the government have contributed significantly to the rapid upward change in electricity consumption, specifically during the winter months in the commercial sector in Korea.

• Journal of the Korea Organic Resources Recycling Association
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• v.24 no.2
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• pp.31-39
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• 2016

Due to the temporal variation of inflow/outflow, the water tank is needed. For the calculation of water tank capacity, the absolute difference between cumulative amounts of supply(e.g., rainfall) and demand(e.g.,watering) is used. No matter the (-) and (+) the absolute maximum capacity of the subtraction is calculated as the capacity. In this paper, using rainfall and watering of greenhouse facilities, it is proved that the non-linear supply or demand can be applied, and it is proved also that the greater non-linear variation case. And as the time interval for monitoring is decreased, the basin or tank volume are increased, with approximately 10 days as the critical monitoring interval for the annual natural rainfall event.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.693-700
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• 2024

As of the end of March 2022, the total area of domestic industrial complexes is 606 km2, which is only about 0.6% of the total land area. However, as of 2018, the annual energy consumption of domestic industrial complexes is 110,866.1 thousand TOE, accounting for 53.5% of the country's total energy consumption and 83.1% of the entire industrial sector energy consumption. In addition, industrial complexes have a significant impact on the environment, accounting for 45.1% of the country's total greenhouse gas emissions and 76.8% of industrial sector greenhouse gas emissions. Under this background, in this study, in order to contribute to the energy efficiency of industrial complexes, a prediction study on energy demand and supply for an industrial complex in Korea using machine learning was conducted. In addition, a simulator UI screen was designed to more efficiently convey information on energy demand/supply prediction results and energy consumption status. Among the machine learning algorithms, Multi-Layer Perceptron (MLP) was used, and Bayesian Optimization was applied as an optimization technique for the prediction model. The energy prediction model for the industrial complex built in this study showed a prediction accuracy of 87.90% for compressed air demand and 99.54% for the flow rate available for the public air compressor.

• Journal of Energy Engineering
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• v.22 no.2
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• pp.211-225
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• 2013

To run an optimal operation of Integrated energy supply facilities, we need to analyze heat consumption patterns of District heating users and derive optimum and maximum load ratio of heat production facilities unit. This study selects three District heat production facilities. It also classifies District heating users into residential apartment buildings and eight non-residential buildings and analyzes heat consumption results for an year. Finally it carries out the analysis of how the ratio change of each type affects maximum load ratio, facility utilization ratio, heat supply range. According to this study, three different District heat facilities of residential apartment building show similar daily and annual heat consumption patterns. Annual average load ratio, maximum load ratio and annual heat demand increase as outdoor temperatures decrease. Non-residential buildings in urban District focused on apartment buildings display similar by the daily and annual heat consumption patterns. Yet their daily and annual maximum load ratio differ according to outdoor temperature, District, building types and their composition ratio. In the case of urban District focused on apartment buildings reach optimum and maximum load ratio when apartment buildings reaches 60-70% of the total. At that point heat supply range becomes maximized and the most economic efficiency is obtained.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.578-579
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• 2007

The importance and necessity of conducting studies on area outage cost assessment have been increasingly important in recent years due to the competitive electricity market environment. The objective of operational issues would be to minimize the total area cost while satisfying all associated system constrains of each area[2]. This paper presents a methodology of the Area annual outage cost assessment by probabilistic reliability evaluation using TRELSS program for KEPCO system. The interrupted energy assessment rate (IEAR) is evaluated by macro approach that is using relations between GRDP and the electrical energy demand. The Expected Energy Not Supplied (EENS) of each area was evaluated using the Transmission Reliability Evaluation for Large-Scale Systems (TRELSS) Version 6_2, a program developed by EPRI are introduced in this paper.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.11
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• pp.25-34
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• 2019

It is important to design windows in a reasonable way considering the performance characteristics of the elements of the window rather than just to increase the thermal energy performance of the window. In this study, the Heat-transfer Coefficient as insulation performance of the windows and together with the grade of the glass's SHGC (Solar Heat Gain Coefficient) were analyzed to relate to the energy efficiency performance of the building by azimuth angle. Based on this basic study, the Heat-transfer Coefficient of windows and the SHGC rating of glass were applied to the unit plan of apartment building, and the Heating and Cooling Demand were analyzed by azimuth angle. Apartment plan types were divided into 2 types of Non-extension and extension of balcony. The designPH analysis data derived from the variant of the Heat-transfer Coefficient and SHGC, were put into PHPP(Passive House Planning Package) to analyze precisely the energy efficiency(Heating and Cooling Demands) of the building by azimuth angle. In addition, assuming the 'ㅁ' shape layout, energy efficiency performance and potential of PV Panel installation also were analyzed by floors and azimuth angle, reflecting the shading effects by surrounding buildings. As the results of the study, the effect of Heat Gain by SHGC was greater than Heat Loss due to the Heat-transfer Coefficient. So it is more effective to increase SHGC to satisfy the same Heating Demand, and increasing SHGC made possible to design windows with low Heat-transfer Coefficient. It was also revealed that the difference in annual Heating and Cooling Demands between the low, mid and high floor households is significantly high. In addition to it, the installation of PV Panel in the form of a shading canopy over the window reduces the Cooling Load while at the same time producing electricity, and also confirmed that absolute thermal energy efficiency could not be maximized without controlling the thermal bridge and ventilation problems as important heat loss factors.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.12
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• pp.630-637
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• 2002

This paper proposed a new diffusion model considering DSM rebate program's support conditions. The proposed method used some aspects of the rebate program such as support qualifications, annual support volume, and support level per appliance as following : The support qualifications were limited as the consumer which can get the rebate program's benefit, the annual support volume was constrained as the fixing budget and the support level per appliance was considered by high-efficient appliance actuality price. This paper also proposed a new method that used neural network as its parameter estimation moth[,4 for the diffusion model. The diffusion model and its parameter estimation method are expected to be able to analyze the diffusion characteristics of high-efficient appliance through the rebate program and the effects of rebate program's support conditions. Also, these will be able to evaluate the impacts and to analyze the cost-effectiveness of Energy Efficiency Demand-Side Management(EEDSM) resources. The case study is performed on the high-efficient lighting appliance rebate program of Korea by using the suggested diffusion model and estimation method and thus verified its validity.