• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.6 no.6
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• pp.42-48
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• 1992

This paper shows a reasonable design standard of substation facility density and demand factor in office buildings, that was made by the systematic and statistical way considering actual conditions, such as investigated electric equipment capacity, electric power consumption, etc for 121 buildings. The saving of electric equipment investment, the decrease of power loss, the improvement of facilities utilization and the decrease of electric power rates an be contributed by the application of the design standard must be applied by the revision of current regulations and laws.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.6 no.1
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• pp.29-39
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• 1992

In this paper, the basic idea of optimum electric system design by means of the forecasting of maximum demand is presented, and the load characteristics and practical operating conditions are based on the technical data. After reconstruction of th model plant by use of above method, power supply reliability, future extention, initial cost, and running cost saving effects are analyzed. As a result, it is verified that the systems wherein the power is supply to each load frm main transformer whose capacity is calculated by forecasting are economic rather than the systems wherein the power is supply to each electric feeders from each corresponding transformer.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.3
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• pp.183-187
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• 2016

Recently, power demand has been increasing every year according to variation of electrical equipments and temperature rise in summer season. So, much more overhead line is being demanded to copy with increasing power demand and operate reliable power system. This paper analysis the characteristics of long span overhead transmission line using special high-tension wire in such as a safety factor, coefficient of elasticity, and the coefficient of linear expansion. Based on the analysis, we proposed the effectiveness of special high-tension wire having much more advantages with respect to height of steel tower and dip compared with conventional ACSR in long span overhead transmission line.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2136-2141
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• 2009

Transmission planning is an important part of power system planning to meet an increasing demand for electricity. The objective of transmission expansion is to minimize operational and construction costs subject to system constraints. There is inherent uncertainty in transmission planning due to errors in forecasted demand and fuel costs. Therefore, transmission planning process is not reliable if the uncertainty is not taken into account. The paper presents a systematic method to find the optimal location and amount of transmission expansion using Cross-Entropy (CE) incorporating uncertainties about future power system conditions. Numerical results are presented to demonstrate the performance of the proposed method.

• Transactions of the Korean hydrogen and new energy society
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• v.34 no.3
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• pp.246-255
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• 2023

Due to lack of hydrogen charging stations and hydrogen supply compared to the supply of hydrogen vehicles, social phenomena such as 2-hour queues and restrictions on charging capacity are occurring, which negatively affects the spread of hydrogen vehicles. In order to resolve these problems, it is essential to have a strategic operation of the hydrogen charging stations. To establish operational strategies, it is necessary to derive customer demand patterns and characteristics through the analysis of sales data. This study derived the demand patterns and characteristics of customers visiting hydrogen charging stations through data analysis from various perspectives, such as charging volume, charging speed, number of visits, and correlation with external factors, based on the hydrogen sales data of off-site hydrogen charging stations located in domestic residential areas.

• International Journal of Advanced Culture Technology
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• v.4 no.1
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• pp.1-9
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• 2016

The demand for energy in Thailand has been continually increasing as the economic and social country grows. Approximately 60% of Thailand's primary energy is imported, mostly petroleum products. In 2008 Thailand's total energy consumption was 80,971 ktoe and the net price of energy imported was up to 1,161 billion Baht which is equivalent to 12.8% of GDP at the current price. The energy consumption or energy demand has been growing at an annual compounded growth rate of 6.42% and the peak electric power demand and electricity consumption was recorded at 22,568 MW and 148,264 GWh and grew at a rate of 7.0% and 7.5% per annum during the period from 1989 to 2008. The gross agriculture production in 2008 was recorded at 135.4 Mt which represents agriculture residue for energy at 65.73 Mt, which is equivalent to energy potential of about 561.64 PJ or 13,292 ktoe an increase in average of 5.59% and 5.44% per year respectively. The agricultural residues can converted to 15,600 GWh/year or 1,780 MW of power capacity. So, if government sector plan to install small biomass gasification for electricity generation 200 kW for Community. The residue agricultural is available for 8,900 plants nationwide. The small biomass power generation for electricity generation not only to reduce the energy imports, it also makes the job and income for people in rural areas as well. This paper's aim is to report the energy situation in Thailand and has studied 5 main agricultural products with high residue energy potential namely sugarcane, paddy, oil palm, cassava, and maize appropriate for small electricity production. These agricultural products can be found planted in many rural areas throughout Thailand. Finally, discuss the situation, methods and policies which the government uses to promote small private power producers supplying electricity into the grid.

• Environmental and Resource Economics Review
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• v.28 no.1
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• pp.147-176
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• 2019

This paper uses research on the Levelized Cost of Electricity (LCOE) in South Korea to conduct a simulation analysis on the impact of nuclear power dependency and usage rates on the social costs of power generation. We compare the $7^{th}$ basic plan for long-term electricity supply and demand, which was designed to increase nuclear power generation, to the $8^{th}$ basic plan for long-term electricity supply and demand that decreased nuclear power generation and increased renewable energy generation in order to estimate changes in social costs and electricity rates according to the power generation mix. Our environmental generation mix simulation results indicate that social costs may increase by 22% within 10 years while direct generation cost and electricity rates based on generation and other production costs may increase by as much as 22% and 18%, respectively. Thus we confirm that the power generation mix from the $8^{th}$ basic plan for long-term electricity supply and demand compared to the $7^{th}$ plan increases social costs of generation, which include environmental external costs.

• Environmental and Resource Economics Review
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• v.31 no.4
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• pp.865-885
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• 2022

Korean government updated her Nationally Determined Contribution (NDC) in 2021 and announced the target and various measures for reductions. Among the many issues, final energy demand and renewable energy power mix for 17 provinces to achieve the target are being analyzed using GCAM-Korea. Simulation results show that final energy demand of 2030 is approximated at the similar level to that of 2018. This is being enabled by the conservation of coal with higher electrification especially in industry sector. Higher power demand with lower coal consumption in final energy consumption is shown to be provided by 33.1% of renewable, 24.6% of gas, and 18.0% of nuclear power generation in 2030. Meanwhile, the share of coal-fired power generation is expected to be reduced to 12.8%. Major future power provider becomes Gyeongbuk (Nuclear), Gyeonggi (Gas), Jeonnam (Nuclear, Gas) and Gangwon (PV, Wind), compared to one of current major power provider Chungnam (Coal). This analysis is expected to provide a useful insight toward the national and provincial energy and climate change policy.

• Journal of the Society of Disaster Information
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• v.18 no.3
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• pp.532-541
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• 2022

Purpose: The purpose of this study is to suggest that the existing power demand prediction method including power demand according to fine dust is included in the existing power consumption by using an air purifier to improve the air quality due to fine dust. Method: The method of the study was compared and analyzed using data on the concentration of fine dust in Seoul for three years, household power consumption, and climate observation, and the effect of fine dust on power consumption in Seoul was identified in April and October. Result: The power consumption of home air purifiers in Seoul due to fine dust differences between April and October was calculated to be 2,141 MWh, accounting for 3.4% of the total difference in the use of home appliances in April and October. Conclusion: The effect of fine dust on household power consumption was verified, and power demand prediction is essential for economic system operation and stable power supply, so power consumption due to fine dust should be considered as well as focusing on power consumption of existing air conditioners and heaters.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.59-65
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• 2021

Electricity contributes to the development of the economy. Therefore, forecasting electricity demand plays an important role in the development of the electricity industry in particular and the economy in general. This study aims to provide a precise model for long-term electricity demand forecast in the residential sector by using three independent variables include: Population, Electricity price, Average annual income per capita; and the dependent variable is yearly electricity consumption. Based on the support of Multiple variable regression, the proposed method established a model with variables that relate to the forecast by ignoring variables that do not affect lead to forecasting errors. The proposed forecasting model was validated using historical data from Vietnam in the period 2013 and 2020. To illustrate the application of the proposed methodology, we presents a five-year demand forecast for the residential sector in Vietnam. When demand forecasts are performed using the predicted variables, the R square value measures model fit is up to 99.6% and overall accuracy (MAPE) of around 0.92% is obtained over the period 2018-2020. The proposed model indicates the population's impact on total national electricity demand.