• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.254-259
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• 2006

It is increased electrical energy consumption with the development of intelligence society in the subway station and thus an energy conservation through efficient use of electricity became more important. This paper shows a reasonable design load density in subway stations, that was made by the systematic and statistical way considering actual conditions, such as investigated electric equipment capacity, peak power consumption, demand factor, etc., for 34 subway stations and 10 electrical design offices. In this dissertation, it is necessary to analyse the key features and general trend from the investigated data. It made an analysis of the feature parameters, such as average, standard deviation, median, maximum, maximum and thus it was carried linear and nonlinear regression analysis.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.161-171
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• 2019

Varied methods have been researched continuously because the past as the daily maximum electricity demand expectation has been a crucial task in the nation's electrical supply and demand. Forecasting the daily peak electricity demand accurately can prepare the daily operating program about the generating unit, and contribute the reduction of the consumption of the unnecessary energy source through efficient operating facilities. This method also has the advantage that can prepare anticipatively in the reserve margin reduced problem due to the power consumption superabundant by heating and air conditioning that can estimate the daily peak load. This paper researched a model that can forecast the next day's daily peak load when considering the influence of temperature and weekday, weekend, and holidays in the Seasonal ARIMA, TBATS, Seasonal Reg-ARIMA, and NNETAR model. The results of the forecasting performance test on the model of this paper for a Seasonal Reg-ARIMA model and NNETAR model that can consider the day of the week, and temperature showed better forecasting performance than a model that cannot consider these factors. The forecasting performance of the NNETAR model that utilized the artificial neural network was most outstanding.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.1
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• pp.49-67
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• 2014

This paper proposes a real time pricing model for smart grid considering consumers' behavior, real time price elasticity, and exogenous price. Based on the proposed model, we found the weight of utility over cost is the most sensitive factor compared to other factors. Also, if the electricity price is set to be changed too sensitively to energy consumption, it is warned that real time pricing sometimes can cause increment of peak-time demand and volatility. Finally, real time pricing could be less efficient when the difference between the maximum and the minimum consumption level is small.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.6
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• pp.85-90
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• 2014

This paper shows a reasonable demand power, that was made by the systematic and statistical way considering actual conditions, such as investigated transformer capacity and peak power for the last 6 years of subway substation customer as to AMR. In this dissertation, it is necessary to analyze the key features and general trend from the investigated data. It made an analysis of the feature parameters, such as average, standard deviation, median, maximum, minimum and thus it was carried by the linear and nonlinear regression analysis. And we studied on the application of a BESS. Analysis showed that the revulsion of capital is about 3 years and 4 months.

• Journal of Communications and Networks
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• v.14 no.6
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.10
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• pp.1508-1516
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• 2015

This paper proposes the optimal operation of ESS (Energy Storage System) in the substation of urban railway in an economical point of view. Since the load patterns of urban railway have different characteristics with the general power demand pattern, the characteristics motivate us to develop the optimal operation algorithm for ESS under Korean electricity billing system. We also introduce two different ESS operation strategies for peak load shaving and electricity consumption charge minimization respectively, and formulate each scheme. Historical data from Namgwangju substation are used for economical comparison of the strategies. The results show that the proposed algorithm is the most cost-effective ESS operation scheme among the strategies and reduces around 5 percent of electric charges compared to the charge without ESS operation.

• Journal of Environmental Science International
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• v.23 no.8
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• pp.1455-1462
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• 2014

The purpose of this study is to examine green consumer behavior (green product purchasing behavior and green consumption life) affected by demographical characteristics, and cognition degree of green life (cognition of a green indicator, a green life catalyst system, and environmental problems). It's also to promote strategy and suggest effective activation plans for the vitalization of green consumer behavior. To carry out the task, verification of credibility, multiple regression analysis, two-step cluster analysis, and multinomial logistic analysis were used. The results are as follows: First, the factors that effect green product purchasing behavior were gender, age, cognitive of a green indicator, carbon points system, electricity peak hour system, and seriousness of environmental damage due to lifestyle. Second, the factors that effect green lifestyle were gender, age, carbon grade indicator system, cognition of a green system, and the seriousness of environmental damage due to lifestyle. Third, the comparative group characteristic analysis showed low rates for careless green consumer behavior groups compared to the passive green consumer behavior groups in cognition of a green indicator, green system, and environmental problems. For active green consumer behavior groups, the analysis showed high rates in cognition of carbon grades, eco-labeling, electricity peak hour system, and environmental damage due to lifestyle. In order to encourage green consumer behavior, it's evident that cognition of a green indicator, a green life catalyst system, and environmental problems need to be improved through strategic education and continuous encouragement.

• Journal of Integrative Natural Science
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• v.15 no.2
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• pp.89-97
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• 2022

This paper presents the comprehensive feasibility study of solar mini-grid project located in Bajhang District, Sudur Paschim Province, Nepal. The study has been conducted with the aim of developing a suitable size solar mini-grid system to meet electricity demand of proposed settlements of the village people. The study forecasts that the estimated average daily peak power consumption of load is about 20kW and average daily energy demand of load is about 100-150kWh/day in the base year 2022. The shared ratio of productive end uses is about 25% of the total power consumption and about 27% of the total energy demand, which will be used for small business/income generation activities and required 45kWp size solar power generation mini-grid system. The estimated project cost for the proposed 45kW solar mini-grid system technology, including 3 years of operation & maintenance, as well as power distribution network up to end user's premises is about 0.24 million USD. It is concluded that 45kWp photovoltaic mini-grid is feasible for the location.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.49 no.3
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• pp.177-185
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• 2000

In this study, the characteristics of various electricity and high resistivity ash collection were measured at superimposed nanosecond pulse energization. The pulse was generated through the hydrogen thyratron. Superimposed pulse was nanosecond duration pulse that had fast pulse rising time 100[ns], short pulse width 500∼850[ns] and pulse fall time 400∼750[ns]. The results of this study are summarized as followings; Frist, compared with the DC ESP(electrostatic precipitator), superimposed pulse ESP could induce higher peak voltage, and had the about 30[%] reduction of ESP collection area and 50∼80[%] reduction of power consumption. showing the same efficiency. Second, enhancement factor H had 1.9∼3.6 with the increase of migration velocity.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.4
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• pp.265-272
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• 2011

The electrical load profiles of end-users must be analysed properly to introduce distributed generation system efficiently. In this study, numerical simulation for predicting a residential electrical load profile was developed to satisfy categorized electricity consumption range. We applied bottom-up approach to compose electrical load profile by using data from official reports and statistics. The electrical load profile produced from the simulation predicted peak times of public report accurately and agreed well with the standard residential electrical load profile of official reports within average error of 16.2%.