• Journal of Families and Better Life
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• v.20 no.6
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• pp.81-93
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• 2002

The purpose of this study is to analyze the effects of household income drops on household economic status during economic crisis periods. Using the data taken from Korean Household Panel Study for 1996 and 1998, it was investigated how household income change affected household income, expenditure, and assets/debt. The economic status change of the income-decreased group was compared with that of the income-increased group. The major findings were as follows: Average income of the total sample was 1,905 thousand won in 1996, while 1,419 thousand won in 1998. The household of which income was decreased during the period was 65.1% of total sample. Average income of the group was reduced from 2,263 thousand won to 1,239 thousand won. Among income sources, the amount of income from real asset was found to be the highest decreasing rate, and the amounts of both business and employed-work income were reduced almost up to an half of those in two years ago. The amounts for all expenditure categories were also decreased with decreasing household income. Especially the expenditures for food away from home, leisure, durable, recreation, and vehicle-related expense were found to have the highest income elasticity. The households with decreased income were found to reduce household expenditures by 377 thousand won per month, which was 70.9% of that in 1996. Decreases in household income resulted in decreases in net wealth by 10,170 thousand won. With decreases in household income, the amounts of total insurance and private savings such as gye were decreased, and so were the amounts of real assets and monetary assets.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.933-940
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• 2018

The conversion of the internal combustion engine vehicle to the electric vehicle is suggested as a solution to the problem of global climate change and environmental pollution. Accordingly, this study was started to promote the use of electric vehicles. The purpose of this study is to identify the basic background knowledge and current status of electric vehicles in Korea and abroad, and expand from previous understanding on which factors affect ones choice on electric vehicles by considering individual characteristics and context in detail. In the analysis, a set of demand forecasting models were constructed by grouping the respondents based on the household characteristics as well as the vehicle ownership. At the time in need for better understanding of the feasibility of electric vehicles, it is expected that the research can assist the promotion of electric vehicles. In the follow-up study, I would like to continue the research on the activation of electric vehicles.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1789-1797
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• 2017

It is necessary to charge electric vehicles in order to drive them. Thus, it is essential to have electric vehicle charging facilities in place. In the case of a household battery charger, the power similar to that consumed by a household with a basic contract power of 3kW is consumed. In addition, many consumers who own an electric vehicle will charge their vehicles at the same time. The simultaneous charging of electric vehicles will cause the load to increase, which then will lead to the imbalance of supply and demand in the distribution system. Thus, a smart charging scheme for electric vehicles is an essential element. In this paper, simulated conditions were set up using real data relating to Korea in order to design a smart charging technique suitable for the actual situation. The simulated conditions were used to present a smart charging technique for electric vehicles that disperses electric vehicles being charged simultaneously. The EVs and Smart Charging Technique are modeled using the Electro Magnetic Transients Program (EMTP).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.4
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• pp.667-675
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• 2016

The goal of this study is to be used as baseline data for transportation demand management. At the present time the number of registered car and householding car is increasing, so there is a need to analyze the car ownership pattern through household car hold status. Also, it is necessary to analyze the factor of increasing car. The research is proceeded with classifying as the household which is holding private cars or holding passenger cars and non passenger cars based on the result of the research of the household travel survey data. The result of this study is shown as follows. According to car ownership pattern, there are more households holding passenger cars only when they are holding less than 2 cars. Otherwise there are more households holding passenger car and non passenger car when they are holding more than 3 cars. Using the Ordered Logit Model, there are more differences in factors affects holding cars by variables of housing type and household properties.

• Journal of Families and Better Life
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• v.33 no.1
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• pp.19-39
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• 2015

The purpose of the study was to examine the characteristics and economic status of deficit households. The data for this study were from The Household Income and Expenditure Survey in 2000, 2005, and 2010 conducted by the National Statistics Office (NSO). Deficit households were defined by those who had expenditures higher than their income. Among total households, the proportion of deficit households was 26.84% in 2000, 28.14% in 2005, and 27.15% in 2010. The average propensity to consume was 132.1 in 2005, which was higher than those in 2000 and 2010. Deficit households were classified into five types using cluster analysis: 1)overall-overconsumption group(33.07%), 2)basic needs group(26.33%), 3)transportation expenditure-dominated group(6.73%), 4)education expenditure-dominated group(27.63%), 5)health care expenditure-dominated group(6.24%). The overall-overconsumption group was the largest group of total households and the portion of this group among total households decreased by 4.97%p from 2005 to 2010. However, the education expenditure-dominated group increased by approximately 7.6%p over the period. It was also found that households in 2000 and 2010 were more likely to be in all five groups than households in 2005. Other major determinants of households with deficit were gender, age, number of family members, education level, dual income, home ownership, vehicle ownership, and income class.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.87-106
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• 2024

Vehicle-to-Home (V2H) and Home Centralized Photovoltaic (HCPV) systems can address various energy storage issues and enhance demand response programs. Renewable energy, such as solar energy and wind turbines, address the energy gap. However, no energy management system is currently available to regulate the uncertainty of renewable energy sources, electric vehicles, and appliance consumption within a smart microgrid. Therefore, this study investigated the impact of solar photovoltaic (PV) panels, electric vehicles, and Micro-Grid (MG) storage on maximum solar radiation hours. Several Deep Learning (DL) algorithms were applied to account for the uncertainty. Moreover, a Reinforcement Learning HCPV (RL-HCPV) algorithm was created for efficient real-time energy scheduling decisions. The proposed algorithm managed the energy demand between PV solar energy generation and vehicle energy storage. RL-HCPV was modeled according to several constraints to meet household electricity demands in sunny and cloudy weather. Simulations demonstrated how the proposed RL-HCPV system could efficiently handle the demand response and how V2H can help to smooth the appliance load profile and reduce power consumption costs with sustainable power generation. The results demonstrated the advantages of utilizing RL and V2H as potential storage technology for smart buildings.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1276-1282
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• 2013

This paper proposes a stochastic modeling of plug-in electric vehicles (PEVs) distribution in power systems, and analyzes the corresponding clustering characteristic. It is essential for power utilities to estimate the PEV charging demand as the penetration level of PEV is expected to increase rapidly in the near future. Although the distribution of PEVs in power systems is the primary factor for estimating the PEV charging demand, the data currently available are statistics related to fuel-driven vehicles and to existing electric demands in power systems. In this paper, we calculate the number of households using electricity at individual ending buses of a power system based on the electric demands. Then, we estimate the number of PEVs per household using the probability density function of PEVs derived from the given statistics about fuel-driven vehicles. Finally, we present the clustering characteristic of the PEV distribution via case studies employing the test systems.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.1-10
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• 2017

The high costs of electric vehicle supply equipment (EVSE) and installation are currently a stumbling block to the proliferation of electric vehicles (EVs). The cost-effective solutions are needed to support the expansion of charging infrastructure. In this paper, we develope EV charging system based on the big data analysis of the power consumption patterns. The developed EV charging system is consisted of the smart EV outlet, gateways, powergates, the big data management system, and mobile applications. The smart EV outlet is designed to low costs of equipment and installation by replacing the existing 220V outlet. We can connect the smart EV outlet to household appliances. Z-wave technology is used in the smart EV outlet to provide the EV power usage to users using Apps. The smart EV outlet provides 220V EV charging and therefore, we can restore vehicle driving range during overnight and work hours.

• Journal of Korean Society of Transportation
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• v.7 no.1
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• pp.19-34
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• 1989

In general, Shopping centers are located in the center of transportation, which induce more traffic concentration than other facilities. As a result, it becomes to one of the aggravating factors of urban ＆ transportation problem such as traffic conjestion, parking problems. Thus, in planning shopping-center, it is desirable that consumer\`s trip pattern is should lie more carefully analyzed in order to alleviate the above problems. This study is aimed at finding the characteristics of shopping tripes and analyzing the choice behavior of shopping center and mode-to-shop. This study has developed a nested logit model in which consumers choose shopping center and mode-to-shop with a sequential structure. The model was estimated using household data from the 1989 May, Seoul metropolitan area and the 18 alternatives of shopping center and 5 mode alternatives. The estimated model have been evaluated and it may be concluded that this model for shopping trips is effective and fesible. The conclusion of this study are as fellows. 1. Out-of-vehicle travel time is more important factor affecting behavior of mode choice than in-vehicle travel time. 2. All of direct-elasticities for mode with respect to the travel time is more elastic than travel cost. 3. Accessibility to shop is more important factor affecting the choice of shopping center than parking space. 4. The value of out-of-vehicle travel time exceeds the value of in-vesicle travel time by 1.64 times.

• Journal of Environmental Impact Assessment
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• v.25 no.1
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• pp.1-14
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• 2016

With the continuous expansion of highway network and its traffics, neighboring wildlife habitats are splitted into smaller and more isolated patches. The infrastructures contribute to the wildlife-vehicle collision by creating barriers to animal movement. This kinds of traffic accidents are dangerous factors to the drivers' safety and the facilities on the highway as well as to the wildlife themselves. One of the most common ways to prevent habitat fragmentation are fauna crossings and fences. The cost of the mitigation measures to prevent wildlife-vehicle collision could be monetized. However their economic benefits are difficult to be measured. Using contingent valuation method, this study tries to estimate the economic valuation of wildlife collision prevention projects on the Korean highways. The result shows that 43.88% of Korean household had the positive willingness pay to the projects. Moreover, we found that the recognition of the project or the favourable attitude to the environmental issues could raise the willingness-to-pay. Therefore, active public relation on the project could make the friendly public opinion and increase the number of the household which has the positive willingness-to-pay on the project.