• 가정과삶의질연구
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• 제20권6호
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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.

• 대한토목학회논문집
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• 제38권6호
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• pp.933-940
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• 2018

본 연구에서는 전기자동차 수요에 대해 가구의 유형 및 차량 보유별로 그룹을 분류하고 개인의 특성과 가구차량보유구조 및 구매의향이 있는 경우 등에 따른 차량 구매 선택요인을 찾고자 한다. 이를 위하여 시행한 설문조사 결과를 토대로 수요예측모형을 구축하고 탄력성을 분석 하였다. 주요 결과는 다음과 같다. 첫째, 개인특성인 연령은 증가할수록 전기자동차 구매의향이 높아졌으나 성별은 구매에 있어서 유의미함을 찾아보기 어려웠다. 주택유형 또한 아파트의 경우만 유의미한 결과가 나타났다. 둘째, 차량이 있는 가구의 경우 전기자동차 구입의 중요 요인으로는 연료비와 충전시간, 주행가능거리 등과 같은 실제 사용에 있어 편의성과 관련된 요인이 탄력성이 높은 것으로 나타났다. 셋째, 차량이 없는 가구의 경우에는 차량구매가격이 탄력성이 높은 것으로 분석되었다. 본 연구에서 도출된 연구결과는 향후 전기자동차 수요예측과 보급활성화를 위한 기초적인 자료로 활용될 수 있을 것이라 판단된다.

• Journal of Electrical Engineering and Technology
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• 제12권5호
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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).

• 대한토목학회논문집
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• 제36권4호
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• pp.667-675
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• 2016

본 연구는 향후 교통수요관리를 위한 기초 자료로 활용하고자 가구별 차량보유패턴 및 보유구조를 분석하였다. 차량등록대수와 가구당 차량보유대수가 증가하는 현시점에 가구별 차량보유실태를 통해 보유패턴에 대해 알아 볼 필요가 있다. 또한 차량 증가 원인에 대해 분석 할 필요가 있을 것이다. 가구통행실태 조사의 결과를 바탕으로 승용차를 보유하고 있는 가구와 승용차 및 비승용차 보유하는 가구로 구분하여 연구를 진행하였고 주요 결과는 다음과 같다. 차량보유구조 패턴을 통해 가구당 차량보유대수가 2대 이하인 경우에는 승용차만을 보유하는 가구수가 많았으며 3대 이상의 경우 승용차만 보유하는 가구보다 비승용차와 함께 보유하는 가구 비율이 증가한다는 것을 알 수 있었다. 순서형 로짓 모형을 활용하여 가구별 차량 보유구조를 분석한 결과 가구 속성 자료 및 주거형태 변수에 따라 차량보유에 영향을 주는 요인들이 차이가 있는 것으로 나타났다.

• 가정과삶의질연구
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• 제33권1호
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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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• 제24권4호
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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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• 제8권6호
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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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• 제9권2호
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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.

• 대한교통학회지
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• 제7권1호
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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.

• 환경영향평가
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• 제25권1호
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• pp.1-14
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• 2016

고속도로 망의 지속적인 확장과 교통량 증대로 인해 고속도로에 인접하여 서식하는 야생동물의 생활권은 축소되거나 단절된다. 이는 먹이를 찾거나 번식지로 이동하는 야생동물들의 교통사고 가능성을 높인다. 야생동물 교통사고는 운전자의 안전 및 도로 시설의 위험 요소일 뿐만 아니라 야생동물 자체의 생명에도 위협이 된다. 야생동물의 서식지 분절을 막기 위한 다양한 방법 중 생태통로와 야생동물 유도 울타리가 대표적이다. 이러한 야생동물 교통사고 예방사업의 시설 설치비용은 명확하게 측정되지만, 편익의 경제적 가치를 측정하기는 어렵다. 본 연구에서는 조건부가치측정법을 사용하여 고속도로 상의 야생동물 교통사고 예방사업의 경제적 가치를 추정하였다. 추정결과에 따르면, 우리나라 전체 가구의 약 43.88%가 이 사업에 대한 양(+)의 지불의사를 가진 것으로 나타났다. 이와 더불어 환경문제의 인식이나 동 사업에 대한 사전 인지 정도가 높을수록 지불의사 확률과 지불의사액이 높아지는 것이 확인되었다. 따라서 해당 사업에 대한 적극적인 홍보는 야생동물 교통사고 예방사업에 긍정적인 여론을 형성하고, 동 사업에 양(+)의 금액을 지불할 의사가 있는 가구를 늘리는 데 기여할 수 있을 것으로 보인다.