• Journal of the Optical Society of Korea
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• v.17 no.5
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• pp.376-383
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• 2013

The design of the LEDs lighting in general household illumination was proposed and compared with the fluorescent lighting in this study. Using the LED as a light source would promote energy saving lighting for household illumination purposes. We used the LightTools and DIALux software to design and simulate different standards of illuminance, different correlated color temperatures and different color rendering indices for household environments. The power consumption and efficiency of traditional illuminated light sources and an LED light source with the same standard of illuminance for lighting the household environment were analyzed and compared with each other. Finally, our results show the advantages of using white-light LEDs for lighting and household illumination.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.5
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• pp.459-466
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• 2004

In order to save the energy in apartment houses, it is essential that the energy amount consumed in heating per household should be surveyed and analyzed according to heating method, which can be classified into unit, central and district methods. As a basis, we selected the household with nominal area of 32 py. because it accounts for the most percentage in Korea. It is estimated that the gas amount for cooking is 90 ㎥ and the energy amount for hot water supply is 11.41 GJ for a year, which is necessary to calculate the heating energy. Through the survey of actual energy consumption in Seoul and Gyeonggi, the energy amount used in heating can be obtained according to the heating type: 26.02 GJ/year for the unit heating, 28.09 GJ/year for the central heating and 40.61 GJ/year for the district heating.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.687-691
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• 2001

With today's global environmental and energy problems, high expectations exist for solar power generation to reduce carbon dioxide generated by the consumption of fossil fuels. On the other hand, power consumption in residential homes is increasing every year. Among the many household appliances, the power demand for air conditioners increases dramatically during the summer, particularly in the afternoons. As this pattern closely matches the output pattern of solar cells, it should be possible to combine a photovoltaic array with an air conditioner to decrease the energy consumption within the home. We have developed a residential solar-powered air conditioner that operates through a combination of photovoltaic array and commercial power. In this paper, the configuration and specification of the residential solar-powered system are described to a novel high efficiency inverter using a ZVCS boost converter. And the performance evaluations of the solar-powered air conditioner are examined by the analysis of a new tracking controller with a maximum power $P_{max}$ detection of solar cell.

• Journal of Korea Planning Association
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• v.54 no.5
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• pp.129-138
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• 2019

This study aims to empirically examine the relationship between building energy consumption and building and local factors in Seoul. Building energy issue is an important topic for low carbon and eco-friendly city development. Building physical, socio-economic and environmental factors effect to increasing or decreasing energy consumption. However, there are different characteristic in each area, and this kind of variable has a hierarchical structure. The multi-level model was used to consider the hierarchical structure of the variables. In this study, a multi-level model was applied to confirm the difference between areas. Spatial area is Seoul, Korea and the temporal scope is August, summer season. As the result, in Model 1 (Null Model), ICC is 0.817. This shows that the energy consumption differs by 8.174% due to factors at the Dong level. Model 2 (Random Intercept Model) suggests that building's physical factors and Average age, Household size and Land price in Dong level have significant effects on Building energy consumption. In Model 3 (Random Coefficient Model), random effect variables have intercepts and slopes to vary across groups. This study provides a perspective for policy makers that the building energy reduction policies to be applied for buildings should be differently applied on area. Furthermore, not only physical factors but also socio-economic and environmental factors are important when making energy reduction policy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2377-2398
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• 2021

In the recent modernized world, utilization of natural resources (renewable & non-renewable) is increasing drastically due to the sophisticated life style of the people. The over-consumption of non-renewable resources causes pollution which leads to global warming. Consequently, government agencies have been taking several initiatives to control the over-consumption of non-renewable natural resources and encourage the production of renewable energy resources. In this regard, we introduce an IoT powered integrated framework called as green home architecture (GHA) for green score calculation based on the usage of natural resources for household purpose. Green score is a credit point (i.e.,10 pts) of a family which can be calculated once in a month based on the utilization of energy, production of renewable energy and pollution caused. The green score can be improved by reducing the consumption of energy, generation of renewable energy and preventing the pollution. The main objective of GHA is to monitor the day-to-day usage of resources and calculate the green score using the proposed green score algorithm. This algorithm gives positive credits for economic consumption of resources and production of renewable energy and also it gives negative credits for pollution caused. Here, we recommend a green score based tax calculation system which gives tax exemption based on the green score value. This direct beneficiary model will appreciate and encourage the citizens to consume fewer natural resources and prevent pollution. Rather than simply giving subsidy, this proposed system allows monitoring the subsidy scheme periodically and encourages the proper working system with tax exemption rewards. Also, our GHA will be used to monitor all the household appliances, vehicles, wind mills, electricity meter, water re-treatment plant, pollution level to read the consumption/production in appropriate units by using the suitable sensors. These values will be stored in mass storage platform like cloud for the calculation of green score and also employed for billing purpose by the government agencies. This integrated platform can replace the manual billing and directly benefits the government.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.1
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• pp.72-81
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• 2014

Recently, because of irregular power demand, we have suffered from an electric power shortage. The necessity of the adoption of smart grid which makes effective supply of power by using the two-way communication across the grid between the customers and electric energy providers is growing more and more. If smart grid set up in our country, the third-parties which provide services to customer using the information acquired from smart grid, might be revved up. In this paper, we suggest a methodology how classify the types of family by analysing an power consumption pattern using data mining technique. To make a classifier for categorizing the household types, we need power consumption data and their family type. However, it is hard to get both of them. Therefore we develop the simulator that generates power consumption patterns of the household and classify the types of family. Also, we present a potential for application services such as customized services for a specific family or goods marketing.

• Environmental and Resource Economics Review
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• v.16 no.2
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• pp.275-311
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• 2007

Hydrogen energy is emphasized as a substitutable energy of carbon-based energy system in the future, since it is non-depletable and clean energy. Long term vision of Korean government on the national energy system is to promote hydrogen energy by 15% of final energy demand until 2040. This study analyzes economic impacts of hydrogen energy development employing a dynamic CGE model for Korea. Frontier technology such as hydrogen energy is featured as slow diffusion at the initial stage due to the learning effect and energy complementarity. Without government intervention, hydrogen energy would be produced upto 6.5% of final energy demand until 2040. However, if government subsidizes sales price of hydrogen energy by 10%, 20%, and 30%, share of hydrogen energy would increase 9.2%, 15.2%, and 37.7% of final energy demand. This result shows that the slow diffusion problem of hydrogen energy as frontier technology could be figured out by market incentive policy. On the other hand, production levels of transportation sector would increase while growth rate of oil and electricity sectors would decline. Household consumption would be affected negatively since increase of consumption due to the price decrease would be overwhelmed by income reduction owing to the increase of tax. Overall, GDP would not decrease or increase significantly since total production, investment, and export would increase even if household consumption declines.

• Journal of Environmental Policy
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• v.13 no.2
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• pp.99-129
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• 2014

This research estimates the impact of population aging on energy use and carbon emissions by energy sources and by industrial sectors in Korea until 2035. For the estimation, the structural change in household consumption expenditure identified by the age-specific consumption pattern was analyzed in conjunction with energy and environment input-output tables. The estimation result presents that, despite the population aging, energy use and carbon emissions induced by household consumption continue to increase until 2026, and then that elevated levels of energy use and carbon emissions will be maintained for a considerable period of time. According to the estimation by energy sources, the use of natural gas will show substantial increase while the use of crude oil will switch to a downturn at a relatively early period. According to the estimation by industrial sectors, carbon emissions in the sectors with relatively high consumption share of old households such as medical health, dwelling, lighting, heating, air-conditioning, and food will have substantial increase, whereas those in the sectors associated with education, transport, catering, and accommodation services will turn downward relatively early. In addition, the study analyzes through policy simulation the impact of aging-related policy similar to the basic pension system, which is recently being discussed for legislation, on energy use and carbon emissions.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.813-818
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• 2008

In order to reduce energy consumption, this study presents a way to energy reduction through energy-feedback which enables a household to self-recognize the need for energy reduction and respond to. The effect of this energy-feedback has been reported as $10{\sim}15%$ in average, and been actively investigated in abroad from 1970's while study in korea has been in its first step. In this study, examination on the cases of abroad study is made as it shows the effectiveness and applicability of energy feedback. And paradigms to consider for application to korea will be suggested anticipating the change of actions through energy feedback.

• 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.