• International Journal of Precision Engineering and Manufacturing-Green Technology
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• v.5 no.5
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• pp.623-630
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• 2018

The renewable energy systems have been in the spotlight as an alternative for environmental issues. Therefore, the governmental policies are being implemented to spread of promote power generation system using renewable energy in various countries around the world. In addition, Korea has also developed a policy called the power trading contract which can profit from electricity produced from renewable power generation system through Korea Electric Power Corporation (KEPCO) and Korea Power Exchange (KPX). As a result, the power trading contracts can trade power after self-consuming in-house by using small-scale renewable power system for residential customers as well as electricity retailers. The power trading contracts applicable as a small-scale power system have a 'Net metering (NM)' and a 'Power Purchase Agreement (PPA)', and these two types of power trading contracts trade surplus power, but payment method of each power trading is different. The microgrid proposed in this paper is based on grid connected microgrid using Photovoltaic (PV) system and Energy Storage System (ESS), that supplied power to residential demand, we evaluate the operation cost of microgrid by power demand in each power trading contracts and propose the appropriate power trading contracts according to electricity demand.

• 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 Electrical Engineering and Technology
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• v.13 no.1
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• pp.11-19
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• 2018

With the development of smart grid technology, it has become a hotspot to increase benefits of both residential users and electric power companies through demand response technology and interactive technology. In this paper, the game theory is introduced to the interaction between residential users and an electric company, making a mutually beneficial situation for the two. This paper solves the problem of electricity pricing and load shifting in the interactive behavior by building the game-theoretic process, proposing the interaction strategy and doing the optimization. In the simulation results, the residential users decrease their cost by 11% mainly through shifting the thermal loads and the electric company improves its benefits by 5.6% though electricity pricing. Simulation analysis verifies the validity of the proposed method and shows great revenue for the economy of both sides.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.12
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• pp.568-574
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• 2001

The variations of real time electric power price in competitive electricity markets have influence on electric power demands of the consumers. The effects of the consumers for electric power price can be expressed the price elasticity coefficient of the power demand as a measurement. Residential, commercial, and industrial consumers with different characteristics cause the different price elasticity of the power demand due to changing the pattern of consumption. It is necessary that the effects of electric power demands as a function of elasticity coefficient for each loads should be analyzed in Korea which is processing deregulated electric market. Therefore, this paper calculate the elasticity coefficient of each loads and analysis the effects of electric power demands as a function of elasticity coefficient of inflexible and flexible consumers in competitive electricity market.

• Journal of the Korean housing association
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• v.23 no.6
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• pp.31-38
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• 2012

In this paper, we draws tendency of the electricity consumption in residential buildings according to inhabitants Composition types and the level of incomes. it is necessary to reduce energy cost and keep energy security through the electricity demand forecasting and management technology. Progressive social change such as increases of single household, the aging of society, increases in the income level will replace the existing residential electricity demand pattern. However, Only with conventional methods that using only the energy consumption per-unit area are based on Energy final consumption data can not respond to those social and environmental change. To develop electricity demand estimation model that can cope flexibly to changes in the social and environmental, In this paper researches propensity of electricity consumption according to the type of residents configuration, the level of income. First, we typed form of inhabitants in residential that existed in Korea. after that we calculated hourly electricity consumption for each type through National Time-Use Survey performed at the National Statistical Office with considering overlapping behavior. Household appliances and retention standards according to income level is also considered.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.189-210
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• 2022

Cities around the world have paid attention to public transportation as an alternative to reducing traffic congestion caused by automobile usage, excessive energy consumption, and environmental pollution. This study measures accessibility to subway stations in Seoul using a supply-demand-based accessibility technique. Then, the impacts were analyzed through land prices by use and segment. As a result of analysis using the multilevel hedonic price models, accessibility considering both supply and demand for the subway had a positive effect on both residential and non-residential land prices. The effect was stronger for residential than for non-residential. Further, among the accessibility measured by the three functions, the accessibility by the Exponential function was most suitable for the residential land price, and the accessibility measured by the Power function for the non-residential land price had the highest explanatory power. Also, looking at the impacts by land price segments, it was found that higher access to metro stations had the greatest positive impacts on the most expensive segment of residential and non-residential land prices. The results of this study can be applied not only to identify the impacts of public investment on neighborhoods, but also to support real estate valuation.

• Journal of Energy Engineering
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• v.11 no.2
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• pp.142-148
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• 2002

The variations of real time electric price in competitive electricity markets have influence on electric power demands of the consumers. Residential, commercial, and industrial consumers with different characteristics cause the different price elasticity of the demand due to changing the pattern of consumption. Therefore, this paper analyze the effects of spot pricing for the change of the electric power demand based on the demand elasticity of each loads in competitive electricity market.

• 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.

• Smart Media Journal
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• v.8 no.4
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• pp.72-79
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• 2019

The automated demand response (DR) program encourages consumers to participate in grid operation by reducing power consumption or deferring electricity usage at peak time automatically. However, successful deployment of the automated DR program sphere needs careful assessment of appliances load profile (ALP). To this end, the recent method estimates frequency, consistency, and peak time consumption parameters of the daily ALP to compute their potential score to be involved in the DR event. Nonetheless, as the daily ALP is subject to varying with respect to the DR time ALP, the existing method could lead to an inappropriate estimation; in such a case, inappropriate appliances would be selected at the automated DR operation that effected a consumer comfort level. To address this challenge, we propose a more proper method, in which all the three parameters are calculated using ALP that overlaps with DR time, not the total daily profile. Furthermore, evaluation of our method using two public residential electricity consumption data sets, i.e., REDD and REFIT, shows that our energy management systems (EMS) could properly match a DR target. A more optimal selection of appliances for the DR event achieves a power consumption decreasing target with minimum comfort level reduction. We believe that our approach could prevent the loss of both utility and consumers. It helps the successful automated DR deployment by maintaining the consumers' willingness to participate in the program.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1276-1280
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• 2015

Among the various statistical factors for South Korea, the population has been steadily decreased by lower birthrate. Nevertheless, the number of household is constantly increasing amid population aging and single life style. In general, residential electricity use is more the result of the number of household than the population. Therefore, residential electricity consumption is expected to be far higher for decades to come. The existing long-term load forecasting, however, do not necessarily reflect the growth of single and two-member households. In this respect, this paper proposes the long-term load forecasting for residential users considering the effect of changes of the housing type, and in the case study the changes of the residential load pattern is analyzed for accurate long-term load forecasting.