• KIEE International Transactions on Power Engineering
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• 제5A권4호
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• pp.403-411
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• 2005

At present, the Cournot model is one of the most commonly used theories to analyze the gaming situation in an oligopoly type market. However, several problems exist in the successful application of this model to the electricity market. The representative one is obtaining the inverse demand curve able to be induced from the relationship between market price and demand response. In the Cournot model, each player offers their generation quantity to obtain maximum profit, which is accomplished by reducing their quantity compared with available total capacity. As stated above, to obtain the probable Cournot equilibrium to reflect the real market situation, we have to induce the correct demand function first of all. Usually the correlation between price and demand appears over the long-term through statistical data analysis (for example, regression analysis) or by investigating consumer utility functions of several consumer groups classified as residential, industrial, and commercial. However, the elasticity has a tendency to change continuously according to the total market demand size or the level of market price. Therefore it should be updated as the trading period passes by. In this paper we propose a method for inducing and updating this price elasticity of demand function for more realistic market equilibrium.

• 전기학회논문지
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• 제64권9호
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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.

• International Journal of Precision Engineering and Manufacturing-Green Technology
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• 제5권5호
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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.

• 대한전기학회논문지:전력기술부문A
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• 제50권12호
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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 Electrical Engineering and Technology
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• 제13권1호
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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.

• 에너지공학
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• 제11권2호
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• pp.142-148
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• 2002

경쟁적인 전력시장에서 실시간 전력가격의 변화는 전력소비자들의 전력소비에 영향을 주게된다. 서로 다른 특성을 가지는 가정용, 상업용, 산업용 부하들은 전력소비 성향의 변화에 따라 서로 다른 가지 탄력성을 가진다. 따라서, 본 논문에서는 계산된 각 용도별 부하에 대한 수요 탄력성을 적용하여 경쟁 전력시장에서 수요 탄력성에 따른 전력수요의 변화가 현물가격에 미치는 영향을 분석한다.

• 대기
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• 제24권4호
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• pp.515-522
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• 2014

In this study it is attempted to estimate the possible change in energy use for residential and commercial sector in Korea under a future climate change senario. Based on the national energy use and observed temperature data during the period 1991~2010, the optimal base temperature for determining heating and cooling degree days (HDD and CDD) is calculated. Then, net changes in fossil fuel and electricity uses that are statistically linked with a temperature variation are quantified through regression analyses of HDD and CDD against the energy use. Finally, the future projection of energy use is estimated by applying the regression model and future temperature projections by the CMIP5 results under the RCP8.5 scenario. The results indicate that, overall, the net annual energy use will decrease mostly due to a large decrease in the fossil fuel use for heating. However, a clear seasonal contrast in energy use is anticipated in the electricity use; there will be an increase in a warm-season demand for cooling but a decrease in a cold-season demand for heating.

• 스마트미디어저널
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• 제8권4호
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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 Journal of Asian Finance, Economics and Business
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• 제8권10호
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• pp.269-283
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• 2021

The government policies and initiatives to guarantee sustainable energy and clean environmental conditions contributed to the introduction of green technology electricity appliances in the market. This study sought to determine the physiological and socio-economics-demographic factors driving residential electricity consumers to use green technology electricity appliances, mainly solar PV, smart meter, electric vehicle, and battery storage technology. By understanding consumer intention, the investors of solar PV, battery storage, electric vehicle, and smart meter can estimate the demand and upscale the market for the corresponding products. For that purpose, the intention to use the solar PV, smart meter, electric vehicle, and battery storage function is developed by utilizing the combination of the theory of planned behavior, technology acceptance, and reasoning action. A reliable and valid structured online questionnaire and stepwise multiple regression are used to identify the possible factors that drive consumer behavior intention. The results show that the social influence, knowledge on RE, and perceived price significantly influence residential consumers' willingness to adopt the technologies offered. The findings of this study suggest that the involvement of NGOs, public figures, and citizens' cooperation are all necessary to spread information about the government's objectives and support Malaysia's present energy and environmental policies.

• 자원ㆍ환경경제연구
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• 제27권2호
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• pp.287-313
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• 2018

본 연구는 전력수요의 냉방 및 난방 수요를 측정하고 분석한다. 이를 위해 냉난방기온효과를 추정하고 이를 Chang et al. (2014)의 전력수요함수 모형에 적용하여 전력수요를 기본수요, 냉방수요 그리고 난방수요로 분해하였다. 1999년 1월부터 2016년 12월의 한국의 일반용과 주택용 전력수요를 분석한 결과, 난방수요의 증가율이 기본수요와 냉방수요의 증가율을 월등히 상회하였으며 특히 일반용에서 난방수요 증가가 두드러졌다. 평년기온으로 통제한 기온보정된 난방수요는 실현된 난방수요보다 상대적으로 '더' 증가하였고, 냉방수요는 반대로 기온보정된 수요가 실현된 수요에 비해서 '덜' 증가하였다. 본 논문은 전력수요 내의 냉방 및 난방수요를 측정할 뿐 아니라 경제주체들의 전력수요 변화 패턴을 확인했다는 점에 의의가 있으며, 추정 결과들은 향후 전력수요예측과 에너지수요관리 정책 수립에 도움을 줄 수 있을 것으로 기대된다.