• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.23-26
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• 2017

Social Welfare is useful concept for evaluating the effectiveness of an economic policy in micro economics. This paper focuses on Social Welfare(SW) of electricity market incorporating demand response(DR). Competition between DR and generation company is modeled as a simple bid function. DR function can be considered as an negative generation(called Negawatt) and as an element of modified demand function. These two approaches result in the same demand reduction, generation power, and the market price. However, SW in the modified demand function approach is not identical to SW in the Negawatt approach. It makes the numerical index of DR effectiveness less persuasive. This paper proposes modified definition of SW in the demand function approach. The proposed definition of SW leads the DR effectiveness index to be identical to that in the Negawatt approach.

• KEPCO Journal on Electric Power and Energy
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• v.1 no.1
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• pp.67-71
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• 2015

The concept known as Vehicle-to-Grid (V2G) is to provide power to help balance loads by charging at night when demand is low and sending power to the grid when demand is high. Therefore, it is important to model the cost-benefit characteristics of Electric vehicle(EV)'s operation considering the negawatt market in real time. This paper proposes a methodology to formulate the various costs and economic benefits for sending the EV's power back to the grid, including a concept of inconvenience costs caused by operating the EV as a battery. This paper also introduces the general decision-making process based on the cost-benefit analysis in order to simulate the reasonable participation of V2G service. In the case study, it is confirmed by two-case simulations that the proposed approach is useful to help EV owners' decision-making. In the future, it is expected that the proposed methodology can be used as a decision-making guideline to help prepare the EV' power transmission.

• Journal of the Korea Convergence Society
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• v.8 no.1
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• pp.19-23
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• 2017

Energy is a vital resource for the economic growth and the social development for any country. As the industry becomes more sophisticated and the economy more grows, the electricity demand is increasing. So forecasting electricity demand is an important for electricity suppliers. Forecasting electricity demand makes it possible to distribute electricity demand. As the market for Negawatt market began to grow in Korea from 2014, the prediction of electricity consumption demand becomes more important. Moreover, power consumption forecasting provides a way for demand management to be directly or indirectly participated by consumers in the electricity market. We use Genetic Algorithms to predict the energy demand of the fishing industry in Jeju Island by using GDP, per capita gross national income, value add, and domestic electricity consumption from 1999 to 2011. Genetic Algorithm is useful for finding optimal solutions in various fields. In this paper, genetic algorithm finds optimal parameters. The objective is to find the optimal value of the coefficients used to predict the electricity demand and to minimize the error rate between the predicted value and the actual power consumption values.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.165-172
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• 2018

This paper presents a structure of the retail electricity market based on the local pool with LDERP(Local Distributed Energy Resource Provider) for small energy prosumers. LDERP is an operator for the proposed market, which conducts performance measurement and settlement by the distribution plan determined through contract with participants. The trading process is designed similarly to the negawatt market. In the case study, the many-sided conditions of the proposed market are comparatively analyzed with the existing prosumer programs. The results demonstrate the effectiveness of the proposed framework in determining the purpose of market operating for the benefit of participants according to the various situations.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.946-954
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• 2016

Energy industry is undergoing a paradigm shift in customer participation in the smartgrid. Customers traditionally consume electrical power. But nowadays not only do they generate electricity from private distributed generations, they can participate in demand response programs with their negawatt power which means a theoretical unit of power representing an amount of energy saved. Therefore development of decision-making criteria for electric load aggregation becomes a greater consideration as an amount of energy saved from demand response resources increases. This paper proposes load aggregators' decision-making criteria in the industrial sector where it made up the largest portion in demand response portfolio in order to assure reliability performance for demand response resources.