• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.1
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• pp.49-67
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• 2014

This paper proposes a real time pricing model for smart grid considering consumers' behavior, real time price elasticity, and exogenous price. Based on the proposed model, we found the weight of utility over cost is the most sensitive factor compared to other factors. Also, if the electricity price is set to be changed too sensitively to energy consumption, it is warned that real time pricing sometimes can cause increment of peak-time demand and volatility. Finally, real time pricing could be less efficient when the difference between the maximum and the minimum consumption level is small.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.7
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• pp.889-895
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• 2014

Korea electric power industry had been under vertical monopoly but is typically getting restructured for free competition. An ideal pricing system under the competitive market system is 'unbundled pricing system' and 'marginal pricing system', but the current pricing system still adheres to the traditional bundled system and the average cost pricing system. Especially, progressive electricity rates for residential use reflect governmental policy-making which is focused on income redistribution & welfare, industrial supports and energy saving. This study proposes new and reasonable residential electricity pricing systems which are Time-Of-Use (TOU) and Real-Time Pricing (RTP) to reflect variations in the wholesale price of electricity. It also presents examples of various tariffs for residential electricity pricing systems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.3
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• pp.306-311
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• 2013

The Real-Time-Pricing (RTP) brings greatest values in terms of economic incentives and efficiency among the dynamic pricing schemes. The electric power industry in Korea is mainly operated by publicly owned utilities and strongly regulated by the government; therefore, revenue reconciliation of RTP is inevitably required to prevent revenue deficits. In this paper, a revenue reconciliation of real-time pricing considering imperfect information on customer response is proposed to prevent revenue deficit and distortion of the spot price. A case study is present to verify the applicability of the proposed method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.804-809
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• 2012

This paper presents the economic impact of consumer participation in Real-Time Pricing (RTP). A computer model was developed to analyze the impact of real-time pricing on the average price, electricity sales, and the social welfare. Four revenue reconciliation alternative were introduced to illustrate the effect of RTP. Finally a case study was done to analyze the consequent impact of the dynamic load profile on the long-term fuel mix, and the results were compared with those of $5^{th}$ national power development plan.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.1964-1970
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• 2010

A new intelligent power network (Smart Grid) that grafts some new technologies, such as the extension of the new and reproducible energy, electric motors, and electric storages, onto the regulation of green house gases according to the recent convention on climate changes has been actively promoted. As establishing such an intelligent power network, it is possible to implement a real-time rate system according to the change from the conventional single directional information transmission to the bidirectional information transmission. Such a real-time rate system can provide power during the chip rate hour by avoiding the high rate hour although customers use the same level of power through providing such real-time rate information including power generation costs. In this study, the establishment of an operating system that makes an effective use of the real-time rate system and its operation method are to be proposed.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.435-437
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• 2002

This Paper presents the technical perspective on the Real Time Pricing(RTP). So far customer has no control on the electricity pricing. But the price hike in California makes changes in the electricity demand and pricing. In such environments. RTP has become an important role in Demand Side Management. Here the system configuration, advantages of RTP are described. Also the relationship between RTP and AMR is considered.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2002.05b
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• pp.181-198
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• 2002

This article describes a methodology for evaluating huge aerospace R&D investments using the real options pricing method. Option pricing has been proposed as a useful approach for modeling investment in R&D. Two important features of R&D investments are that an R&D project takes time to complete and that the outcome of R&D investments is highly uncertain. This makes the analysis of R&D investments difficult. Traditional tools for project evaluation, like IRR or the NPV, are inadequate for coping with the high uncertainty. Hence, In this article I propose a log-transformed binomal lattice method, and it will show that option pricing might be an adequate framework for evaluating such types of aerospace investments.

• Journal of Electrical Engineering and Technology
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• v.4 no.1
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• pp.49-54
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• 2009

One of the major challenges confronting a multiservice electric utility is the establishment of the right prices for its services. The key objectives of particular pricing schemes are reasonableness of company earnings, economic efficiency, the responsiveness of supply and of the allocation of sources to the desires of consumers, and maintenance of some degree of competition. This paper proposes a value-based pricing mechanism amenable to the current deregulation situation in electricity market allowing service differentiation. The proposed pricing mechanism can be implemented in a nodal auction model, and can also be applied to direct load control.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.5
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• pp.644-651
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• 2014

The renewable energy system and the real-time pricing can provide the significant economic advantage for end-user of residential house. However, according to recent studies, high initial cost of renewable energy system such as photovoltaic (PV) system and lack of suitable load control methods adjusting electric power consumption in response to time-varying price are regarded as the major obstruction for introduction of renewable energy system and real-time pricing in residental household. In this paper, we propose automated optimal load control strategy which aim to achieve not only minimizing the electricity cost but also the increase in the utilization rates of PV generation power of residential PV house in real-time pricing environment. Simulation results show that our proposed optimal load control strategy leads to significant reduction in the electricity costs and increase in the utilization rates of power generated by PV system in comparison with the conventional PV house. Therefore, the proposed optimal load control strategy can provide more economic benefit to end-user.

• ETRI Journal
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• v.42 no.4
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• pp.585-595
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• 2020

Integration of multiple communication technologies in a smart grid (SG) enables employing cognitive radio (CR) technology for improving reliability and security with low latency by adaptively and effectively allocating spectral resources. The versatile features of the CR enable the smart meter to select either the unlicensed or the licensed band for transmitting data to the utility company, thus reducing communication outage. Demand response management is regarded as the control unit of the SG that balances the load by regulating the real-time price that benefits both the utility company and consumers. In this study, joint allocation of the transmission power to the smart meter and consumer's demand is formulated as a two stage multi-armed bandit game in which the players select their optimal strategies noncooperatively without having any prior information about the media. Furthermore, based on historical rewards of the player, a real-time pricing adaptation method is proposed. The latter is validated through numerical results.