• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.93-104
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• 2024

Demand response is a strategy that encourages customers to adjust their consumption patterns at times of peak demand with the aim to improve the reliability of the power grid and minimize expenses. The integration of renewable energy sources into smart grids poses significant challenges due to their intermittent and unpredictable nature. Demand response strategies, coupled with reinforcement learning techniques, have emerged as promising approaches to address these challenges and optimize grid operations where traditional methods fail to meet such kind of complex requirements. This research focuses on investigating the application of reinforcement learning algorithms in demand response for renewable energy integration. The objectives include optimizing demand-side flexibility, improving renewable energy utilization, and enhancing grid stability. The results emphasize the effectiveness of demand response strategies based on reinforcement learning in enhancing grid flexibility and facilitating the integration of renewable energy.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.1956-1963
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• 2010

Studies on the development of various energy management programs and real-time bidirectional information infrastructures have been actively conducted to promote the reduction of power demands and CO2 emissions effectively. In the conventional energy management programs, the demand response program that can transition or transfer the power use spontaneously for power prices and other signals has been largely used throughout the inside and outside of the country. For measuring the effect of such demand response program, it is necessary to exactly estimate short-term loads. In this study, the power consumption patterns in both individual and group consumers were analyzed to estimate the exact short-term loads, and the relationship between the actual power consumption and seasonal factors was also analyzed.

• Structural Engineering and Mechanics
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• v.58 no.2
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• pp.327-345
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• 2016

Many experimental and analytical studies have been conducted with beam-column subassemblages composed of a two-span beam to investigate the progressive collapse resistance of RC frames. Most study results reveal a strength-decreased transition phase in the nonlinear static load-deflection curve, which may induce dynamic snap-through response and increase the chord rotation demand for effective catenary action (ECA). In this study, the nonlinear static response is idealized as a piecewise linear curve and analytical pseudo-static response is derived for each linearized region to investigate the rotation demands for the ECA of the two-span RC beams. With analytical parameters determined from several published test results, numerical analysis results indicate that the rotation demand of 0.20 rad recommended in the design guidelines does not always guarantee the ECA. A higher rotation demand may be induced for the two-span beams designed with smaller span-to-depth ratios and it is better to use their peak arch resistance (PAR) as the collapse strength. A tensile reinforcement ratio not greater than 1.0% and a span-to-depth ratio not less than 7.0 are suggested for the two-span RC beams bridging the removed column if the ECA is expected for the collapse resistance. Also, complementary pseudo-static analysis is advised to verify the ECA under realistic dynamic column loss even though the static PAR is recovered in the nonlinear static response. A practical empirical formula is provided to estimate an approximate rotation demand for the ECA.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.1
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• pp.222-228
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• 2017

The aims of the demand response market are stabilization of the power supply and improving of the reliability of the power system. The various applications of the energy storage system (ESS) in the railway systems are studied and implemented to raise the energy efficiency. It is one of the most important how to determine the obligation reduction capacity (ORC) in participation to the demand response market because it has an influence on the profit extremely. In this paper, when participating to the demand response market with demands in the urban railway, we calculated the available ORC and economically evaluated ESS based on the real load data.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1719-1728
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• 2017

Recent concerns about environmental conditions have triggered the growing interest in using green energy resources. These sources of energy, however, bring new challenges mainly due to their uncertainty and intermittency. In order to alleviate the concerns on the penetration of intermittent energy resources, this paper investigates impacts of realizing demand-side potentials. Among different demand-side management programs, this paper considers demand response wherein consumers change their consumption pattern in response to changing prices. The research studies demand response potentials from different load sectors on generation system well-being. Consumers' sensitivity to time-varying prices is captured via self and cross elasticity coefficients. In the calculation of well-being indices, sequential Monte Carlo simulation approach is accompanied with fuzzy logic. Finally, IEEE-RTS is used as the test bed to conduct several simulations and the associated results are thoroughly discussed.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2157-2165
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• 2017

This study deals with the design of the mechanism in which demand response (DR) resources are traded in the power generation market. In general, a DR aggregator (DRA), which extends DR resources and provides technical support, is central to this mechanism. In this study, power users, called DR customer (DRC), participate in load reduction and are also modeled to participate directly in DR-related bidding. The DRA provides incentives to the DRC, indirectly impacting the market, and the DRC use the bid parameters strategically. We present the conditions for finding Nash Equilibrium (NE) in game problems of various participants including market operators, and analyze the characteristics of DRA and DRC related models. It also analyzes the impact of the participants on the market according to various types of competition and coalitions between DRA and DRC.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.269-271
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• 2004

전력산업 구조의 변화와 전력수급의 안정성 확보를 위해, 다양한 전원개발에 대한 연구가 시도되고 있다. 본 연구에서는 현재 미국에서 시행하고 있는 수요응답자원(Demand Response Resource)에 대한 수요응답 프로그램(Demand Response Program)의 성과를 조사하고 이를 분석하였다. 미 연방에너지 규제위원회(FERC)의 시장표준안과 각 주의 공익규제위원회(PUC)에 규제에 의해 대부분의 미 전력시장에서는 이러한 수요응답 프로그램을 시행하고 있다. 본 논문에서는 미국 전력시장을 대표하는 New England ISO, PJM, 그리고 NYISO 세 곳의 수요응답 프로그램 효과를 조사하였다. 본 논문에서는 수요응답 프로그램의 참여자 수와 수용응답 이벤트 발생 건 수, 총 차단부하량, 평균 차단부하량, 그리고 지급액의 관점에서 수요웅담 프로그램의 효과를 조사하였다.

• Proceedings of the KIEE Conference
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• summer
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• pp.671-673
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• 2004

Demand Response Programs (DRP) are critical to the operation of efficient and competitive energy markets. and provide critical market improvements to Independent System Operators (ISO). To all energy market Participants, they Provide savings and cost reductions when end users have the ability to respond to wholesale prices. Now, in the competitive electricity market, DRP is classified by Emergency and Economic DRP to reduce costs and maintain reliability. In this paper, we survey the trend of Demand Response Program over the world and compare the practical performance among the markets in US.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.12
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• pp.991-994
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• 2016

This paper presents a load management method based on OpenADR of smart grid. Previous demand side algorithm is restricted on reducing peak power. But, in this paper we suggest a method of performing the energy-saving control according to the power price utilizing building automatic control system installed on the customer side in the case of hourly differential pricing signal is transmitted to the open automated demand response system. And, we showed the integrated demand management software for 3 buildings.

• Environmental and Resource Economics Review
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• v.27 no.2
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• pp.287-313
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• 2018

This paper measures and analyzes cooling and heating demand in Korean electricity demand using time-varying temperature response functions and cooling and heating temperature effects. We fit the model to Korean data for residential and commercial sector over 1999:01~2016:12 and the estimation results show that the growth rate of heating demand is much higher than that of base and cooling demand, and especially the growth rate of heating demand in commercial sector is much higher. And we define the temperature-normalized demand conditioning that monthly temperatures are assumed as average monthly temperatures. The growth rate of heating demand in the estimated temperature-normalized demand is higher than that in the real demand. Our results are expected to be a base data for Winter Demand Management and short-term electricity demand forecasting.