• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1296-1304
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• 2013

This study performed an analysis on power demand reduction effects exhibited by demand response programs, which are advanced from traditional demand-side management programs, in the smart grid environment. The target demand response systems for the analysis included incentive-based load control systems (2 month-ahead demand control system, 1~5 days ahead demand control system, and demand bidding system), which are currently implemented in Korea, and price-based demand response systems (mainly critical peak pricing system or real-time pricing system, currently not implemented, but representative demand response systems). Firstly, the status of the above systems at home and abroad was briefly examined. Next, energy saving effects and peak demand reduction effects of implementing the critical peak or real-time pricing systems, which are price-based demand response systems, and the existing incentive-based load control systems were estimated.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2221-2224
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• 2011

During an emergency due to a shortage of power, a load aggregator (LA) can use the demand response operation system to deploy demand response resources (DRRs) through various demand response (DR) programs. This paper introduces the demand response operation system for a load aggregator to manage various demand response resources in a smart grid environment.

• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.384-386
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• 2002

As restructuring in power industry has introduced competitive markets, a new method on demand side management has been developed. Many programs using the method were developed with providing several choices for customer. Nowadays the programs are called demand response as the load management is done by customer's responding to the market price signal. It was proven that the method was effective for demand control with the active consumer's attending for the program. This paper analyses the perspective and the requirement for designing the demand response system.

• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.291-297
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• 2010

A system called demand response programs (DRP) is being introduced among various countries owing to the lack of new generation capacity and the higher fuel generation cost. It is a program which provides for the end-users to select their consumption of electricity by recognizing the value of their consumption in real time. That is, Demand Response can be defined as the changes in electric usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity or other signals. It is expected that the effects of DRP are preventing price spike, improving supply reliability and social welfare and increasing option of customers. Considering the customer's thermal comfort zone, this paper determines the most profitable combination of optimal incentives and amounts of load reduction for a retailer to maximize profits according to predicted outdoor temperatures while implementing DRP.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.46-52
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• 2013

Economic properties of an integrated wind power plant (WPP) and the demand response (DR) programs in the sample electricity market are studied. Time of use (TOU) and direct load control (DLC) are two of the DR programs that are applied in the system. The influences of these methods and the incentive payments by market operator's (MOs) with variable elasticity are studied. It is observed that DR with TOU and DLC programs together yields better revenue and energy saving for MOs.

• Journal of Electrical Engineering and Technology
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• v.9 no.3
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• pp.789-795
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• 2014

In a demand response (DR) market run by independent system operators (ISOs), load aggregators are important market participants who aggregate small retail customers through various DR programs. A load aggregator can minimize the allocation cost by efficiently allocating its demand response resources (DRRs) considering retail customers' characteristics. However, the uncertain response behaviors of retail customers can influence the allocation strategy of its DRRs, increasing the economic risk of DRR allocation. This paper presents a risk-based DRR allocation method for the load aggregator that takes into account not only the physical characteristics of retail customers but also the risk due to the associated response uncertainties. In the paper, a conditional value-at-risk (CVaR) is applied to deal with the risk due to response uncertainties. Numerical results are presented to illustrate the effectiveness of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1069-1078
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• 2018

Demand response (DR) programs give opportunity to consumers to manage their electricity bills. Besides, distribution system operator (DSO) is interested in using DR programs to obtain technical and economic benefits for distribution network. Since small consumers have difficulties to individually take part in the electricity market, an entity named demand response provider (DRP) has been recently defined to aggregate the DR of small consumers. However, implementing DR programs face challenges to fairly allocate benefits and payments between DRP and DSO. This paper presents a procedure for modeling the interaction between DRP and DSO based on a bilevel programming model. Both DSO and DRP behave from their own viewpoint with different objective functions. On the one hand, DRP bids the potential of DR programs, which are load shifting and load curtailment, to maximize its expected profit and on the other hand, DSO purchases electric power from either the electricity market or DRP to supply its consumers by minimizing its overall cost. In the proposed bilevel programming approach, the upper level problem represents the DRP decisions, while the lower level problem represents the DSO behavior. The obtained bilevel programming problem (BPP) is converted into a single level optimizing problem using its Karush-Kuhn-Tucker (KKT) optimality conditions. Furthermore, point estimate method (PEM) is employed to model the uncertainties of the power demands and the electricity market prices. The efficiency of the presented model is verified through the case studies and analysis of the obtained results.

• 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.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.76.1-76.1
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• 2011

With the growing penetration of distributed generation including from renewable sources, smart grid power system is needed to address the reliability problem. One important feature of smart grid is demand response. In order to design a demand response program, it is indispensable to understand how consumer reacts upon the change of electricity price. In this paper, we construct an econometrics model to estimate the hourly price elasticity of demand. This panel model utilizes the hourly load data obtained from KEPCO for the period from year 2005 to 2009. The hourly price elasticity of demand is found to be statistically significant for all the sample under investigation. The samples used for this analysis is from the past historical data under the price structure of three different time zones for each season. The result of the analysis of this time of use pricing structure would allow the policy maker design an appropriate incentive program. This study is important in the sense that it provides a basic research information for designing future demand response programs.