• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.915-922
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• 2017

Demand Response Market (DR Market) has risen as one of the key solutions to address the growth and fluctuation of electricity consumptions. In Korea, DR market has been in operation since 2014, where the focus has been mainly on large-scale loads. Small-scale DR market, however, is becoming increasingly important because small power consumers' contribution to the national power consumption has been increasing and because small loads tend to show large fluctuations. Furthermore, small-scale DR can improve social awareness on energy issues which can bring additional impacts. In this paper, we provide the findings from a small-scale consumer DR pilot. The pilot was conducted in the summer of 2016 on over 5,000 small-scale users in Korea, and smartphone applications were used in the pilot. The effectiveness of small-scale DR Market is analyzed and addressed, and the results indicate a promising future of small-scale DR Market.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1091-1096
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• 2011

Currently, the concern about the environment is the issue all over the world, and in particular, carbon emissions of the power plants will not be able to disregard from the respect of generation cost. This paper proposes DR (demand response) as a method of reducing carbon emissions and therefore, carbon emissions cost. There are a number of studies considering DR, and in this paper, the effect of DR is focused on the side of carbon emission reduction effect considering Time-Of-Use (TOU) program, which is one of the most important economic methods in DSM. Demand-price elasticity matrix is used in this paper to model and analyze DR effect. Carbon emissions is calculated by using the carbon emission coefficient provided by IPCC (Intergovernmental Panel on Climate Change), and generator's input-output characteristic coefficients are also used to estimate carbon emission cost as well as the amount of carbon emissions. Case study is conducted on the RBTS IEEE with six buses. For the TOU program, it is assumed that parameters of time period partition consist of three time periods (peak, flat, off-peak time period).

• 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.10 no.3
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• pp.755-765
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• 2015

A thermostatically controlled load (TCL) can be one of the most appropriate resources for demand response (DR) in a smart grid environment. DR capability can be effectively implemented in a TCL with various intelligent control methods. However, because traditional on-off control is still a commonly used method in a TCL, it is useful to develop a method for adding DR capability to the TCL with an existing on-off controller. As a specific realization of supervisory control for implementing DR capability in the TCL, two methods are proposed - a method involving the changing of a set point and a method involving the paralleling of an identified system without delay. The proposed methods are analyzed through the simulations with an electric heater for different power consumption levels in the on-state. Considerable cost benefit can be achieved with the proposed methods when compared with the case without DR. In addition, the observations suggest that a medium power consumption level, instead of the maximum power, in the on-state should be used for consistently obtaining the cost benefit without severe temperature deviation from the specified temperature range for DR.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.8
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• pp.1074-1079
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• 2013

Demand response(DR) is potential generation alternative to improve the reliability indices of system and load points. However, when demand resources scheduled in DR market fail to reduce demand, it can create new problems associated with maintaining a reliable supply. In this paper, a reliability model of demand resource is constructed considering customers' behaviors in the same form as conventional generation units, where availability and unavailability are associated with the simple two-state model. As a result, the generalized reliability model of demand resources is represented by multi-state model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.312-321
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• 2018

The Korean DR market proposes suppression of peak demand under reliability crisis caused a natural disaster or unexpected power plant accidents as well as saving power plant construction costs and expanding amount of reserve as utility's perspective. End-user is notified a DR event signal DR execution before one hour, and executes DR based on requested amount of load reduction. This paper proposes a DR energy management algorithm that can be scheduled the optimal operations of chiller system and ESS in the next day considering the TOU tariff and DR scheme. In this DR algorithm is divided into two scheduling's; day-ahead operation scheduling with temperature forecasting error and operation rescheduling on DR operation. In day-ahead operation scheduling, the operations of DR resources are scheduled based on the finite number of ambient temperature scenarios, which have been generated based on the historical ambient temperature data. As well as, the uncertainties in DR event including requested amount of load reduction and specified DR duration are also considered as scenarios. Also, operation rescheduling on DR operation day is proposed to ensure thermal comfort and the benefit of a COB owner. The proposed method minimizes the expected energy cost by a mixed integer linear programming (MILP).

• Smart Media Journal
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• v.8 no.4
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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 Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1225-1228
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• 2011

This paper presents an advanced energy saving algorithm in building. It is important to aggregate a various demand side resource which is controllable on demand response environment. Previous demand side algorithm for building is restricted on peak power. In this paper, we suggest duty cycle algorithm for AHU on demand response to reduce the quantity of building power consumption. The test results show that the proposed algorithm is very effective.

• 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.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.213-214
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• 2015

국내에 수요자원 거래시장은 개설이 되었지만 아직까지 여러 목적에 맞는 최적 입찰전략에 대해서는 논의된 바가 많지 않다. 본 논문에서는 수요자원 중에서도 특히 산업용 수용가 ESS(Energy Storage System)에 대해서 경제성 DR(Demand Response) 시장에 참여 할 때 최대의 이익의 얻을 수 있는 입찰전략을 제시하였다. 그리고 이익 뿐만 아니라 유찰 위험까지 고려할 수 있는 현대 포트폴리오 이론을 적용한 입찰전략을 제시하였다.