• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.541_542
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• 2009

This paper reviews the definition and background of dynamic pricing which is the essential element of demand response system. Also, economic efficiency and related issues on dynamic pricing are studied. Several issues on design and operation of demand response system, which can implement the dynamic pricing, are described. Therefore the results will be helpful for developing the demand response system with dynamic pricing.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1116-1120
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• 2014

With the shift of the energy paradigm from supply side management to demand side management, demand resource management and demand response plays an important role in the energy industry. As a consequency, a lot of researches have been done to provide a suitable demand response system. However, most of the demand response systems are based on the propriety products that cannot be modified. In this paper, we are proposing an automated demand response system using an EnerNOC provided open source code. We implemented the demand response server (VTN) and demand response client (VEN), and validated the OpenADR2.0 compliances using the open source code. We also used an Arduino microcontoller to demonstrate the communication schemes to control various devices.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.664-666
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• 2003

본 연구에서는 신 수요관리 기법인 DR(Demand Response) 시스템의 적용 현황을 분석하였다. 현재 전력사에서 사용하고 있는 9개의 프로그램에 대한 특성 및 적용 사례를 조사하고 분석하였다. 또한 DR 프로그램의 전형적인 실행과정을 살펴보고 DR의 효과적인 응용에 필요한 부분인 단기 부하예측의 필요와 이들의 방법에 대해서 조사하였다. 부하 예측을 위해서는 수요자의 부하 정보의 분석이 기반이 된다. 따라서 국내에 DR시스템을 도입할 경우에는 수요자의 부하 정보인 Load Profile에 대한 정보의 분석 시스템의 개발이 선행되어야 할 것으로 판단된다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.1
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• pp.17-23
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• 2013

The BESS(Battery Energy Storage System) is an useful device for load leveling, but the high cost, installation space and safety issues are the main barriers for supplying it widely. The important factor in supplying BESS to customers successfully is the payback period. As most of the H/W cost factors are uncontrollable, the optimization of storage volume can be useful factor in improving payback period. In order to obtain optimized BESS volume, the load factor, demand ratio, peak shaving ratio, electric rates and benefits from DR participation of customer should be analyzed. In this paper, we could verify the peak cutting capability and cost effectiveness under the some proposed conditions and changing value of PCS and battery based on the customers data after volume optimization process was applied, and we can identified the saturation point of load factor and shortening of customer's payback period.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.12
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• pp.1192-1196
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• 2009

Recently, the environment contamination problem and energy saving are the social issues. So, the Green IT based Smart Grid was suggested. The smart grid will let rates fluctuate even more dynamically, depending on conditions using energy. Thus, green IT includes the dimensions of environmental sustainability and the economics of energy efficiency. The smart controller in which it is controlled by DR in order to manage the energy consumption by using AMI is needed in order to apply its technology to the real life. In this paper, DR_WTIM of the IEEE1451.5 base which has the DR function for connecting to AMI of the wireless base is developed. By using this apparatus for the power control system, the energy saving effect is shown. Moreover, by using the IEEE1451.5 technology, the problem of energy consumption is solved in order to apply to power controller designed for efficient use energy.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.613-616
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• 2006

본 연구에서는 신 수요관리 기법인 DR(Demand Response)시스템의 개발 및 운영현황을 알아 보았다. 특히 DR 시스템의 구성 방안과 각 모듈들의 설계시 검토 및 요구 사항을 분석하였다. 그리고 공급자와 수요자를 잇는 네트워크는 국가전력 IT과제에서 Portal의 개념을 도입하여 CP(Consumer Portal) 및 DP(Device Portal)에 의한 채널의 표준화를 시도하고 있다. DR의 개념은 수요관리와 가격 응답으로 공급자의 관리 기능과 가격 또는 인센티브 등이 제공되는 수요자가 참여하는 서비스의 양면을 가지고 있다. 이와 같은 시스템이 개발될 경우에는 전력사와 소비자 사이의 양방향 통신 채널이 형성되고 따라서 실시간 수요의 측정이 가능해진다. 또한 이를 토대로 DR 시스템을 사전 검토 및 계획상의 문제점을 분석하여 한국형 DR 시스템의 개발에 대한 기반을 조성하고자 하였다.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.3
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• pp.391-395
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• 2016

In the last few decades, global electricity consumption has dramatically increased and has become drastically fluctuating and uncertain causing blackout. Due to the unexpected peak electricity demand, we need significant electricity supply. The solutions to these problems are smart grid system which is envisioned as future power system. Smart grid system can reduce electricity peak demand and induce effective electricity consumption through various price policies, demand response (DR) control methodologies, and state-of-the-art smart equipments in order to optimize electricity resource usage in an intelligent fashion. Demand response (DR) is one of the key technologies to enable smart grid. In this paper, we propose greedy technique for demand response smart grid system. The proposed scheme focuses on minimizing electricity bills, preventing system blackout and sacrificing user convenience.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.3
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• pp.536-542
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• 2010

This paper presents an unique approach to scheme a demand response (DR) program in the electricity market from a customer-oriented perspective, which is based on the analytic hierarchy process (AHP). The proposed program has the objective to maintain the system reliability at the emergency period, and it is designed as an incentive-based program (IBP) considering Korea power systems with the cost-based generation pool (CBP). The DR program using AHP could represent the mutual importance degrees of load curtailment criteria from the viewpoint of different load-holders, thus customers' participation in this program is determined by the incentive payments corresponding the specific load curtailment conditions. A test system for the case study is used to demonstrate the usefulness and applicability of the proposed approach, and the load profiles with the proposed DR program and the required incentive payments are obtained. The results show not only the enhancement of system reliability but also the economic benefit within Pareto-improvement.

• ETRI Journal
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• v.35 no.4
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• pp.677-686
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• 2013

In this paper, we first introduce a general architecture of an energy management system in a home area network based on a smart grid. Then, we propose an efficient scheduling method for home power usage. The home gateway (HG) receives the demand response (DR) information indicating the real-time electricity price, which is transferred to an energy management controller (EMC). Referring to the DR, the EMC achieves an optimal power scheduling scheme, which is delivered to each electric appliance by the HG. Accordingly, all appliances in the home operate automatically in the most cost-effective way possible. In our research, to avoid the high peak-to-average ratio (PAR) of power, we combine the real-time pricing model with the inclining block rate model. By adopting this combined pricing model, our proposed power scheduling method effectively reduces both the electricity cost and the PAR, ultimately strengthening the stability of the entire electricity system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.97-115
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• 2022

Smart power grid is a user friendly system that transforms the traditional electric grid to the one that operates in a co-operative and reliable manner. Demand Response (DR) is one of the important components of the smart grid. The DR programs enable the end user participation by which they can communicate with the electricity service provider and shape their daily energy consumption patterns and reduce their consumption costs. The increasing demands of electricity owing to growing population stresses the need for optimal usage of electricity and also to look out alternative and cheap renewable sources of electricity. The solar and wind energy are the promising sources of alternative energy at present because of renewable nature and low cost implementation. The proposed work models a smart home with renewable energy units. The random nature of the renewable sources like wind and solar energy brings an uncertainty to the model developed. A stochastic dual descent optimization method is used to bring optimality to the developed model. The proposed work is validated using the simulation results. From the results it is concluded that proposed work brings a balanced usage of the grid power and the renewable energy units. The work also optimizes the daily consumption pattern thereby reducing the consumption cost for the end users of electricity.