• ETRI Journal
• /
• v.16 no.3
• /
• pp.11-26
• /
• 1994

In Korea, the price schedule for local telephone combines two-part tariffs and peak-load pricing subject to rate-of-return (RoR) regulation. Although the effect of RoR regulation on two-part tariffs or peak-load pricing has been separately analyzed by many authors in some detail, the behaviour of regulated firm under combined two-part and peak-load pricing has not been studied until now. This paper examines the effect of regulation on the rate structure and welfare under combined two-part and peak-load pricing.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.65 no.7
• /
• pp.1128-1134
• /
• 2016

Demand response provides customer load reductions based on high market prices or system reliability conditions. One type of demand response, price-based program, induces customers to respond to changes in product rates. However, there are large-scale general and industrial customers that have difficulty changing their energy consumption patterns, even with rate changes, due to their electricity demands being commercial and industrial. This study proposes an in-house pricing model for large-scale general and industrial customers, particularly those with multiple business facilities, for self-regulating demand-side management and cost reduction. The in-house pricing model charges higher rates to customers with lower load factors by employing peak to off-peak ratios in order to reduce maximum demand at each facility. The proposed scheme has been applied to real world and its benefits are demonstrated through an example.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.6
• /
• pp.1296-1304
• /
• 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
• /
• v.59 no.12
• /
• pp.2165-2172
• /
• 2010

This paper presents the operation algorithm of microgrid on the Real Time Pricing(RTP) for building the smart grid. RTP is higher power price variability than flat rate and time of use. However it has an effect on peak clipping and peak load shifting due to the increased price on peak time power demand. When the RTP are applied to the microgrid system, the proposed algorithm is able to be effective and economic operation. The implemented system is operated for the economic operation in microgrid connected with the power system. On the other hand, when the microgrid is operated on isolation mode, it focus on the improvement of stability and the power supply reliability of the sensitive loads. The test system are implemented and calculated on various operation modes based on non-dispachable generator output and RTP data for validating the proposed operation algorithm. The calculated results are compared to the implemented results using real-time simulator. It can be confirmed that the proposed operation system are identical results to the calculated one. When the proposed operation algorithm is applied to the system, it can be show the effectiveness of the peak clipping and peak load shifting and the improvement of economic feasibility.

• Proceedings of the KIEE Conference
• /
• 2008.07a
• /
• pp.586-587
• /
• 2008

지난 논문 "Critical Peak Pricing 요금제를 이용한 일반 수용가 대상 수요관리의 방법" 및 그 후속 연구에서는 일반 수용가를 대상으로 한 효율적인 수요관리의 한 방법으로써 Critical Peak Pricing 요금제를 제안하였다[1]. 또한 이 요금제에서 핵심이 되는 최적 critical peak 시점을 푸는 하위 문제들 및 방법론을 제시하였는데, 이 논문에서는 그 하위 문제들 중 수용가의 부하를 예측하는 문제를 다룬다. 우리는 energy service provider(ESP)가 관리해야 할 수용가의 수가 매우 많다는 점에 주목하여, 각 수용가의 1일 부하 사용량 패턴을 몇 개의 그룹으로 나누어 각 그룹에 대해 critical peak 최적 시점을 결정하는 연구를 수행하였다. 이러한 수용가 부하량 패턴 그룹화를 위해 인공 지능의 여러 기법 중 하나인 self-organizing map(SOM)을 사용하였다.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.8
• /
• pp.1025-1032
• /
• 2014

The effective energy management method will provide the significant advantage to the residential customers under real time pricing plan since it can reduce the electricity charge by controlling the energy consumption according to electricity rate. The earlier studies for load management mainly aim to minimize the electricity charges and peak power but put a less emphasis on the human comfort dwelling in the residence. The discomfort and displeasure from the energy management only focusing on reduction of electricity charge will make the residential customer reluctant to enroll the real time pricing plan. In this paper, therefore, we propose optimal load control strategy which aim to achieve not only minimizing the electricity charges but also maintaining human comfort by introducing "the human comfort coefficient." Using the human comfort coefficient, the energy management system can reflect the various human personality and control the loads within the range that the human comfort is maintained. Simulation results show that proposed load control strategy leads to significant reduction in the electricity charges and peak power in comparison with the conventional load management method.

• ETRI Journal
• /
• v.37 no.1
• /
• pp.197-202
• /
• 2015

A smart grid is a modernized electrical grid that uses information about the behaviors of suppliers and consumers in an automated fashion to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity. In the operation of a smart grid, demand side management (DSM) plays an important role in allowing customers to make informed decisions regarding their energy consumption. In addition, it helps energy providers reduce peak load demand and reshapes the load profile. In this paper, we propose a new DSM scheduling scheme that makes use of the day-ahead pricing strategy. Based on the Rubinstein-Stahl bargaining model, our pricing strategy allows consumers to make informed decisions regarding their power consumption, while reducing the peak-to-average ratio. With a simulation study, it is demonstrated that the proposed scheme can increase the sustainability of a smart grid and reduce overall operational costs.

• Environmental and Resource Economics Review
• /
• v.3 no.1
• /
• pp.147-182
• /
• 1993

• Proceedings of the KIEE Conference
• /
• 2008.11a
• /
• pp.460-462
• /
• 2008

일반 수용가를 대상으로 한 효율적인 수요관리의 한 방법으로써 Dynamically-Administered Critical Peak Pricing[1] 요금제를 이용하여 일반 수용가 대상 수요관리를 스마트 미터기인 Smart Cabinet Panel(SCP)를 개발하여 적용하였다. 이 DA-CPP 요금제에는 핵심이 되는 최적 critical peak 시점을 푸는 하위 문제들 및 방법론들이 존재하는데, 우리는 energy service provider(ESP)가 관리해야 할 수용가의 수가 매우 많다는 점에 주목하여, 각 수용가의 1일 부하 사용량 패턴을 몇 개의 그룹으로 나누어 각 그룹에 대해 critical peak 최적 시점을 결정하는 연구를 수행하였다. 이러한 수용가 부하량 패턴그룹화를 위해 인공 지능의 여러 기법 중 하나인 self-organizing map(SOM)을 사용하였다 그리고 ESP와 수음가가 통신할 수 있도록 개발된 SCP를 통해 Critical Peak을 적용하였다.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.12
• /
• pp.1627-1636
• /
• 2014

In real-time electricity price environment, the energy management system can provide the significant advantage to the residential, commercial and industrial customers since it can reduce the electricity charge by controlling the load operation effectively in response to time-varying price. However, the earlier studies for load management mainly focus on the residential and commercial customers except for the industrial customers because most of load operations in industrial sector are intimately related with production schedule. So, it is possible that the inappropriate control of loads in industrial sector causes huge economic loss. In this paper, therefore, we propose load control algorithm for factory energy management system(F-EMS) to achieve not only minimizing the electricity charges but also maintaining production efficiency by considering characteristics of load operation and production schedule. Considering characteristics of load operation and production schedule, the proposed load control algorithm can reflect the various characteristics of specific industrial customer and control their loads within the range that the production efficiency is maintained. Simulation results show that the proposed load control algorithm for F-EMS leads to significant reduction in the electricity charges and peak power in industrial sector.