• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2202-2205
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• 2011

Demand side management is used to maintain the reliability of power systems and to increase the economic benefits by avoiding power plant construction. This paper presents a systematic method to calculate the quantity of seasonal demand side management using time series. A numerical example is presented to calculate the quantity of demand side management in winter season using time series.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.110-112
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• 1992

Recently, increment of power demand is conspicuous, the necessity of demand side management is increased. here, we presented development of economic power demand controller again, we investigated the validity of peak demand control for customers and utilities.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.10
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• pp.1278-1285
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• 2018

For saving electricity bill, energy storage system(ESS) is being installed in factories, public building and commercial building with a Time-of-Use(TOU) tariff which consists of demand charge(KRW/kW) and energy charge(KRW/kWh). However, both of peak reduction and ESS special tariff are not considered in an analysis of initial cost payback period(ICPP) on ESS. Since it is difficult to reflect base rate by an amount of uncertain peak demand reduction during mid-peak and on-peak periods in the future days. Therefore, the ICPP on ESS can be increased. Based on this background, this paper presents the advanced analysis method for the ICPP on ESS. In the proposed algorithm, the representative days of monthly electricity consumption pattern for the amount of peak reduction can be found by the k­means clustering algorithm. Moreover, the total expected energy costs of representative days are minimized by optimal daily ESS operation considering both peak reduction and the special tariff through a mixed-integer linear programming(MILP). And then, the amount of peak reduction becomes a value that the sum of the expected energy costs for 12 months is maximum. The annual benefit cost is decided by the amount of annual peak reduction. Two simulation cases are considered in this study, which one only considers the special tariff and another considers both of the special tariff and amount of peak reduction. The ICPP in the proposed method is shortened by 18 months compared to the conventional method.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.19-22
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• 1993

Demand side management (DSM) is the planning and implementation of those utility designed to influence customer use of electricity in ways that will produce desired changes in the utility's load shape. It is conspicuous that the peak load control of DSM is efficiently adopted. In this paper, the package type air conditioner(A/C) mounted radio controlled switch. During the summer of 1990 KEPCO conducted tests in Seoul areas to determine the economic feasibility of interrupting A/C units for short periods of time during peak load periods. These tests were performed between July 30 and September 20 and were limited to the hours of between 1 and 6 p.m. These tests indicated that each A/C contributes approximately 4.5kW to the system peak and can be switched off 10 minutes out of each 1/2 hour without causing the customer any discomfort. Switching each A/C off for 10 minutes out of each 1/2 hour results in a peak load demand reduction of one kW per unit.

• 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 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.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.113-115
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• 2004

This year korea power system had recorded highest peak load for 6 times and finally it made new peak load 51,264MW at July 29th 3:00 PM. The new peak load is increased 8.2% from the last year peak load 47,385MW and korea power system entered 50,000MW load era. The Korea Power Exchange (KPX) snapped power system data at the peak load time using state estimation function in the EMS. And authors converted the power system data at peak load to PSS/E power flow format. Using this PSS/E peak load power flow data, this paper explains demand analysis result shun capacitor operation, voltage distribution at the peak load. And the paper shows the simulation result of 2 contingency analysis using the snapped PSS/E peak load data.

• 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.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.292-294
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• 2000

This paper is presented the method peak load forecast based on multiple regression Model. Forecasting model was composed with the temperature-humidity and the discomfort index. Also the week periodicity was excluded from weekday change coefficient of two types. Forecasting result was good with about 3[%]. And, utility of presented forecast model using statistical tests has been proved. Therefore, This results establish appropriateness and fitness of forecast models using peak power demand forecasting.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.9
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• pp.1575-1580
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• 2010

Demand Response is a well-known means usually operated by the system operator(SO) or the electricity retailers in order to reduce the peak loads or cut the price in electricity market. KPX(Korea Power eXchange), the SO in Korea has been operating the demand bidding program(or the demand resource market) since it was firstly introduced as the pilot project in 2008. The results has proved to be effective to enhance demand response. This paper describes the basic concepts and the operation results of the program.