• Journal of Korea Society of Industrial Information Systems
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• v.29 no.3
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• pp.67-77
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• 2024

Increasing energy efficiency in factories is an activity aimed at optimizing resource allocation in manufacturing processes to establish production plans. However, this strategy may not apply effectively when night shifts are unavoidable. Additionally, continuous fluctuations in production requirements pose challenges for its implementation in the factory. Recently, with the rapid proliferation of electric vehicles (EVs), technology utilizing electric vehicle batteries as energy storage systems has gained attention. Technology using these batteries can be an alternative for factory energy management. In this paper, a factory energy management method using EV batteries is proposed. The proposed method is analyzed using PSCAD/EMTDC software, considering the state of charge of EV batteries and Time-of-Use (TOU) rates. The proposed method was compared with production scheduling established considering predicted power usage and TOU rates. As a result, production scheduling saved 4,152 KRW per day, while the proposed method saved 7,286 KRW in electricity costs. Through this paper, the possibility of utilizing EV batteries for factory energy management has been demonstrated.

• Journal of the Korean Society for Railway
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• v.20 no.1
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• pp.31-42
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• 2017

Many studies have been performed to reduce electric consumption in railway systems. Due to its low conduction loss and high regenerative braking efficiency characteristics, the ESS powered railway system is chosen as a promising candidate for future railway systems. This paper introduces the ESS powered railway system and analyzes current power charge calculation methods that have been set up by KEPCO (Korea Electric Power Corporation). Based on the analysis, this paper proposes two different power charge reduction methods for the railway system. One is to smooth the peaks of traction energy consumption by supplying additional energy to the grid. The other is to save electric charge by reducing electric energy consumed by the railway during the energy peak time, 2 p.m.~5 p.m., which has highest 'Won/kWh' rates. To verify the effectiveness of the proposed method, the power charge of Seoul Metro Line 2 is recalculated using the method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.7
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• pp.889-895
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• 2014

Korea electric power industry had been under vertical monopoly but is typically getting restructured for free competition. An ideal pricing system under the competitive market system is 'unbundled pricing system' and 'marginal pricing system', but the current pricing system still adheres to the traditional bundled system and the average cost pricing system. Especially, progressive electricity rates for residential use reflect governmental policy-making which is focused on income redistribution & welfare, industrial supports and energy saving. This study proposes new and reasonable residential electricity pricing systems which are Time-Of-Use (TOU) and Real-Time Pricing (RTP) to reflect variations in the wholesale price of electricity. It also presents examples of various tariffs for residential electricity pricing systems.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.640-641
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• 2011

스마트그리드 환경하에서 플러그인 전기 자동차(PEV)는 새로운 도전이자 과제이다. 전 세계적으로 전기 자동차에 대한 관심이 높아지면서 PEV가 전력망에 미치는 영향에 관한 연구가 이루어지고 있다. 본 논문에서는 LA사업자(Load Aggregator)는 소비자들의 부하를 통합적으로 관리하여 에너지 비용을 최소화하며 인센티브 지급을 통한 V2G 서비스를 사용하여 피크 삭감을 유도한다. PEV 운영 비용 최소화와 부하 평탄화를 목적으로 하는 LA사업자에 의한 PEV 충전 부하 관리의 잠재적인 이점들을 평가하며, 최적 충전 제어 방식을 위하여 하루전 시장에서 충전 부하와 V2G 가능 용량을 예측하고 PEV 배터리를 분석하여 모델링하는 방법을 제시하였다. 사례연구에서는 다음의 세 가지 PEV 충전 시나리오 즉, 제어되지 않는 시나리오(퇴근 후 충전), TOU 요금제를 적용한 시나리오와 최적 충전 제어 시나리오에 대해 에너지 비용과 피크 수요 감축 측면에서 비교 평가하였다. 이는 향후 증가하는 PEV로 인한 계통의 경제성 평가 및 신뢰도 평가로 사용할 수 있을 것으로 사료된다.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.205-206
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• 2015

전력소비는 꾸준한 증가를 보이고 있지만 연료가격의 증가와 환경 및 사회적 문제로 발전설비를 늘리는 것은 제한적이다. 따라서 발전설비를 추가하지 않고 전력수급의 안정화를 꾀하기 위해 최근 소비자가 전력시장에 참여하는 수요반응이 주목을 받고 있다. 본 논문은 수용가의 전기 사용료 절감 측면에서 수요반응을 분석해 보았다. 먼저 수용가의 부하패턴을 분석하는 기준을 제시하고 그에 따라 현재 우리나라에서 시행하고 있는 대표적인 수요반응인 계시별 요금제(TOU, Time of Use)에 따라 부하 사용패턴을 재조정함으로써 오는 전기 사용료 감소량과 부하율을 계산하였다.

• Journal of Energy Engineering
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• v.29 no.3
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• pp.74-85
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• 2020

This paper presents an algorithm that evaluated the overload influence by bus upon the distribution system by calculating the daily load curve of PEVs charging by bus based on the daily charging patterns of PEVs according to PEVs penetration scenarios. The proposed algorithm calculates the number of PEVs to estimate the number of households by bus; the probability density function of the charging start time of PEVs, considering driving characteristics of PEVs and the daily load curve of PEVs charging by bus considering battery characteristics according to PEVs penetration scenarios. To verify the evaluation of the overload influence by bus on the distribution system in terms of the proposed algorithm, the cases were reviewed on the target bus(apartment and detached houses) among the feeders of the distribution systems at Dongtan new-town in Korea.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.2
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• pp.164-170
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• 2013

The commercial buildings are consuming about 30% of total energy used in Korea. And a large amount of energy consumption in commercial buildings is consumed by HVAC(Heating, Ventilation, Air Conditioning) system. Therefore, if we can reduce the energy consumption in HVAC or air-conditioning system in commercial buildings, the overall energy consumption in Korea can be reduced. Currently, an electricity charge called Time of Use (TOU) is applied to typical commercial buildings. This paper proposes the novel energy management method where the temperature setting of air-conditioning system are adjusted to minimize the use of electrical energy while indoor comfort level is retained. The simulation test for a typical commercial building shows that the proposed method gives over 10% savings in electricity bills and electricity consumption compared to the conventional air-conditioning method.

• Environmental and Resource Economics Review
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• v.30 no.2
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• pp.237-268
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• 2021

As variable renewable sources rapidly increase due to the Energy Transition plan, integration cost of renewable sources to the power system is rising sharply. The increase in variable renewable energy reduces the capacity factor of existing traditional power capacity, and this undermines the efficiency of the overall power supply, and demand resources are drawing attention as a solution. In this study, we analyzed how much electric vehicle demand resouces, which has great potential among other demand resources, can reduce power supply costs if it is used as a flexible resource for renewable generation. As a methodology, a stochastic form of power system optimization model that can effectively reflect the volatile characteristics of renewable generation is used to analyze the cost induced by renewable energy and the benefits offered by electric vehicle demand resources. The result shows that virtual power plant-based direct control method has higher benefits than the time-of-use tariff, and the higher the proportion of renewable energy is in the power system, the higher the benefits of electric vehicle demand resources are. The net benefit after considering commission fee for aggregators and battery wear-and-tear costs was estimated as 67% to 85% of monthly average fuel cost under virtual power plant with V2G capability, and this shows that a sufficient incentive for market participation can be offered when a rate system is applied in which these net benefits of demand resources are effectively distributed to consumers.

• 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.