• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.45-47
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• 1993

Load Management, is originated from efficiency improvement of energy use, or energy conservaion. Traditionally, electric utilities have constructed new power plants to meet the steadily increasing electricity demand. Power development planning, however, is becoming more difficult in the countries like Korea, Japan, and the United States, and increasing concerns about global environmental problems necessitate changes from existing supply-side options based on fossil-fuel to environmentally agreeable supply strategies. This paper discusses the demand side management strategy with emphasis on the concept, implementation scheme, and current practices employed in utilities.

• Journal of Energy Engineering
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• v.8 no.4
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• pp.505-511
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• 1999

One of the major challenges confronting a multiservice electric utility is the establishment of the right prices, for its services. The key objectives of particular pricing schemes are reasonableness of company earnings. Economic efficiency, the responsiveness of supply and of the allocation of sources to the desires of consumers, and maintenance of some degree of competition. This paper proposes a value-based pricing mechanism amenable to the current deregulation situation in electricity market allowing service differentiation. The proposed pricing mechanism can be implemented ina nodal auction model, and can also be applied to direct load control.

• 한국신재생에너지학회:학술대회논문집
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• 2006.06a
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• pp.339-342
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• 2006

The power outputs of renewable energy such as wind turbines and solar energy powers depend on natural sources. Accordingly, the power outputs of renewable energy is different from capacity rate at the time of peak load. Because of this gap, long term electricity power plan can have over-estimated reserve margin. So, this paper suggests the chronological approach to calculate the reliability assessment of renewable energy.

• The Korean Journal of Applied Statistics
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• v.32 no.1
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• pp.161-171
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• 2019

Varied methods have been researched continuously because the past as the daily maximum electricity demand expectation has been a crucial task in the nation's electrical supply and demand. Forecasting the daily peak electricity demand accurately can prepare the daily operating program about the generating unit, and contribute the reduction of the consumption of the unnecessary energy source through efficient operating facilities. This method also has the advantage that can prepare anticipatively in the reserve margin reduced problem due to the power consumption superabundant by heating and air conditioning that can estimate the daily peak load. This paper researched a model that can forecast the next day's daily peak load when considering the influence of temperature and weekday, weekend, and holidays in the Seasonal ARIMA, TBATS, Seasonal Reg-ARIMA, and NNETAR model. The results of the forecasting performance test on the model of this paper for a Seasonal Reg-ARIMA model and NNETAR model that can consider the day of the week, and temperature showed better forecasting performance than a model that cannot consider these factors. The forecasting performance of the NNETAR model that utilized the artificial neural network was most outstanding.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8576-8584
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• 2015

Load forecasting is needed to make supply and demand plan for a stable supply of electricity. It is also necessary for optimal operational plan of the power system planning. In particular, in order to ensure stable power supply, long-term load forecasting is important. And regional load forecasting is important for tightening supply stability. Regional load forecasting is known to be an essential process for the optimal state composition and maintenance of the electric power system network including transmission lines and substations to meet the load required for the area. Therefore, in this paper we propose a forecasting method using SARIMA during the 12 months (long-term/mid-term) load forecasting by 16 regions of the South Korea.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2255-2260
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• 2007

This Paper focuses on modeling and simulation to analyze the characteristic of hybrid vehicle. The system includes proton exchange membrane fuel cell(PEMFC), photovoltaic generator(PV), lead-acid battery, motor, vehicle and controller. Main electricity is produced by the PEMFC and battery to meet the requirements of a user load. When vehicle is parked in a sunny place, extra power is generated by the photovotaics and is charged in a battery for next drive. Further we evaluate usefulness of this hybrid vehicle by using ADVISOR - the advanced vehicle simulator written in the Matlab/Simulink environment. According to simulation results, the extra power obtained by photovoltaics which have been explored in nature conditions can help to reduce the electrical load of PEMFC and increase the efficiency (over 30%).

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.7
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• pp.9-19
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• 2010

Fuel cell (FC) distributed generation (DG) is gradually becoming more attractive to mainstream electricity users as capacity improves and costs decrease. New technologies including inverters are becoming available to provide a uniform standard interconnection of DGs with an electric power system. Some of the operating conflicts and the effect of DG on power quality are addressed and investigated through simulations on a real distribution network with an FC power plant. The results of these simulations have proved load tracking capability following the real and reactive power change of the load and have shown the flow of overcurrent from an FC power plant during the ground fault of a distribution line.

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

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2157-2165
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• 2017

This study deals with the design of the mechanism in which demand response (DR) resources are traded in the power generation market. In general, a DR aggregator (DRA), which extends DR resources and provides technical support, is central to this mechanism. In this study, power users, called DR customer (DRC), participate in load reduction and are also modeled to participate directly in DR-related bidding. The DRA provides incentives to the DRC, indirectly impacting the market, and the DRC use the bid parameters strategically. We present the conditions for finding Nash Equilibrium (NE) in game problems of various participants including market operators, and analyze the characteristics of DRA and DRC related models. It also analyzes the impact of the participants on the market according to various types of competition and coalitions between DRA and DRC.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.792-794
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• 2005

최근에 들어서 전력산업에 규제완화가 도입되면서 환경이 급변하고 있는 실정이다. 여러 가지의 환경변화가 예상되지만, 그 중에서도 공급자간에 경쟁도입이 전력산업 참여자간에 주요 이슈로 부상하고 있다. 이와 같은 변화는 전력시스템의 기술 개발 뿐만 아니라 경영전략에도 큰 영향을 미치고 있으며, 대 수요자 서비스의 제공이 전략의 핵심이 되고 있다. 따라서 공급자는 보다 나은 서비스를 제공하기 위해서, 수요자 정보의 수집 및 분석을 해야 할 필요가 있다. 본 논문에서는 전력 수요자의 부하 특성을 분석하고 평가하기 위하여 수요특성별로 그룹으로 분류하는 방법을 개발하고, 분류된 그룹의 특징을 분석하였다. 이와 같은 부하분석의 정보는 가격설계, 수요 및 에너지 예측, 송전 및 배전계획, 에너지 효율 향상 및 부하관리의 필수 자료가 된다. 또한 향후에 개발될 전력 부가서비스의 주요 기반이 될 것으로 예상된다.