• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.289-291
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• 2000

In a competitive electricity power market, the price of electricity changes instantly, that of conventional market is predetermined and hardly changes. In such a new environment, customers' behaviors change instantly according to the changing electricity prices. If we develop a electricity load model that well describes the behavior of electricity consumers, we can utilize that model in forecasting the amount of future load, solving the load flow problem and finding the weak point of the system. In this paper new electricity model that considers the price of electricity and power factor of the load is presented. While conventional load model, which is demand function of electricity, uses the price of real and reactive power as the independent variable of the demand function. this new load model uses price of real power and penalty factor according to the power factor for the calculation of amount of electricity demand.

• Nuclear Engineering and Technology
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• 제56권5호
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• pp.1654-1666
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• 2024

The goal of this research is to propose a way to maximize small modular reactor (SMR) utilization to gain better market feasibility in support of carbon neutrality. For that purpose, a comprehensive tool was developed, combining off-design thermohydraulic models, economic objective models (levelized cost of electricity, annual profit), non-economic models (saved CO2), a parameter input sampling method (Latin hypercube sampling, LHS), and a multi-objective evolutionary algorithm (Non-dominated Sorting Algorithm-2, NSGA2 method) for optimizing a SMR-combined heat and power cycle (CHP) system design. Considering multiple objectives, it was shown that NSGA2+LHS method can find better optimal solution sets with similar computational costs compared to a conventional weighted sum (WS) method. Out of multiple multi-objective optimal design configurations for a 105 MWe design generation rating, a chosen reference SMR-CHP system resulted in its levelized cost of electricity (LCOE) below $60/MWh for various heat prices, showing economic competitiveness for energy market conditions similar to South Korea. Examined economic feasibility may vary significantly based on CHP heat prices, and extensive consideration of the regional heat market may be required for SMR-CHP regional optimization. Nonetheless, with reasonable heat market prices (e.g. district heating prices comparable to those in Europe and Korea), SMR can still become highly competitive in the energy market if coupled with a CHP system.

• 대한산업공학회지
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• 제39권1호
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• pp.30-45
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• 2013

Predicting monthly electricity price has been a significant factor of decision-making for plant resource management, fuel purchase plan, plans to plant, operating plan budget, and so on. In this paper, we propose a sophisticated prediction model in terms of the technique of modeling and the variety of the collected variables. The proposed model hybridizes the semi-supervised learning and the artificial neural network algorithms. The former is the most recent and a spotlighted algorithm in data mining and machine learning fields, and the latter is known as one of the well-established algorithms in the fields. Diverse economic/financial indexes such as the crude oil prices, LNG prices, exchange rates, composite indexes of representative global stock markets, etc. are collected and used for the semi-supervised learning which predicts the up-down movement of the price. Whereas various climatic indexes such as temperature, rainfall, sunlight, air pressure, etc, are used for the artificial neural network which predicts the real-values of the price. The resulting values are hybridized in the proposed model. The excellency of the model was empirically verified with the monthly data of electricity price provided by the Korea Energy Economics Institute.

• 한국태양에너지학회 논문집
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• 제36권1호
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• pp.63-73
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• 2016

How effectively a wind farm captures high market prices can greatly influence a wind farm's viability. This research identifies and creates an understanding of the effects that result in various capture prices (average revenue earned per unit of generation) that can be seen among different wind farms, in the current and future competitive SMP (System Marginal Price) market in South Korea. Through the use of a neural network to simulate changes in SMP caused by increased renewables, based on the Korea Institute of Energy Research's extensive wind resource database for South Korea, the variances in current and future capture prices are modelled and analyzed for both onshore and offshore wind power generation. Simulation results shows a spread in capture price of 5.5% for the year 2035 that depends on both a locations wind characteristics and the generations' correlation with other wind power generation. Wind characteristics include the generations' correlation with SMP price, diurnal profile shape, and capacity factor. The wind revenue cannibalization effect reduces the capture price obtained by wind power generation that is located close to a substantial amount of other wind power generation. In onshore locations wind characteristics can differ significantly/ Hence it is recommended that possible wind development sites have suitable diurnal profiles that effectively capture high SMP prices. Also, as increasing wind power capacity becomes installed in South Korea, it is recommended that wind power generation be located in regions far from the expected wind power generation 'hotspots' in the future. Hence, a suitable site along the east mountain ridges of South Korea is predicted to be extremely effective in attaining high SMP capture prices. Attention to these factors will increase the revenues obtained by wind power generation in a competitive electricity market.

• 자원ㆍ환경경제연구
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• 제29권4호
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• pp.499-520
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• 2020

우리나라 제조업 부문의 상대적 전력투입비율은 OECD 국가들에 비해 높은 편이며 이는 전력가격이 OECD 평균보다 상대적으로 낮은 데에 기인한다. 또한 전력부문은 한국에서 온실가스 배출의 상당한 비중을 점유하고 있는데, 2018년 기준으로 전력생산의 투입연료로 석탄과 천연가스가 41.9%와 26.8%를 차지하기 때문이다. 따라서 우리나라 제조 부문에서 전력가격을 인상할 필요가 있으나 중소기업이 대기업보다 상대적으로 더 많은 영향을 받을 것이라는 우려가 있다. 본 연구는 시간가변적 파라메터 모형인 Kalman Filter 추정법을 이용하여 철강산업에서 대기업과 중소기업 전력수요의 가격 탄력성과 산출 탄력성을 추정하였다. 분석 결과, 기업의 크기에 상관없이 산출량 변화가 가격변화보다 전력수요에 더 많은 영향을 미치는 것으로 나타났다. 또한 대기업에서 전력수요에 대한 가격탄력성뿐만 아니라 산출탄력성의 분산이 중소기업보다 더 큰 것으로 추정되었다. 정책적 함의는 철강산업과 같은 에너지다소비 업종에서 어떻게 전력수요를 감축할 것인지에 관련되어 있다.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1460-1470
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• 2015

This paper presents an approach to solve the long-term generation expansion planning problem of the restructured electricity industry using an agent-based environment. The proposed model simulates the generation investment decisions taken by a particular agent (i.e. a generating company) in a market environment taking into account its competitors’ strategic investment. The investment decision of a particular company is modeled taking into account that such company has imperfect foresight on the future system development hence electricity prices. The delay in the construction of new plants is also explicitly modeled, in order to compute accurately the yearly revenues of each agent. On top of a conventional energy market, several capacity incentive mechanisms including capacity payment and capacity market are simulated, so as to assess their impact on the investment promotion for generation expansion. Results provide insight on the investment cycles as well as dynamic system behavior of long-term generation expansion planning in a competitive electricity industry.

• KIEE International Transactions on Power Engineering
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• 제5A권2호
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• pp.193-198
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• 2005

This paper proposes a new method to handle transmission line losses using loss distribution factors (LDF) rather than marginal loss factors (MLF) in electricity market operation. Under a competitive electricity market, the bidding data are adjusted to reflect transmission line losses. To date the most proposed approach is using MLFs. The MLFs are reflected to bidding prices and market clearing price during the trading and settlement of the electricity market. In the proposed algorithm, the LDFs are reflected to bidding quantities and actual generations/ loads. Computer simulations on a 9-bus sample system will verify the effectiveness of the algorithm proposed. Moreover, the proposed approach using LDFs does not make any payments residual while the approach using MLFs induces payments residual.

• KDI Journal of Economic Policy
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• 제41권1호
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• pp.43-58
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• 2019

Since 2009, electricity consumption has developed a unique seasonal pattern in South Korea. Winter loads have sharply increased, and they eventually exceeded summer peaks. This trend reversal distinguishes these load patterns from those in the USA and the EU, where annual peaks are observed during the summer months. Using Levene's test, we show statistical evidence of a rise in temperature but a decrease in variance over time regardless of the season. Despite the overall increase in the temperature, regardless of the season there should be another cause of the increased demand for electricity in winter. With the present study using data from 1991 to 2012, we provide empirical evidence that relatively low electricity prices regulated by the government have contributed significantly to the rapid upward change in electricity consumption, specifically during the winter months in the commercial sector in Korea.

• 전기학회논문지
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• 제62권10호
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• pp.1390-1396
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• 2013

The paper estimated the reasonable market price of lead-acid battery energy storage system (BESS) intended for demand management of electricity customers. As time-of-use (TOU) tariffs have extended to a larger number of customers and gaps in the peak and off-peak rates have gradually risen, deployment of BESS has been highly needed. However, immature engineering techniques, lack of field experiences and high initial investment cost have been barriers to opening up ESS markets. This paper assessed electricity cost that BESS operation could save for customers and, based on the possible cost savings, estimated reasonable prices at which BESSs could become a more prospective option for demand management of customers. Battery scheduling was optimized to maximize the electricity cost savings that BESS would possibly achieve under TOU tariffs conditions. Basic economic factors such as payback period and return on investment were calculated to determine reasonable market prices. Actual load data of 12 industrial customers were used for case studies.

• 자원ㆍ환경경제연구
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• 제22권3호
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• pp.547-580
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• 2013

상품 및 서비스 소비구조의 변경을 통해 에너지절약이 실현될 수 있기 때문에 가정부문의 간접 및 총 에너지소비를 추정할 필요가 있다. 가정부문의 직간접 에너지소비를 보다 정확히 추정하기 위해 본 연구는 기업과 소비자(가정부문) 간 석유제품 및 전력의 가격을 차별화하였다. 한국의 가정부문은 1995-2010년 기간 중 한국 1차 에너지소비 중 55% 이상을 소비하였다. 가정부문의 에너지소비 중 69% 이상이 간접 에너지소비였다. 따라서 가정부문의 직접뿐만 아니라 간접 에너지소비도 에너지절약의 대상이 되어야 한다. 전력 소비는 2009년 한국의 가정부문의 주 에너지소비가 되었다. 생활수준이 향상됨으로써 가정부문은 전력 원단위가 높은 상품과 서비스를 소비하게 되었다. 한국 가정부문이 소비하는 제품의 에너지 원단위가 낮아짐으로써, 에너지소비의 증가율이 감소하게 되었다. 반면에 한국 가정부문의 상품 및 서비스 소비구조는 에너지 다소비형으로 변경되어 오히려 에너지소비 증가를 가속시키는 결과를 초래함으로써, 구조효과는 악화되었다. 이에 따라 에너지정책은 에너지소비를 감소시키기 위해 소비자로 하여금 에너지 저소비형 재화와 용역을 소비하도록 유도하여야 한다. 에너지 저소비형 소비를 촉진시킬 수 있는 주요 수단인 에너지가격 현실화가 요구된다.