• Environmental and Resource Economics Review
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• v.31 no.3
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• pp.393-417
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• 2022

Using hourly SMP data from 2016 to 2020, this paper measures the weekly realized volatility and investigates the main force of its determinants. To this end, we extend the Bayesian variable selection by incorporating the regime-switching model which identifies important variables among a large number of predictors by regimes. We find that the increase in coal and nuclear generation, as well as solar power, reinforce the SMP volatility in both high volatility and low volatility regime. In contrast the increase in gas generation and gas price decrease SMP volatility when SMP volatility is high. These results suggest that the expansion of renewable energy according to 2050 Carbon Neutrality or energy transition policies increases SMP volatility but the increase in the gas generation or reduction of coal generation might offset its impact.

• Korean Chemical Engineering Research
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• v.50 no.3
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• pp.479-491
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• 2012

In this paper we performed evaluation of the economics of a district heating system (DHS) consisting of energy suppliers and consumers, heat generation and storage facilities and power transmission lines in the capital region, as well as identification of optimal operating conditions. The optimization problem is formulated as a mixed integer linear programming (MILP) problem where the objective is to minimize the overall operating cost of DHS while satisfying heat demand during 1 week and operating limits on DHS facilities. This paper also propose a new forecasting model of the system marginal price (SMP) using past data on power supply and demand as well as past cost data. In the optimization, both the forecasted SMP and actual SMP are used and the results are analyzed. The salient feature of the proposed approach is that it exhibits excellent predicting performance to give improved energy efficiency in the integrated DHS.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.3
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• pp.144-151
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• 2005

This paper presents a forecasting technique of the short-term marginal price (SMP) using an Artificial Neural Network (ANN). The SW forecasting is a very important element in an electricity market for the optimal biddings of market participants as well as for market stabilization of regulatory bodies. Input data are organized in two different approaches, time-axis and day-axis approaches, and the resulting patterns are used to train the ANN. Performances of the two approaches are compared and the better estimate is selected by a composition rule to forecast the SMP. By combining the two approaches, the proposed composition technique reflects the characteristics of hourly, daily and seasonal variations, as well as the condition of sudden changes in the spot market, and thus improves the accuracy of forecasting. The proposed method is applied to the historical real-world data from the Korea Power Exchange (KPX) to verify the effectiveness of the technique.

• Environmental and Resource Economics Review
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• v.31 no.4
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• pp.645-668
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• 2022

Hydrogen energy is emerging as an important means of carbon neutrality in the various sectors including power, transportation, storage, and industrial processes. Fuel cell power plants are the fastest spreading in the hydrogen ecosystem and are one of the key power sources among means of implementing carbon neutrality in 2050. However, high volatility in system marginal price (SMP) and renewable energy certificate (REC) prices, which affect the profits of fuel cell power plants, delay the investment timing and deployment. This study applied the real option methodology to analyze how the dual uncertainties in both SMP and REC prices affect the investment trigger price level in the irreversible investment decision of fuel cell power plants. The analysis is summarized into the following three. First, under the current Renewable Portfolio Standard (RPS), dual price uncertainties passed on to plant owners has significantly increased the investment trigger price relative to one under the deterministic price case. Second, reducing the volatility of REC price by half of the current level caused a significant drop in investment trigger prices and its investment trigger price is similar to one caused by offering one additional REC multiplier. Third, investment trigger price based on gray hydrogen and green hydrogen were analyzed along with the existing byproduct hydrogen-based fuel cells, and in the case of gray hydrogen, economic feasibility were narrowed significantly with green hydrogen when carbon costs were applied. The results of this study suggest that the current RPS system works as an obstacle to the deployment of fuel cell power plants, and policy that provides more stable revenue to plants is needed to build a more cost-effective and stable hydrogen ecosystem.

• Current Photovoltaic Research
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• v.5 no.3
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• pp.100-104
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• 2017

This paper analyzes the correlation between Net Benefit Test (NBT) and System marginal price (SMP), which has a significant impact on the allocation of demand response (DR) resources in resource scheduling and commitment (RSC) process, based on the performance data of the demand resource market which has been established in 2014. Demand resources compete with generation resources in the RSC process, and it is prescribed to use demand resources only when net benefit occurs. Analysis result shows that the larger the SMP than the Net Benefit Threshold Price (NBTP), the more the winning bid of demand response resource was. It is interpreted that the introduction of NBT in DR market is justified. The demand resource market has been steadily growing. It is required to expand the scope of resources up to the small-sized DR, and to expand the functionalities of demand resources not only in the current energy market but also in the reserve market in the future. In order for that, institutional improvements are required.

• New & Renewable Energy
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• v.10 no.1
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• pp.41-49
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• 2014

For a proper valuation of wind power project, it is necessary to consider volatilities of key parameters such as annual energy production, electricity sales price, and long term interest rate. Real option methodology allows to calculate option values of these parameters. Volatilities to be considered in wind project valuation are 1) annual energy production (AEP) estimation due to meteorological variation and estimation errors in wind speed distribution, 2) changes in system marginal price (SMP), and 3) interest rate fluctuation of project financing which provides refinancing option to be exercised during a loan tenor for commercial scale projects. Real option valuation turns out to be more than half of the sales value based on a case study for a FIT scheme wind project that was sold to a financial investor.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.83-86
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• 2008

정부는 2006년 8월 기존의 발전차액 지원제도를 개정하여 발전차액 기준가격 지원대상 확대, 적용기간의 15년 단일화, 수력, 바이오에너지는 고정요금과 변동요금 중에서 선택할 수 있는 선택권 부여, 기술발전에 따라 태양광, 풍력, 연료전지는2-3년간의 유예기간 이후 매년 감소율을 적용하여 기준가격을 낮추는 등 많은 제도개선 내용을 반영하였다. 2006년 10월부터 개정된 발전차액 지원제도가 시행된 이후 태양광, 풍력의 신규진입이 대폭 증가하였고 수력, LFG, 바이오가스는 대부분 변동요금을 신청하였으며 2007년 집행된 신재생에너지 발전차액 기반기금의 55% 이상이 태양광발전에 지급되는 편중현상의 영향이 나타났다. 따라서 변동요금 설계시보다 SMP 평균이 22원 이상 높아져 변동요금의 재설계, 태양광 발전의 기반기금규모가 55% 이상을 점유하고 있으며 향후 더욱 심화될 예정이므로 특정전원의 기반기금 점유비중 제한 및 최근 수년간 준공된 신재생에너지의 운영실적을 분석하고 법적요건을 상세히 검토하여 투자비, 운영비, 이용률등을 재조정하여 기준가격을 합리적으로 개정하여 제2의 신재생에너지 도약기를 마련해야 할 것이다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.168-175
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• 2020

Recently, there has been an increasing need to expand the supply of renewable energy as a solution to greenhouse gas emissions. Therefore, as a measure to promote domestic renewable energy investment and gradual expansion, this study analyzed the investment value of renewable energy projects utilizing the unoccupied spaces of public enterprise's facilities and presented a strategic decision-making framework to support efficient national land development and government measures. The NPV was estimated to be 286 million won if the expansion of the facility was not considered, but it is reasonable to postpone the expansion decision because the value of -130 million won was calculated if the expansion was considered. On the other hand, the real-option value was estimated to be 444 million won, taking SMP uncertainty, expansion, and abandonment options into account, and an additional value of 288 million won was calculated from an analysis of the expansion project using the existing NPV analysis.