• Journal of Korean Institute of Industrial Engineers
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• v.39 no.3
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• pp.183-191
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• 2013

We address the power generation mix problem that considers not only nuclear and fossil fuels such as oil, coal and LNG but also renewable energy technologies. Unlike nuclear or other generation technologies, the expansion plan of renewable energy is highly uncertain because of its dependency on the government policy and uncertainty associated with technology improvements. To address this issue, we conduct a delphi survey and forecast the capacity of renewable energy. We further propose a stochastic mixed integer programming model that determines an optimal capacity expansion and the amount of power generation using each generation technology. Using the proposed model, we test eight generation mix scenarios and particularly evaluate how much the expansion of renewable energy contributes to the total costs for power generation in Korea. The evaluation results show that the use of renewable energy incurs additional costs.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.3
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• pp.135-150
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• 2012

This paper presents a portfolio model for a long-term power generation mix problem. The proposed portfolio model evaluates generation mix by considering the tradeoffs between the expected cost for power generation and its variability. Unlike conventional portfolio models measuring variance, we introduce Conditional Value-at-Risk (CVaR) in designing the variability with aims to considering events that are enormously expensive but are rare such as nuclear power plant accidents. Further, we consider uncertainties associated with future electricity demand, fuel prices and their correlations, and capital costs for power plant investments. To obtain an objective generation by each energy source, we employ the sample average approximation method that approximates the stochastic objective function by taking the average of large sample values so that provides asymptotic convergence of optimal solutions. In addition, the method includes Monte Carlo simulation techniques in generating random samples from multivariate distributions. Applications of the proposed model and method are demonstrated through a case study of an electricity industry with nuclear, coal, oil (OCGT), and LNG (CCGT) in South Korea.

• Journal of Energy Engineering
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• v.24 no.1
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• pp.164-171
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• 2015

Although coal-fired power generation has played a role as base load unit, it has incurred various social costs in the process of generating and providing electricity. It is necessary to extend the proportion of low-carbon power generations, and reduce the ratio of coal-fired power generation to cope with global climate changes. This study, therefore, attempts to estimate the public's willingness-to-pay (WTP) for substitution of supplied electricity from hydro-electricity generation, a representative renewable energy, for coal-fired power generation. To this end, we apply the contingent valuation (CV) method, widely used technique when valuing non-market goods, to elicit the public's WTP. In addition, a spike model is employed to consider zero WTPs. After the empirical analysis with 1,000 households CV survey data, the results show that mean household's WTP for replacing supplied electricity from hydro-electricity generation with coal-fired power generation is estimated to be about 54 KRW per kWh. The results of this study are expected to contribute to determining energy-mix and provide benefit information of hydro-electricity generation.

• Journal of Energy Engineering
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• v.26 no.3
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• pp.51-63
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• 2017

Paris Agreement on Climate Change(2015) requires to reduce the greenhouse gas emission. One of the responses to the requirement is to change the proportion of power generation, which is summarized to the decrease in thermal power and the increase in new and renewable power. This article conducts a comparative analysis on the economic effects between thermal- and new and renewable- power generations, using the Input-Output Table from The Bank of Korea. The results of this analysis show that the new and renewable power generation has got the larger effects in production-inducing, value-added-inducing, employment-inducing, and supply-shortage scopes, while the smaller effect in price-pervasive scope than the thermal power generation. According to these results, the complex consideration should be taken into when the changes in power generation mix are tried. Especially, the political efforts to reduce the supply-shortage effect of new and renewable power and the price-pervasive effect of thermal power will be important.