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http://dx.doi.org/10.7232/JKIIE.2013.39.3.183

Forecasting Renewable Energy Using Delphi Survey and the Economic Evaluation of Long-Term Generation Mix  

Koo, Hoonyoung (School of Business, Chungnam National University)
Min, Daiki (School of Business, Ewha Womans University)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.39, no.3, 2013 , pp. 183-191 More about this Journal
Abstract
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.
Keywords
Power Generations Mix; Renewable Energy; Delphi Survey; Economic Evaluation; Monte Carlo Simulation; Korea's Power Policy;
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Times Cited By KSCI : 2  (Citation Analysis)
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