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Abstract: During the last few decades, energy planning has focused on meeting domestic demand at lower total costs. However, global warming and the shared recognition of it have transformed the problem of energy planning into a more complex task with a greater number of issues to be considered. Since the key issue is to reduce greenhouse effects, governments around the world have begun to make investments in renewable energy systems (e.g., hydro, wind, solar, and/or biomass power). The relatively high costs of renewable energy systems and the uncertain outlook of their rate of diffusion in the market make it difficult to heavily rely on them. The uncertain variations in production cost over time are especially challenging. To handle uncertainties, the concept of the learning rate was adopted in this study so as to compute the costs of energy systems in the future and Monte Carlo simulation was performed. The aim of this study was to optimize plans of conventional and prospective renewable energy systems with respect to production cost. The production cost included capital, fixed, variable, and external costs. For the case study, the energy situation in South Korea was used. The results of the case study where the proposed methodology was applied could provide useful insights economically and strategies of sustainable energy management for ambiguous environments. [Copyright &y& Elsevier]

Abstract: This paper studies economics of renewable energy systems with consideration of future prospects on costs and uncertain external conditions that may affect competitiveness in the power plant market. The concept of learning curve is adopted to compute estimates on the costs of installing and operating renewable energy systems in the future; fuel costs and carbon price are modeled as scenario-dependent variables to analyze their impact on total costs under different scenarios. The proposed approach allows evaluation and comparison of total costs necessary in implementing renewable energy plans under varying technological, and/or economical conditions that face uncertainty at present. Moreover, analyzing the evaluation results further with techniques like sensitivity analysis can identify factors central to reducing the total costs. As an illustrative case-study, the Korean government’s renewable energy plan has been evaluated accordingly, under three different scenarios defined by International Energy Agency (IEA). The evaluation results indicate minor changes in total costs of achieving the plan among three scenarios, mainly due to counterbalancing between the price of fossil fuels and carbon price. Further analyses revealed factors central to lowering the total costs necessary in implementing the plan—hybridization between renewable energy systems, reduction of biomass production costs via technological innovation, increasing learning rates by focusing on R&D and international cooperation. [Copyright &y& Elsevier]

Abstract: In this paper, a new approach has been proposed that allows a robust optimization of sustainable energy planning over a period of years. It is based on the modified energy flow optimization model (EFOM) and minimizes total costs in planning capacities of power plants and CCS to be added, stripped or retrofitted. In the process, it reduces risks due to a high volatility in fuel prices; it also provides robustness against infeasibility with respect to meeting the required emission level by adopting a penalty constant that corresponds to the price level of emission allowances. In this manner, the proposed methodology enables decision makers to determine the optimal capacities of power plants and/or CCS, as well as volumes of emissions trading in the future that will meet the required emission level and satisfy energy demand from various user-sections with minimum costs and maximum robustness. They can also gain valuable insights on the effects that the price of emission allowances has on the competitiveness of RES and CCS technologies; it may be used in, for example, setting appropriate subsidies and tax policies for promoting greater use of these technologies. The proposed methodology is applied to a case based on directions and volumes of energy flows in South Korea during the year 2008. [Copyright &y& Elsevier]