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H 2 is an important commodity chemical that can also be used as an alternative fuel. The way how H 2 is currently produced and distributed, however, is not compatible with this usage. This is primarily due to the high costs associated with storing and delivering H 2 from the centralized production facilities to the end-use sites like H 2 stations that will be distributed throughout a region. Here, we propose a methodology for configuring the distributed H 2 production system that minimizes the overall cost in delivering H 2 to demand sites while meeting the safety requirements. The methodology also takes into account changes in costs with respect to production volume by applying the concept of economy of scale. The proposed methodology is applied to a hypothetical case involving H 2 supply to three stations. The results demonstrate significant reduction in the overall cost when adopting the optimal solution found by our methodology compared to the traditional, centralized production system. Insights on the cost structures associated with producing and delivering H 2 are provided, as well as specific improvements required to make H 2 affordable at the level defined by the international society. • A new methodology for configuring sizes and layout of distributed H 2 production system. • Comparative analysis between the centralized and distributed H 2 production system. • Costs of various H 2 production technologies and sensitivity analyses of key parameters. [ABSTRACT FROM AUTHOR]

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]