Search

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 Photosynthetic H 2 production has been a compelling but elusive objective. Here we describe how coordinated bioreactor, metabolic pathway, and protein engineering now suggest feasibility for the sustainable, solar-powered production of a storable fuel to complement our expanding photovoltaic and wind based capacities. The need to contain and harvest the gaseous products provides decisive solar bioreactor design advantages by limiting O 2 exposure to prolific, but O 2 -sensitive H 2 producing enzymes—[FeFe] hydrogenases. CO 2 supply and cell growth can also be limited so that most of the photosynthetic reduction capacity is directed toward H 2 production. Yet, natural [FeFe] hydrogenases are still too O 2 sensitive for technology implementation. We report the discovery of new variants and a new O 2 tolerance mechanism that significantly reduce the sensitivity to O 2 exposure without lowering H 2 production rates or losing electrons to O 2 reduction. Testing the improved hydrogenases with a biologically derived, light-dependent electron source provides evidence that this game changing technology has the potential for sustainable large-scale fuel production. Highlights • A single Cys replacement improved O 2 tolerance with only a minor activity loss. • Saturation mutagenesis found synergistic, non-Cys mutations for improving O 2 tolerance. • Higher O 2 tolerance enabled more than 300% improvement in light-driven H 2 production. [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]

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]