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Summary: This paper is concerned with innovative approaches to renewable energy sources computation methodologies, which provide more refined results than the classical alternatives. Such refinements provide additional improvements especially for replacement of fossil energy usages that emit greenhouse gas (GHG) into the atmosphere leading to climate change impact. Current knowledge gap among each renewable energy source calculation is rather missing fundamentals of plausible, rational, and logical explanations for the interpretation of results. In the literature, there are rather complicated and mechanically applicable methodologies, which require input and output measurement data match with missing physical explanations. The view taken in this review paper is to concentrate on quite plausible, logical, rational, and effectively applicable innovative energy calculation methodologies with simplistic fundamentals. For this purpose, a set of renewable energy methodological approaches is revisited with their innovative structures concerning solar, wind, hydro, current, and geothermal energy resources. With the increase in the renewable energy utilizations to combat the undesirable impacts of global warming and climate change, there is a need for better models that will include physical environmental conditions and data properties in the probabilistic, statistical, stochastic, logical, and rational senses leading to refined and more reliable estimations with application examples in the text. Finally, new research directions are also recommended for more refined innovative energy system calculations. [ABSTRACT FROM AUTHOR]

SUMMARY For several years recently, the price of oil has fluctuated due to the weak US dollar and financial risks. In particular, the WTI crude oil price reached $147 per barrel in July of 2008, which is the highest price thus far. An awareness of an impending crisis and concern over climate change are driving an increase in R&D for alternative energy sources instead of fossil-based energy. However, the researches based on traditional method show negative options about the economic value of new and renewable energy. This paper evaluates the value of new and renewable energy through a real option method which considers the uncertainty associated with fossil energy and the uncertainty of the success of R&D. The evaluating model assumes that the fossil energy price follows a geometric mean reverting process and that the probability of success with R&D on renewal forms of energy follows a binomial probability model. The model considers four options: the option to continue R&D, the option to delay R&D, the option to deploy R&D, and the option to abandon R&D. Finally, the value of Korean R&D on renewal forms of energy is analyzed by the model. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: Energy conversion systems have assumed a crucial role in current society. The threat of climate change, fossil fuel depletion and the growing world energy demand ask for a more sustainable way of electricity production, eg, by using renewable energy sources, by improving the conversion efficiency and/or by controlling power plant emissions. Despite the relationship between exergy and sustainability stated in literature, exergy losses are usually not considered when comparing systems and energy sources for power generation. The exergetic sustainability assessment method named Total Cumulative Exergy Loss (TCExL) has been used to assess several systems for electricity production, ie, a coal‐fired power plant, a coal‐fired power plant including carbon capture and storage, a biomass‐fired power plant, an offshore wind farm and a photovoltaic park. The results of the TCExL method have been compared with an environmental sustainability indicator, ie, the overall ReCiPe endpoint indicator and the economic indicator named Present Worth Ratio. The offshore wind farm is the best system from the exergetic and environmental point of view. The photovoltaic park is the system with the second‐best scores. However, from the economic viewpoint including subsidy by the Dutch government, the photovoltaic park performs better than the wind farm system and the system that performs best is the biomass‐fired power plant. Without subsidy, only the coal‐fired power plant without carbon capture and storage is profitable. The exergetic sustainability scores of the coal‐fired and biomass‐fired power plants are similar, but from the environmental sustainability viewpoint, the biomass‐fired power plant performs better than both coal‐fired power plants. As the results of environmental and economic sustainability assessments strongly depend on models, weighting factors, subsidy, market prices, etc, while the results of the exergetic sustainability assessment do not, it is recommended that the exergetic sustainability be taken into account when assessing the sustainability of power generation and other technological systems. [ABSTRACT FROM AUTHOR]

SUMMARY In this study, an integrated community-scale energy model (ICEM) was developed for supporting renewable energy management (REM) systems planning with the consideration of changing climatic conditions. Through quantitatively reflecting interactive relationships among various renewable energy resources under climate change, not only the impacts of climate change on each individual renewable energy but also the combined effects on power-generation sector from renewable energy resources could be incorporated within a general modeling framework. Also, discrete probability levels associated with various climate change impacts on the REM system could be generated. Moreover, the ICEM could facilitate capacity-expansion planning for energy-production facilities within a multi-period and multi-option context in order to reduce energy-shortage risks under a number of climate change scenarios. The generated solutions can be used for examining various decision options that are associated with different probability levels when availabilities of renewable energy resources are affected by the changing climatic conditions. A series of probability levels of hydropower-, wind- and solar-energy availabilities can be integrated into the optimization process. The developed method has been applied to a case of long-term REM planning for three communities. The generated solutions can provide desired energy resource/service allocation and capacity-expansion plans with a minimized system cost, a maximized system reliability and a maximized energy security. Tradeoffs between system costs, renewable energy availabilities and energy-shortage risks can also be tackled with the consideration of climate change, which would have both positive and negative impacts on the system cost, energy supply and greenhouse-gas emission. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]