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The chapter defines ´energy democracy´ and provides arguments for citizens´energy. It approaches the topic from the perspective of social innovation, investigating the question how energy cooperatives could become agents of a sustainable transition in Luxembourg.

Increasing consumption of fossil energy resources, which has become a general problem of our world, has led to researches on renewable energy sources as an alternative in developed and developing countries. In this article, the integration problems of population, economy, state politics and solar-based renewable energy production that affect the energy production and consumption of developed and developing countries have been addressed. In this study, the total electricity consumption and production in China, India, USA, Germany and Turkey along with the renewable energy and the value of solar energy in electricity production are considered. Among the countries discussed in the study, the share of electricity production of renewable energycan be seen in light of these data that Turkey has the highest values with 32%. Turkey is followed by Germany with 30%, China with 24%, India with 15% and US with 13%.

Modern life depends on fossil fuels, an unrenewable resource, continually being depleted. As a result, developing viable alternatives is necessary. Pyrolysis, a thermochemical process using high temperatures to decompose organic matter in the absence of oxygen, has been highlighted as a possible solution. This study aimed to evaluate the effect of particle size, peak temperature and the addition of the Cu-SrO/ZSM-5 catalyst on the quality of bio-oil produced from sugarcane bagasse feedstock. The bagasse was sieve-separated into four size classes: <425 μm, <600 μm, <2.36 mm, and Raw (unseparated). Each size fraction was evaluated for baseline physical and chemical properties and applicability to pyrolytic bio-oil generation. Thermal gravimetric analysis (TGA) and scanning electron microscopy were performed on the bagasse feedstock to understand its physical and thermal properties better. TGA was used to understand the thermal decomposition of the sugarcane bagasse with and without catalyst influence, as well as to study the bagasse kinetic properties. Pyrolysis gas chromatography mass spectrometry (Py-GC/MS) was performed on catalytic and non-catalytic samples to evaluate the chemical product distribution. The quality of the bio-oil is based on maximising hydrocarbons and minimising the concentration of oxygenated compounds in the yield. Fibrous rind presents better quality bio-oil, and the inclusion of a catalyst greatly increases the concentration of hydrocarbons. The calorific value of the bio-oil was approximately 34.15 MJ kg–1 compared to 14.8 ± 0.4 MJ kg–1 of the feedstock bagasse. Therefore, the sugarcane bagasse's energy density was increased through application of pyrolytic decomposition. This study presents valuable implications on the Australian sugar industry as a way to increase the potential profit from bagasse assets and increase the domestic availability of liquid fuels.

none ; 2 ; Authors: Ruti P.M., De Felice M. ; In the energy sector climate information can play a strategic role, particularly in hot spot regions such as the Mediterranean region. In order to limit GHG emissions, within the European Union framework there will be opportunities for trading renewable energy quotas among member states and to gain credit for electricity imported from renewable sources in countries outside the European Union. This framework will trigger new strong interaction between climate information providers and energy sector stakeholders. The basic assumption of this perspective, of course, is that a prediction of climate on multi-decadal time scales is attainable. © 2013 Elsevier Inc. All rights reserved. ; none ; 10840/5007 ; De Felice, M. ; De Felice, M.; Ruti, P. M.

The controversy over energy‐production risks is in part due to uncertainties and disagreements over the specification of these systems and their characteristics and in part due to the lack of a solid conceptual framework for comparisons between qualitatively different types of risks. The difficulties in specifying energy risks arise primarily from the necessity of using oversimplified descriptions of energy systems and their effects. The major simplifications include the use of marginal analysis (even when inappropriate), the omission of indirect risks, and the incorrect specification of the systems to be analyzed. Comparisons between qualitatively different risks are hampered by the lack of a solid basis for treating occupational risks relative to public risks, catastrophic risks versus chronic risks, and risks distributed differently in time. The difficult problems encountered when social values relating to risk change rapidly lead to delay and indecision. The choice of analytical simplifications and the specification of values systems for energy analysis are best made by considering the context and application of the analysis.

High Performance Computing (HPC) resources have become the key actor for achieving more ambitious challenges in many disciplines. In this step beyond, an explosion on the available parallelism and the use of special purpose processors are crucial. With such a goal, the HPC4E project applies new exascale HPC techniques to energy industry simulations, customizing them if necessary, and going beyond the state-of-the-art in the required HPC exascale simulations for different energy sources. In this paper, a general overview of these methods is presented as well as some specific preliminary results. ; The research leading to these results has received funding from the European Union's Horizon 2020 Programme (2014-2020) under the HPC4E Project (www.hpc4e.eu), grant agreement n° 689772, the Spanish Ministry of Economy and Competitiveness under the CODEC2 project (TIN2015-63562-R), and from the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP). Computer time on Endeavour cluster is provided by the Intel Corporation, which enabled us to obtain the presented experimental results in uncertainty quantification in seismic imaging ; Postprint (author's final draft)

High Performance Computing (HPC) resources have become the key actor for achieving more ambitious challenges in many disciplines. In this step beyond, an explosion on the available parallelism and the use of special purpose processors are crucial. With such a goal, the HPC4E project applies new exascale HPC techniques to energy industry simulations, customizing them if necessary, and going beyond the state-of-the-art in the required HPC exascale simulations for different energy sources. In this paper, a general overview of these methods is presented as well as some specific preliminary results. ; The research leading to these results has received funding from the European Union's Horizon 2020 Programme (2014-2020) under the HPC4E Project (www.hpc4e.eu), grant agreement n° 689772, the Spanish Ministry of Economy and Competitiveness under the CODEC2 project (TIN2015-63562-R), and from the Brazilian Ministry of Science, Technology and Innovation through Rede Nacional de Pesquisa (RNP). Computer time on Endeavour cluster is provided by the Intel Corporation, which enabled us to obtain the presented experimental results in uncertainty quantification in seismic imaging ; Postprint (author's final draft)