1,720,970 research outputs found
Might future electricity generation suffice to meet the global demand?
Full text linkElectricity supply is one of the critical issues in the energy field. Due to the high shares of greenhouse gases emissions, the electricity sector is experiencing a transition towards a progressively wider use of low-carbon technologies. At the same time, electrification of end-use sectors is identified as one of the most suitable mitigation strategies, although requiring larger electricity production. This paper relates the historical development trends for installed capacity of electricity production technologies to the theory of the S-curves, building a method to depict plausible developments in the electricity sector. Projections are performed considering the existence of an upper limit for industrial capacity development, and according to a path envisaging a revolutionary, an evolutionary and a maturity phase for technologies showing considerable growth trends. Oppositely, stagnation is taken into account for those not showing any remarkable progress. The computed curves are used to perform forecasts about electricity generation potentials until 2050, showing how the projected growth trend of electricity generation technologies would result in a production sufficient to meet the expected global demand, even excluding the contribution of fossil fuels in some cases. In perspective, the presented method can be applied to retrieve maximum capacity constraints for energy system models
Projection of post-pandemic Italian industrial production through vector autoregressive models
No full textEnergy system models for the analysis of future scenarios are mainly driven by the set of energy service demands that define the broad outlines of socio-economic development throughout the model time horizon. Here, the long-term effects of the COVID-19 pandemic on the drivers of the industrial production in six energy-intensive subsectors are addressed using Vector AutoRegressive models. The model results are computed either considering or not considering the effects of the pandemic. The comparison to established pre-pandemic trends allows for validating the robustness of the selected model. The anticipated effect of the pandemic to 2040 shows a long-term reduction by 3% to 10%, according to the different subsector, in the industrial energy service demand. When the computed service demands are used as input to the TIMES-Italy model, which shows good capability to reproduce the energy consumption of the industrial sectors in the period 2006–2020, the impact of the pandemic on energy consumption forecasts can be assessed in a business-as-usual scenario. The results show how the long-term effects of the shock caused by the pandemic could lead, by 2040, to a total industrial energy consumption 5% lower than what was foreseen before the pandemic, while the energy mix remains almost unchanged
Can We Rely on Open-Source Energy System Optimization Models? The TEMOA-Italy Case Study
Full text linkEnergy system models have become crucial to assess the effectiveness of possible energy policies in pursuing the declared environmental objectives. Among bottom-up models, the tools most widely used by researchers and institutions to perform scenario analyses and policy evaluations rely on commercial software and closed databases, limiting the transparency of the studies. The purpose of this work is to demonstrate that open-source tools, relying on open databases, can be used as a valid alternative to commercial tools, getting equivalent results not only for simple case studies as done so far, but also for complex (national, regional, or multi-regional) reference energy systems. Working on the already available open TEMOA optimization framework, a bottom-up technology-rich model is developed here for the Italian reference energy system on an extended TEMOA version, comparable in detail and complexity to the equivalent TIMES framework. The accuracy of the novel TEMOA-Italy model in a business-as-usual scenario is assessed, showing that the average relative differences with respect to the consolidated TIMES-Italy results are in the order of few percent. The open-source model, available on Github, is now ready for the test and implementation of new optimization paradigms, which was not possible in the TIMES framework
Role of technology learning in the decarbonization of the iron and steel sector: An energy system approach using a global-scale optimization model
Full text linkThe iron and steel sector, characterized by fossil fuel-driven processes is one of the most difficult to decarbonize
and a significant source of greenhouse gas emissions. Various new technologies promise to change this, but
their development is highly uncertain. This paper aims to analyze the prospects of key low-carbon technologies
in the sector, focusing on the impact of technology learning, in the light of the uncertainty related to the
learning rate. An optimization energy system model was used with an iterative learning formulation, adopting
different learning assumptions. The results show that learning may have only a minor impact in the short
and medium term, reducing global carbon emissions of the sector by 3% (at most) in 2050, compared to a
non-learning scenario. In the long term, high learning potentials for novel processes are important, leading to
a market share of up to the 80% by the end of the century. The learning potential for Carbon Capture and
Storage processes, however, plays no role in the simulations. Early investments and research and development
can help unlock the full potential of the technologies, while more detailed studies should be performed to
better understand the retrofitting impact in the shorter term
Could clean industrial progresses and the rise of electricity demand foster the penetration of nuclear fusion in the European energy mix?
No full textThe effects of the update of the EUROfusion TIMES Model (ETM) industrial sector to account for the introduction of low-carbon technologies is presented and discussed in this work. ETM is a minimum-cost energy system model aimed at investigating the conditions for the introduction of nuclear fusion in the future electricity mix. The most interesting ETM long-run scenarios (until 2100) must comply with stringent environmental targets to pursue the Below-2-Degrees objective, identified in the Paris Agreement, allowing wide commercial adoption of innovative production processes - currently under test or research - which would almost completely replace well-established fossil-based industrial techniques in the iron and steel, chemicals, non-ferrous metals, non-metallic minerals and pulp and paper sub-sectors. Among them, low-carbon and electrolysis-based processes could open the way to a considerable increase of electricity demand, requiring also clean resources not to undermine sectoral efforts in becoming more environmentally sustainable, and the same does the implementation of CCS technologies. The study shows that the industrial sector contributes to the energy mix decarbonization by relying on CCS technologies, when available, or new low-carbon technologies. The progressive electrification of the industrial sector turns into an increasing final electricity demand which is covered by renewables and nuclear when stringent climate policies are put in place. Despite technological constraints are likely to slow down fusion deployment in the future, a range of scenarios show that nuclear fusion could contribute to generation of carbon-free electricity in the future European energy system
Analysis of the effects of electrification of the road transport sector on the possible penetration of nuclear fusion in the long-term european energy mix
Full text linkThe European Roadmap towards the production of electricity from nuclear fusion foresees the potential availability of nuclear fusion power plants (NFPPs) in the second half of this century. The possible penetration of that technology, typically addressed by using the global energy system EUROFusion TIMES Model (ETM), will depend, among other aspects, on its costs compared to those of the other available technologies for electricity production, and on the future electricity demand. This paper focuses on the ongoing electrification process of the transport sector, with special attention devoted to road transport. A survey on the present and forthcoming technologies, as foreseen by several manufacturers and other models, and an international vehicle database are taken into account to develop the new road transport module, then implemented and harmonized inside ETM. Following three different storylines, the computed results are presented in terms of the evolution of the road transport demand in the next decades, fleet composition and CO2emissions. The ETM results are in line with many other studies. On one hand, they highlight, for the European road transport energy consumption pattern, the need for dramatic changes in the transport market, if the most ambitious environmental goals are to be pursued. On the other hand, the results also show that NFPP adoption on a commercial scale could be justified within the current projection of the investment costs, if the deep penetration of electricity in the road transport sector also occurs
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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