• Energy Research
• Open Source close
• Embargo close
• US close
• IT close
• FR close

The lifetime and reliability of power transformers are primarily dependent on the hot-spot temperature in the windings, as temperature is the most important factor determining the insulation degradation rate. Key to removing the heat from the transformer is the radiator which must be carefully designed to keep the temperatures within limits under all operating conditions whilst minimizing the transformer size, weight and cost. This paper compares the analytical method used to predict the radiator performance with computational fluid dynamics (CFD) models in terms of heat dissipation. It is found that the analytical method and CFD models give similar results in the air natural (AN) cooling modes, whereas the analytical method overestimates the heat dissipation in the air forced (AF) cooling modes. Moreover, the thermal conduction effect in the radiator wall is investigated under different operating conditions and for different radiator sizes using the CFD models. The simulation results indicate that the radiator wall contributes to 6%-10% of the total heat dissipation under some circumstances and therefore should not be simply ignored in radiator models.

Modelling the economics of climate change is daunting. Many existing methodologies from social and physical sciences need to be deployed, and new modelling techniques and ideas still need to be developed. Existing bread-and-butter micro- and macroeconomic tools, such as the expected utility framework, market equilibrium concepts and representative agent assumptions, are far from adequate. Four key issues—along with several others—remain inadequately addressed by economic models of climate change, namely: (1) uncertainty, (2) aggregation, heterogeneity and distributional implications (3) technological change, and most of all, (4) realistic damage functions for the economic impact of the physical consequences of climate change. This paper assesses the main shortcomings of two generations of climate-energy-economic models and proposes that a new wave of models need to be developed to tackle these four challenges. This paper then examines two potential candidate approaches—dynamic stochastic general equilibrium (DSGE) models and agent-based models (ABM). The successful use of agent-based models in other areas, such as in modelling the financial system, housing markets and technological progress suggests its potential applicability to better modelling the economics of climate change.

Abstract As main contributors to greenhouse gas emissions, power and transportation are crucial sectors for energy system decarbonization. Their interaction is expected to increase significantly: plug-in electric vehicles add a new electric load, increasing grid demand and potentially requiring substantial grid upgrade; hydrogen production for fuel cell electric vehicles or for clean fuels synthesis could exploit the projected massive power overgeneration by intermittent and seasonally-dependent renewable sources via Power-to-Hydrogen. This work investigates the infrastructural needs involved with a broad diffusion of clean mobility, adopting a sector integration perspective at the national scale. The analysis combines a multi-node energy system balance simulation and a techno-economic assessment of the infrastructure to deliver energy vectors for mobility. The article explores the long-term case of Italy, considering a massive increase of renewable power generation capacity and investigating different mobility scenarios, where low-emission vehicles account for 50% of the stock. First, the model solves the energy balances, integrating the consumption related to mobility energy vectors and taking into account power grid constraints. Then, an optimal infrastructure is identified, composed of both a hydrogen delivery network and a widespread installation of charging points. Results show that the infrastructural requirements bring about investment costs in the range of 43–63 G€. Lower specific costs are associated with the exclusive presence of FCEVs, whereas the full reliance on BEVs leads to the most significant costs. Scenarios that combine FCEVs and BEVs lie in between, suggesting that the overall power + mobility system benefits from the presence of both drivetrain options.

The optical and photovoltaic properties of Si NCs / SiC multilayers (MLs) are investigated using a membrane-based solar cell structure. By removing the Si substrate in the active cell area, the MLs are studied without any bulk Si substrate contribution. The occurrence is confirmed by scanning electron microscopy and light-beam induced current mapping . Optical characterization combined with simulations allows us to determine the absorption within the ML absorber layer, isolated from the other cell stack layers. The results indicate that the absorption at wavelengths longer than 800 nm is only due to the SiC matrix. The measured short-circuit current is significantly lower than that theoretically obtained from absorption within the ML absorber, which is ascribed to losses that limit carrier extraction. The origin of these losses is discussed in terms of the material regions where recombination takes place. Our results indicate that carrier extraction is most efficient from the Si NCs themselves, whereas recombination is strongest in SiC and residual a-Si domains . Together with the observed onset of the external quantum efficiency (EQE) at 700-800 nm, this fact is an evidence of quantum confinement in Si NCs embedded in SiC on device level.

Abstract Latest trends in the photovoltaic sector see the use of innovative photovoltaic technologies with extended spectral responsivity ranging from 300 to 1200 nm for non-concentrating terrestrial applications, and to 1800 nm for concentrating PV and space applications. As a consequence, an update of the IEC 60904-9 standard is ongoing with a definition of new spectral ranges for the assessment of the spectral match. This poses new challenges to laboratories and research centers on whether or not they still are able to accurately measure the spectral mismatch of their sun simulator in the newly-defined spectral regions. Prior to that, there is a need to understand if the commercially available spectroradiometers are ready to extend their measurement range as prescribed by the forthcoming new standard. This paper analyses two options for an extension of the spectrum characterisation of solar simulators to 300–1200 nm and compares them in terms of spectral match of global normal irradiance (GNI) spectra acquired under natural sunlight by eight spectroradiometers during the 6th European Spectroradiometer Intercomparison. The acquired spectra are also compared in terms of an index of consistency of the spread of the measured spectra with the estimated measurement uncertainty, hereafter named as performance statistics E n . Results show that all investigated laboratories assure the equivalence of the spectral match classification well below the 25% limit corresponding to class-A simulators. When considering the more stringent class-A+ corresponding to a 12.5% limit, one of the two considered options that rearranges the 300–1200 nm spectral range into 6 bands appears to still assure the equivalence of the class A+ limits among considered instruments. The E n performance index analysis highlights some inconsistencies with the estimated measurement uncertainty or instrument drifts from the expected performance, and the need of further improvements in calibration, set up and measurement procedures.

The chemical and petrochemical sector is by far the largest industrial energy user, accounting for 30% of the industry's total final energy use. However, due to its complexity its energy efficiency potential is not well understood. This article analyses the energy efficiency potential on a country level if Best Practice Technologies (BPT) were implemented in chemical processes. Two approaches are applied and an improved dataset referring to Europe has been developed for BPT energy use. This methodology has been applied to 66 products in fifteen countries that represent 70% of chemical and petrochemical sector's energy use worldwide. The results suggest a global energy efficiency potential of 16% for this sector, excluding savings in electricity use and by higher levels of process integration, combined heat and power (CHP) and post-consumer plastic waste treatment. The results are more accurate than previous estimates. The results suggest significant differences between countries, but a cross-check based on two different methods shows that important methodological and data issues remain to be resolved. Further refinement is needed for target setting, monitoring and informing energy and climate negotiation processes. For the short and medium term, a combination of benchmarking and country level analysis is recommended.

The stability of winter wheat-flowering-date is crucial for ensuring consistent and robust crop performance across diverse climatic conditions. However, the impact of climate change on wheat-flowering-dates remains uncertain. This study aims to elucidate the influence of climate change on wheat-flowering-dates, predict how projected future climate conditions will affect flowering date stability, and identify the most stable wheat genotypes in the study region. We applied a multi-locus genotype-based (MLG-based) model for simulating wheat-flowering-dates, which we calibrated and evaluated using observed data from the Northern China winter wheat region (NCWWR). This MLG-based model was employed to project flowering dates under different climate scenarios. The simulated flowering dates were then used to assess the stability of flowering dates under varying allelic combinations in projected climatic conditions. Our MLG-based model effectively simulated flowering dates, with a root mean square error (RMSE) of 2.3 days, explaining approximately 88.5 % of the genotypic variation in flowering dates among 100 wheat genotypes. We found that, in comparison to the baseline climate, wheat-flowering-dates are expected to shift earlier within the target sowing window by approximately 11 and 14 days by 2050 under the Representative Concentration Pathways 4.5 (RCP4.5) and RCP8.5 climate scenarios, respectively. Furthermore, our analysis revealed that wheat-flowering-date stability is likely to be further strengthened under projected climate scenarios due to early flowering trends. Ultimately, we demonstrate that the combination of Vrn and Ppd genes, rather than individual Vrn or Ppd genes, plays a critical role in wheat-flowering-date stability. Our results suggest that the combination of Ppd-D1a with winter genotypes carrying the vrn-D1 allele significantly contributes to flowering date stability under current and projected climate scenarios. These findings provide valuable insights for wheat breeders and producers under future climatic conditions.

Revolutionary catalyst protection by single layer graphene capping, tremendous catalyst lifetime longevity and activity enhancement towards oxygen reduction reaction.