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This paper presents an integrated vehicle model to simulate simultaneously the driver, powertrains, chassis, body, road condition, vehicle dynamics and the Active Suspension (AS) system with/without an energy harvesting module. The developed model is used to investigate the ride comfort and influences of energy harvesting AS system on the total energy consumption of battery Electric Vehicles (EVs) relative to EVs with a passive suspension system. Preliminary simulation results show that compared to EVs with a passive suspension system, the ones with AS system improve ride comfort, up to 31% reduction of the vehicle body acceleration RMS value, with an expense of higher energy consumption. This expense can be reduced to about 2.8% when using an energy harvesting AS system. Simulation results also demonstrate that the available energy for recuperation during the AS system operation is significant in relation to the regenerative braking energy of the propulsion system, up to approx. 70% on bumpy road surfaces.

Abstract This paper provides a forecast of electricity consumption in Cyprus up to the year 2030, based on econometric analysis of energy use as a function of macroeconomic variables, prices and weather conditions. If past trends continue electricity use is expected to triple in the coming 20–25 years, with the residential and commercial sectors increasing their already high shares in total consumption. Besides this reference scenario it was attempted to assess the impact of climate change on electricity use. According to official projections, the average temperature in the Eastern Mediterranean is expected to rise by about 1 °C by the year 2030. Using our econometrically estimated model, we calculated that electricity consumption in Cyprus may be about 2.9% higher in 2030 than in the reference scenario. This might lead to a welfare loss of 15 million Euros in 2020 and 45 million Euros in 2030; for the entire period 2008–2030 the present value of costs may exceed 200 million Euros (all expressed in constant Euros of 2007). Moreover, we assessed the additional peak electricity load requirements in the future because of climate change: extra load may amount to 65–75 Megawatts (MW) in the year 2020 and 85–95 MW in 2030.

Data Availability: The data that support the findings of this study are available from the corresponding author, C. Wen, upon reasonable request. ; Deep-learning-based fault diagnosis of wind turbine has played a significant role in advancing the renewable energy industry. However, the imbalanced data sampled by the supervisory control and data acquisition systems has led to low diagnosis accuracy. Additionally, deep neural networks can encounter issues like gradient vanishing and insufficient feature learning during backpropagation when the model is too deep. This article introduces a novel approach that is based on dynamic weight loss functions to modulate unbalanced data and improve diagnostic accuracy by focusing on misclassification of a small sample number. The proposed approach employs a 1D-CNN model and an ensemble-learning-based convolution neural network (EL-CNN) to enhance diversity of models and complementarity of feature learning. The EL-CNN model addresses the problem of local features being overlooked and provides more accurate results. The effectiveness of this proposed approach is well demonstrated through experimental cases on real wind turbine pitch system fault data. Two different networks using three different loss functions and three state-of-the-art fault diagnosis models are tested, demonstrating the EL-CNN model’s superiority. ; This work was supported in part by the European Union’s Horizon 2020 Research and Innovation Programme under Grant 820776 (INTEGRADDE), the Engineering and Physical Sciences Research Council (EPSRC) of the UK, the Royal Society of the UK, the Alexander von Humboldt Foundation of Germany, the BRIEF Award of Brunel University London, the National Natural Science Foundation of China under Grant 61973209, the Natural Science Foundation of Shanghai of China under Grant 20ZR1421200, and the Capacity Building Project of Shanghai Local Colleges and Universities of China under Grant 22010501100.

Technical and economic developments in battery and fast-charging technologies could soon make fuel cell electric vehicles, which run on hydrogen, superfluous in road transport

Optical system design has a significant impact on solar power plant efficiency. It can be advantageous to be able to very precisely adapt mirror shapes in order to improve energy yield. In this article it is investigated whether it is feasible to use non-uniform rational Beziers splines (NURBS) to describe mirrors. Algorithms and equations to evaluate optical performance by ray tracing are lined out. A parameterization scheme is given that reduces the degrees of freedom to a level suitable for automatic processing. To prove feasibility, a secondary reflector based on a NURBS surface and a compound parabolic concentrator (CPC) are designed for a specific test application and compared to each other. It is found that the suggested design method is feasible on contemporary personal computers and that the NURBS based surface performs well compared to the CPC.

AbstractDespite the rapid increase in the performance of perovskite solar cells (PSC), they still suffer from low lab‐to‐lab or people‐to‐people reproducibility. Aiming for a universal condition to high‐performance devices, we investigated the morphology evolution of a composite perovskite by tuning annealing temperature and precursor concentration of the perovskite film. Here, we introduce thermal annealing as a powerful tool to generate a well‐controlled excess of PbI2 in the perovskite formulation and show that this benefits the photovoltaic performance. We demonstrated the correlation between the film microstructure and electronic property and device performance. An optimized average grain size/thickness aspect ratio of the perovskite crystallite is identified, which brings about a highly reproducible power conversion efficiency (PCE) of 19.5 %, with a certified value of 19.08 %. Negligible hysteresis and outstanding morphology stability are observed with these devices. These findings lay the foundation for further boosting the PCE of PSC and can be very instructive for fabrication of high‐quality perovskite films for a variety of applications, such as light‐emitting diodes, field‐effect transistors, and photodetectors.

Gasification is considered to be a promising way to use biomass with high efficiency in combined heatand power production, for the production of second generation biofuels and in the chemical industry.Especially allothermal fluidized bed steam gasification produces a medium calorific, nitrogen free gassuitable for a variety of downstream processes. In general the raw product gas has to be cleaned fromcondensable hydrocarbons (tar) and conditioned (e.g. adjustment of the H2/CO-ratio) before downstreamuse. The operating conditions of the gasification reactor have a large impact on the quality of the productgas. Hence first steps to a product gas low in tar content can be undertaken directly in the reactor. In thisstudy the capability of influencing the tar content and gas composition by changing temperature (750?840 C), steam to biomass (S/B) ratio (0.8?1.2) and pressure (0.1?0.25 MPa) in an allothermal bubblingfluidized bed steam gasifier is investigated. It is found that rising temperature reduces the total tar contentand affects especially heterocyclic and light aromatic compounds. At atmospheric pressure the naphthalenecontent increases slightly with increasing temperature in contrary to pressurized gasificationwhere naphthalene decreases significantly with increasing temperature. An increase in the S/B ratio leadsto a decreasing total tar content, this tar reduction according to a higher steam content is higher at highertemperatures. Increasing pressure leads to increasing total tar content mainly due to naphthalene, theeffect is most distinct for low S/B ratios.

Since 2015, the intended climate actions of the Paris Agreement signatories have been reported as nationally determined contributions (NDC). These climate actions are fully aligned with the 13th Sustainable Development Goal (SDG) which calls for urgent action to combat climate change. The same, however, cannot be said for their relation to the other 16 SDGs of the 2030 Agenda for Sustainable Development, since climate action can either enhance or compromise the prospects for SDG implementation. In light of this challenge, this paper proposes a simple method for quantifying the synergies and trade-offs between national climate actions and the SDGs. The method, referred to as Q-SCAN, makes use of a seven-step scale and the SDG Climate Action Nexus tool. The effectiveness of the method has been demonstrated on a case study of North Macedonia, a non-Annex I, Western Balkan country with a coal-intensive energy system. Based on the experience in the preparation of the country’s enhanced NDC, the paper elaborates how the method can be used to contribute to the alignment of the national climate actions with the SDGs and how it can be used to improve stakeholder engagement.

Intermediate band materials incorporate a collection of energy levels with special optoelectronic properties within the semiconductor bandgap. This feature broadens the energy range of the solar spectrum useful for photovoltaic conversion and has the potential for enabling both high-current and high-voltage photovoltaic cells. Here we present our preliminary results on a novel intermediate band solar cell based on creating an intermediate band through the incorporation of a large concentration of Ti atoms in a GaAs crystal. The characterization of the material verifies a high concentration of incorporated Ti and the absence of structural defects. The cells show below-bandgap photon absorption with a likely contribution from As antisites and Ga vacancies. The initially degraded open-circuit voltage of the cells exhibits a high voltage recovery from 0.1 V (at room temperature and one-sun irradiance conditions) to 1.4 V (at low temperature and concentrated light).