In recent years, perovskite solar cells (PSCs), often referred to as the third generation, have rapidly proliferated. Their most prominent deficiencies are their low efficiency and poor stability. To enhance their productivity, a combination of silicon and perovskite is employed. Here, we present a 3D simulation analysis of various electrical and optical properties of PSCs using the SILVACO simulation software. Using the inverted planar method with inorganic transport materials and the proper selection of anti-reflective coatings with a back contact layer increases the efficiency of PSCs to 28.064%, and enhances their stability without using silicone composites. Several materials, including CaF₂, SiO₂, and Al₂O₃, with various thicknesses have been employed to investigate the effect of anti-reflective coatings, and to improve the efficiency of the simulated PSC. The best thickness of the absorbent layer is 500 nm, using a CaF₂ anti-reflective coating with an optimal thickness of 110 nm. A polymer composition of Spiro-OMeTAD and inorganic materials Cu₂O and NiOx was used as the hole transport material (HTM) and inorganic ZnO was employed as the electron transport material (ETM) to optimize the solar cell efficiency, and an optimized thickness was considered for these materials. Yields of 29.261, 28.064 and 27.325% were obtained for Spiro-OMeTAD/ZnO, Cu₂O/ZnO and NiOx/ZnO, respectively. Thus, Spiro-OMeTAD yields the highest efficiency. This material is highly expensive with a complex synthesis and high degradability. We proposed to employ Cu₂O to alleviate these problems; however, this reduces the efficiency by 1.197%. As a graphene connector has high flexibility, reduces cell weight, and is cheaper and more accessible compared to other metals, it was regarded as an optimal alternative. The simulation results indicate that using the inverted planar method with inorganic transport materials for graphene-based PSCs is highly promising. Full article

So far, airport security screening has only been analysed in terms of efficiency, level of service, and protection against any acts of unlawful interference. Screening procedures have not yet addressed the need to limit operator-to-passenger contact. However, the pandemic situation (COVID-19) has shown that it is a factor that can be a key protection for the health of passengers and operators. The purpose of this paper was to analyse the feasibility of reducing contact between operators and passengers in the airport security screening system by process management with respect to the power consumption of the system. Experimental research was conducted on a real system. A computer simulation was applied to estimate system performance and power consumption. The paper identifies the important findings that expand upon previous knowledge. The results showed that there are two key factors: the experience of operators and proper system structure. These factors can significantly reduce the number of operator-to-passenger contacts and, in parallel, provide lower energy consumption of the system. The results obtained in this article showed that proper management improves the process by up to 37%. This approach expands the World Health Organization’s policy of prevention against COVID-19 and helps to ensure sustainable process management. Full article

Deterministic forecasting models have been used through the years to provide accurate predictive outputs in order to efficiently integrate wind power into power systems. However, such models do not provide information on the uncertainty of the prediction. Probabilistic models have been developed in order to present a wider image of a predictive outcome. This paper proposes the lower upper bound estimation (LUBE) method to directly construct the lower and upper bound of prediction intervals (PIs) via training an artificial neural network (ANN) with two outputs. To evaluate the PIs, the minimization of a coverage width criterion (CWC) cost function is proposed. A particle swarm optimization (PSO) algorithm along with a mutation operator is further implemented, in order to optimize the weights and biases of the neurons of the ANN. Furthermore, wavelet transform (WT) is adopted to decompose the input wind power data, in order to simplify the pre-processing of the data and improve the accuracy of the predictive results. The accuracy of the proposed model is researched from a seasonal perspective of the data. The application of the model on the publicly available data of the 2014 Global Energy Forecasting Competition shows that the proposed WT-LUBE-PSO-CWC forecasting technique outperforms the state-of-the-art methodology in important evaluation metrics. Full article

Multidimensional crisis phenomena (financial–economic, environmental and social), plaguing the international community, especially in the last 30 years, have intensified resentment towards traditional models of growth and socio-economic development. The European Commission has placed the idea of a green economy (GE) at the heart of the Europe 2020 strategy. This paper presents an assessment of the implementation of the green economy assumptions in EU countries in 2018, taking 2010 as the base year. Using taxonomic methods, a synthetic evaluation index (GEI—Green Economy Index) was constructed based on a multi-criterion set of 27 indicators. This paper attempts to answer the following questions: How green are the European economies? What are the main challenges in this context? The average value of the index for the EU countries decreased in the studied years from 0.3423 to 0.3294, which can be interpreted as a slowdown in the greening processes. The key recommendations for the upcoming years include the improvement of energy efficiency indicators, the further increase in the share of renewable energy sources in the energy balance. Moreover, a significant problem continues to be the high percentage of the population at risk of poverty or social exclusion, as well as low CO₂ and resource productivity rates. Full article

Large amounts of lignin residue is expected in the future when biorefineries for producing biofuels and bio-products will increase in numbers. It is, therefore, valuable to find solutions for using this resource for the sustained production of useful bioenergy or bio-products. Anaerobic digestion could potentially be an option for converting the biorefinery lignin into a valuable energy product. However, lignin is recalcitrant to biodegradation under anaerobic conditions unless the structure is modified. Wet oxidation followed by steam explosion (wet explosion) was previously found to make significant changes to the lignin structure allowing for biodegradation under anaerobic conditions. In this study, we examine the effect of wet explosion pretreatment for anaerobic digestion of wheat straw lignin under mesophilic (37 °C) conditions. Besides the biorefinery lignin produced from wheat straw, untreated lignin was further tested as feed material for anaerobic digestion. Our results showed that wet exploded lignin pretreated with 2% NaOH showed the highest lignin degradation (41.8%) as well as the highest methane potential of 157.3 ± 9.9 mL/g VS. The untreated lignin with no pretreatment showed the lowest methane yield of 65.8 ± 4.8 and only 3.5% of the lignin was degraded. Overall, increased severity of the pretreatment was found to enhance anaerobic degradation of lignin. Full article

Hybrid electric aero-propulsion requires high power-density electric motors. The use of a constrained optimization method with the finite element analysis (FEA) is the best way to design these motors and to find the best solutions which maximize the power density. This makes it possible to take into account all the details of the geometry as well as the non-linear characteristics of magnetic materials, the conductive material and the current control strategy. Simulations were performed with a time stepping magnetodynamic solver while taking account the rotor movement and the stator winding was connected by an external electrical circuit. This study describes the magnetic FEA direct optimization approach for the design of Halbach array permanent magnet synchronous motors (PMSMs) and its advantages. An acceptable compromise between precision and computation time to estimate the electromagnetic torque, iron losses and eddy current losses was found. The finite element simulation was paired with analytical models to compute stress on the retaining sleeve, aerodynamic losses, and copper losses. This type of design procedure can be used to find the best machine configurations and establish design rules based on the specifications and materials selected. As an example, optimization results of PM motors minimizing total losses for a 150-kW application are presented for given speeds in the 2000 rpm to 50,000 rpm range. We compare different numbers of poles and power density between 5 kW/kg and 30 kW/kg. The choice of the number of poles is discussed in the function of the motor nominal speed and targeted power density as well as the compromise between iron losses and copper losses. In addition, the interest of having the current-control strategy as an optimization variable to generate a small amount of flux weakening is clearly shown. Full article

The drivers underpinning the emergence of SARS-CoV-2 and climate change attest to the fact that we are now living in the Anthropocene Epoch, with human activities significantly impacting and altering the global ecosystem. Here, we explore the historical context of zoonoses, the effect of anthropogenic climate change and interrelated drivers on the emergence of, and response to emerging infectious diseases. We call attention to an urgent need for inculcating a One Health research agenda that acknowledges the primary interconnection between animals, humans, pathogens, and their collective milieus to foster long term resilience across all systems within our shared planetary environment. Full article

This paper describes the development and validation of an innovative protection system based on medium-voltage fuses for a high-power switching conversion system. This special conversion system, rated to deliver about 56 MW to the load, is based on neutral-point clamped IGCT inverters, connected to the same dc link through a set of distributed busbars, with a dc-link voltage of 6.5 kV and a capacitive stored energy up to 837 kJ. The sudden release of this energy in case of a switch failure in one inverter and the subsequent short circuit of one leg can lead to destructive consequences. From the analysis of different protection strategies, performed by numerical simulations of the fault evolutions, the developed solution based on medium-voltage fuses was found the only provision able to cope with such high stored energy and uncommon circuit topology. Custom fuses were developed for this application, and a specially tailored test was designed for validating the fuse selection. The paper, after summarizing the work carried out to simulate the fault evolution and select the protection, presents the analyses carried out to set up the validation test, and describes and discusses the results of the test and the complementing numerical simulations, which demonstrated the effectiveness of the protection system. Full article

The current paper presents the development and characterization of polyvinylidene fluoride (PVDF)-Zn₂GeO₄ (ZGO) fine fiber mats. ZGO nanorods (NRs) were synthesized using a hydrothermal method and incorporated in a PVDF solution to produce fine fiber mats. The fiber mats were prepared by varying the concentration of ZGO NRs (1.25–10 wt %) using the Forcespinning^® method. The developed mats showed long, continuous, and homogeneous fibers, with average fiber diameters varying from 0.7 to 1 µm, depending on the ZGO concentration. X-ray diffraction spectra depicted a positive correlation among concentration of ZGO NRs and strengthening of the beta phase within the PVDF fibers. The composite system containing 1.25 wt % of ZGO displayed the highest piezoelectric response of 172 V. This fine fiber composite system has promising potential applications for energy harvesting and the powering of wearable and portable electronics. Full article

Hydropower plants affect the distribution and composition of sediments. The main aim of this study was to analyze the spatial distribution of sediment pollution in the vicinity of a small hydropower plant. The grain composition of the sediments, the content of heavy metals (Cu, Ni, Cr, Zn, Pb, and Cd) and select physicochemical properties (pH, electrolytic conductivity) were tested at 14 points upstream and downstream of the hydropower plant on the Ślęza River in Poland, as well as at reference point. The interactions between the tested parameters were also verified. The results of the conducted analysis show that hydropower plants significantly affect the composition and properties of sediments. Large amounts of sediment are deposited on damming weirs, accumulating heavy metals and other substances. The differences in the concentrations of elements were significant, and Cu, Ni, Cr, Zn and Pb were 8.74, 9.53, 3.63, 8.26 and 6.33 times higher, respectively, than the median value at points upstream of the hydropower plant than downstream. It was shown that the tested parameters of the sediments interact with each other and are correlated; heavy metals showed a synergistic effect, while other parameters configurations showed an antagonistic effect. The higher content of heavy metals upstream of the hydropower plant resulted from the presence of finer sediment—classified as silt—in this section. Downstream of the hydropower plant, there were mainly sands, which showed a lower ability to absorb substances. This work contributes to improving the rational management of the worldwide issue of sediments within dams located in river valleys. Moreover, it is in line with the 2030 Sustainable Development Goals adopted by the United Nations, particularly in the fields of clean water and sanitation, clean and available energy, and responsible consumption and production. Full article

Energy security is of key importance for states and international organizations. An important issue in energy security is the assessment of current and future energy security methods. While the assessment of the current methods is relatively easy, since it is based on recent information, the assessment of the future methods is burdened with uncertainty and is therefore much more difficult. Therefore, the aim of the article is to develop a new approach for assessing current and future energy security issues based on a complex security index, supported by the computationally transparent fuzzy multi-criteria decision analysis (MCDA) method. The use of the fuzzy MCDA methods allows one to capture the uncertainty of assessments and forecasts, and the forecasts themselves were based on the Holt’s method; the international energy security risk index (IESRI) was used as the source of the data to generate the forecasts. The research compared two data sources for forecasts (IESRI categories and metrics) and two methods of forecast fuzzification. As a result, the forecasted assessments and rankings of energy security for the 2020–2030 period were obtained. On the basis of these forecasts, general trends shaping energy security were also indicated. Full article

State-of-the-art Predictive Maintenance (PM) of Electrical Machines (EMs) focuses on employing Artificial Intelligence (AI) methods with well-established measurement and processing techniques while exploring new combinations, to further establish itself a profitable venture in industry. The latest trend in industrial manufacturing and monitoring is the Digital Twin (DT) which is just now being defined and explored, showing promising results in facilitating the realization of the Industry 4.0 concept. While PM efforts closely resemble suggested DT methodologies and would greatly benefit from improved data handling and availability, a lack of combination regarding the two concepts is detected in literature. In addition, the next-generation-Digital-Twin (nexDT) definition is yet ambiguous. Existing DT reviews discuss broader definitions and include citations often irrelevant to PM. This work aims to redefine the nexDT concept by reviewing latest descriptions in broader literature while establishing a specialized denotation for EM manufacturing, PM, and control, encapsulating most of the relevant work in the process, and providing a new definition specifically catered to PM, serving as a foundation for future endeavors. A brief review of both DT research and PM state-of-the-art spanning the last five years is presented, followed by the conjunction of core concepts into a definitive description. Finally, surmised benefits and future work prospects are reported, especially focused on enabling PM state-of-the-art in AI techniques. Full article

Territorial energetic and environmental planning provides operational solidity to the concept of sustainable development, in particular in energy-related issues, where recent attention to and social awareness of climate change are driving actions and policies at local and international levels. The goals of the United Nations Agenda 2030 can be reached through the strategy of glocalization, giving more responsibility to local administrations like municipalities. In this work, a scientific methodology is developed and validated to revise Sustainable Energy Action Plans (SEAP) and the monitoring phase of municipalities. The methodology starts from measured data in the territory considered and makes use of specific statistical models in order to estimate the needed data. The methodology considers the energy consumption of the main sectors: residential, transportation, tertiary, and commercial, with a particular focus on municipal competences (public lighting, urban transport, municipal fleet, etc.). Renewable energy is also considered due to its importance in local energy production. In order to go deeper into SEAPs, in this paper, the authors describe the quantitative analysis of the Baseline Emission Inventory, the quantification of the SEAP planning actions, and the definition of the Monitoring Emission Inventory, which is the final step of the planning process. This step was done for nine municipalities of the Abruzzo region with different characteristics (size, population, climate, geographical position, economy, etc.) in order to widen the results of the analysis and test the robustness of the methodology. Indeed, it gave a quantitative dimension to the primary energy consumption and CO₂ emissions for 2018, compared with the 2005 baseline values, and the final results are related to the reduction commitments planned for 2020. All the municipalities were considered to have achieved this goal, surpassing the 20% emissions reduction. This validated methodology is also the basis for the development of the Sustainable Energy and Climate Action Plans (SECAPs), which integrate adaptation actions and mitigation ones. Full article

High-performance districts and communities offer opportunities for reducing energy use, emissions, and costs, and can be instrumental in helping cities achieve their climate goals. The design of such communities requires identification of opportunities early on and their re-evaluation throughout the planning process. There is a need for energy modeling tools that connect 3D Computer-Aided Design (CAD) platforms to simulation engines, enabling detailed energy analysis of districts within the workflows and tools used by practitioners. This paper introduces the Dragonfly and URBANopt^TM combined toolset that supports the creation of urban models from a range of geometry formats typically used by designers and planners, and provides an integrated pathway to simulate district-scale energy systems. The toolset is piloted by a global architecture and master planning firm to evaluate several key urban-scale technical questions for the design of a district in Chicago. The findings indicate that, while energy savings can be achieved through traditional architectural studies and enhancements to individual building efficiency, the modeling toolset helps identify additional savings and insights that can be achieved when considering district-scale energy systems. Finally, this study demonstrates how the Dragonfly/URBANopt toolset can integrate with master planning workflows, thereby enabling an iterative performance-based design process. Full article

We demonstrate a working functional prototype of a cooperative perception system that maintains a real-time digital twin of the traffic environment, providing a more accurate and more reliable model than any of the participant subsystems—in this case, smart vehicles and infrastructure stations—would manage individually. The importance of such technology is that it can facilitate a spectrum of new derivative services, including cloud-assisted and cloud-controlled ADAS functions, dynamic map generation with analytics for traffic control and road infrastructure monitoring, a digital framework for operating vehicle testing grounds, logistics facilities, etc. In this paper, we constrain our discussion on the viability of the core concept and implement a system that provides a single service: the live visualization of our digital twin in a 3D simulation, which instantly and reliably matches the state of the real-world environment and showcases the advantages of real-time fusion of sensory data from various traffic participants. We envision this prototype system as part of a larger network of local information processing and integration nodes, i.e., the logically centralized digital twin is maintained in a physically distributed edge cloud. Full article