Many technologies for cutting the magnetic laminations, from which electric motors cores are built, change material properties, among which are magnetizability and iron loss, thus affecting the motor parameters such as motor efficiency. This problem is particularly important for low-power motors, in which the dimensions of the magnetic circuit elements are relatively small. The correct estimation of the motor efficiency is important as early as at its design stage. This is possible when the correct material characteristics are used. This knowledge and analytical model enabling fast estimation of material properties (depending on the actual size) are necessary for engineers, who design electrical motors by analyzing many solution variants in a short time. The author proposes an analytical model of changing material properties, implemented in SPICE software. Its effectiveness was compared with measurement results while being a competitive solution in relation to other analytical models.... [more]

This paper discusses the impact of COVID-19’s vulnerability context on Malawi’s Energy Sector and outlines mechanisms for enhancing Malawi’s energy-sector resilience based on experiences from a range of stakeholders. The investigation was conducted online by inviting purposively selected stakeholders to create presentations responding to thematic questions. The final sample had 19 stakeholders with representation from policy-makers, regulatory bodies, national grid supply players, off-grid players, development agencies, bankers, professional bodies, civil society, and women’s rights bodies. The presentations from the stakeholders highlighted how COVID-19 affects the operation costs of energy systems and implementation of energy systems projects in areas that require stimulus packages to contain energy system delivery costs and prevent disruption of essential services amid the COVID-19 pandemic. These services include stakeholder responses to COVID-19 in the energy sector, the role of d... [more]

As the technology is emerging, the process industries are actively migrating to Industry 4.0 to optimize energy, production, profit, and the quality of products. It should be noted that real-time process monitoring is the area where most of the energies are being placed for the sake of optimization and safety. Big data and knowledge-based platforms are receiving much attention to provide a comprehensive decision support system. In this study, the Advanced Advisory system for Anomalies (AAA) is developed to predict and detect the abnormal operation in fired heaters for real-time process safety and optimization in a petrochemical plant. This system predicts and raises an alarm for future problems and detects and diagnoses abnormal conditions using root cause analysis (RCA), using the combination of FMEA (failure mode and effects analysis) and FTA (fault tree analysis) techniques. The developed AAA system has been integrated with databases in a petrochemical plant, and the results have be... [more]

As part of the recent electrification of the transportation industry, internal combustion engines are being coupled with or replaced by electric motors. This movement towards an electrified drivetrain poses new noise, vibration, and harshness (NVH) challenges related to electric motors. In this paper, the acoustic signature of an electric motor was analyzed to obtain a better understanding of the sound generated by these motors. This work provides an insight into an acoustic measurement technique that can be used to identify certain frequency bands that significantly contribute to the perceived sound. In the first part, the structural response of the motor was correlated with its acoustic spectra. Furthermore, data from acoustic and structural measurements were used to analyze the order content of the signal and identify critical contributors to the overall perceived sound. The differences between data captured by microphones in different positions around the motor helped to localize c... [more]

Biodiesel has attracted considerable interest as an alternative biofuel due to its many advantages over conventional petroleum diesel such as inherent lubricity, low toxicity, renewable raw materials, biodegradability, superior flash point, and low carbon footprint. However, high production costs, poor low temperature operability, variability of fuel quality from different feedstocks, and low storage stability negatively impact more widespread adoption. In order to reduce production costs, inexpensive inedible oilseed alternatives are needed for biodiesel production. This study utilized inedible tamarind (Tamarind indica) seed oil as an alternative biodiesel feedstock, which contained linoleic (31.8%), oleic (17.1%), and lauric (12.0%) acids as the primary fatty acids. A simple and cost-effective high vacuum fractional distillation (HVFD) methodology was used to separate the oil into three fractions (F1, F2, and F3). Subsequent transesterification utilizing basic, acidic, and enzymatic... [more]

This work evaluates the influence of combining twisted fins in a triple-tube heat exchanger utilised for latent heat thermal energy storage (LHTES) in three-dimensional numerical simulation and comparing the outcome with the cases of the straight fins and no fins. The phase change material (PCM) is in the annulus between the inner and the outer tube, these tubes include a cold fluid that flows in the counter current path, to solidify the PCM and release the heat storage energy. The performance of the unit was assessed based on the liquid fraction and temperature profiles as well as solidification and the energy storage rate. This study aims to find suitable and efficient fins number and the optimum values of the Re and the inlet temperature of the heat transfer fluid. The outcomes stated the benefits of using twisted fins related to those cases of straight fins and the no-fins. The impact of multi-twisted fins was also considered to detect their influences on the solidification process... [more]

Sensorless algorithms for Permanent Magnet Synchronous Motors (PMSM) have achieved increasing interest in the technical literature over the last few years. They can be divided into active methods and passive methods: the first inject high-frequency signals exploiting rotor anisotropy, whereas the second are based on observers. Recently, a sensorless control based on a rotor flux observer has been presented in the technical literature, which gives very accurate results in terms of rotor position estimation and robustness. In this paper, the aforementioned observer is considered and a procedure for choosing stabilizing gains of the observer is proposed. The contribution of the paper is three-fold: the mathematical modelling of the rotor flux observer, the methodology for the definition of the observer gains, and the presentation of the experimental results.

This paper aims to evaluate the life cycle greenhouse gas (GHG) emissions of importing electrical power into Singapore, generated from a large-scale solar photovoltaic (PV) power plant in Australia, through a long-distance subsea high-voltage direct current (HVDC) cable. A cost optimization model was developed to estimate the capacities of the system components. A comprehensive life cycle assessment model was built to estimate emissions of manufacturing and use of these components. Our evaluation shows that, for covering one fifth of Singapore’s electrical energy needs, a system with an installed capacity of 13GWPV, 17 GWh battery storage and 3.2GW subsea cable is required. The life cycle GHG emissions of such a system are estimated to be 110gCO2eq/kWh, with the majority coming from the manufacturing of solar PV panels. Cable manufacturing does not contribute largely toward GHG emissions. By varying full-load hours and cable lengths, it was assessed that sites closer to Singapore might... [more]

Vehicle-to-grid services make use of the aggregated capacity available from a fleet of vehicles to participate in energy markets, help integrate renewable energy in the grid and balance energy use. In this paper, the critical components of such a service are described in the context of a commercial service that is currently under development. Key among these components is the prediction of available capacity at a future time. In this paper, we extend a previous work that used a deep learning recurrent neural network for this task to include online machine learning, which enables the network to continually refine its predictions based on observed behaviour. The coronavirus pandemic that was declared in 2020 resulted in closures of the university and substantial changes to the behaviour of the university fleet. In this work, the impact of this change in vehicles usage was used to test the predictions of a network initially trained using vehicle trip data from 2019 with and without online... [more]

Effective solutions are needed to decrease the greenhouse gases emissions of the transport sector, not only in terms of supply-side measures, but also including demand-side solutions. This paper focuses on the passenger demand related to daily commuting, either for work or study purposes. A bottom-up analysis is presented, which draws from detailed data for Lombardy, the most populous region in Northern Italy, to build an estimate of the annual energy consumption and emissions related to commuting. The potential of different measures to decrease emissions is evaluated, including the renovation of the vehicle stock, higher levels of remote working, and the deployment of carpooling schemes. The results show that the largest part of the current emissions from commuting is caused by car use, both due to its higher modal share and to the higher specific emissions, which are in turn also contributed by the low occupancy rates. The renewal of the current vehicle stock can lead to significant... [more]

Hydrogen production from water splitting remains difficult due to the low equilibrium constant (e.g., Kp ≈ 2 × 10−8 at 900 °C). The coupling of methane combustion with water splitting in an oxygen transport membrane reactor can shift the water splitting equilibrium toward dissociation by instantaneously removing O2 from the product, enabling the continuous process of water splitting and continuous generation of hydrogen, and the heat required for water splitting can be largely compensated for by methane combustion. In this work, a CFD simulation model for the coupled membrane reactor was developed and validated. The effects of the sweep gas flow rate, methane content and inlet temperature on the reactor performance were investigated. It was found that coupling of methane combustion with water splitting could significantly improve the hydrogen generation capacity of the membrane reactor. Under certain conditions, the average hydrogen yield with methane combustion could increase threefol... [more]

Self-driving cars, i.e., fully automated cars, will spread in the upcoming two decades, according to the representatives of automotive industries; owing to technological breakthroughs in the fourth industrial revolution, as the introduction of deep learning has completely changed the concept of automation. There is considerable research being conducted regarding object detection systems, for instance, lane, pedestrian, or signal detection. This paper specifically focuses on pedestrian detection while the car is moving on the road, where speed and environmental conditions affect visibility. To explore the environmental conditions, a pedestrian custom dataset based on Common Object in Context (COCO) is used. The images are manipulated with the inverse gamma correction method, in which pixel values are changed to make a sequence of bright and dark images. The gamma correction method is directly related to luminance intensity. This paper presents a flexible, simple detection system called... [more]

The transport of CO2, as a part of the carbon capture and storage chain, has received increased attention in the last decade. This paper aims to evaluate the most promising CO2 liquefaction processes that can be used for port-to-port and port−offshore CO2 ship transportation. The energetic, exergetic, and economic analyses are applied. The liquefaction pressure has been set to 15 bar (liquefaction temperature −30 °C), which corresponds to the design of the existing CO2 carriers. The three-stage vapor-compression process has been selected among closed systems (with propane-R290, ammonia-R717, and R134a as the working fluid) and the precooled Linde−Hampson process—as the open system (with R717). The three-stage vapor-compression process R290 shows the lowest energy consumption, and the CO2 liquefaction cost 21.3 USD/tCO2. Although the power consumption of precooled Linde−Hampson process is 3.1% higher than the vapor-compression process with R209, the lowest total capital expenditures are... [more]

High torque and power density are unique merits of transverse flux machines (TFMs). TFMs are particularly suitable for use in direct-drive systems, that is, those power systems with no gearbox between the electric machine and the prime mover or load. Variable speed wind turbines and in-wheel traction seem to be great-potential applications for TFMs. Nevertheless, the cogging torque, efficiency, power factor and manufacturing of TFMs should still be improved. In this paper, a comprehensive review of TFMs topologies and design is made, dealing with TFM applications, topologies, operation, design and modeling.

It is well known that over the last 60 years the trend of long-lived greenhouse gas emissions have shown a strong acceleration. There is an increasing concern and a mounting opposition by public opinion to continue with the use of fossil energy. Western countries are presently involved in a so-called energy transition with the objective of abandoning fossil energy for renewable sources. In this connection, hydrogen can play a central role. One of the sustainable ways to produce hydrogen is the use of microalgae which possess two important natural catalysts: photosystem II and hydrogenase, used to split water and to combine protons and electrons to generate gaseous hydrogen, respectively. For about 20 years of study on photobiological hydrogen production, our scientific hopes were based on the application of the sulfur protocol, which indisputably represented a very important advancement in the field of hydrogen production biotechnology. However, as reported in this review, there is inc... [more]

Modern computing resources, including machine learning-based techniques, are used to maintain stability between the demand and supply of electricity. Machine learning is widely used for the prediction of energy consumption. The researchers present several artificial intelligence and machine learning-based methods to improve the prediction accuracy of energy consumption. However, the discrepancy between actual energy consumption and predicted energy consumption is still challenging. Various factors, including changes in weather, holidays, and weekends, affect prediction accuracy. This article analyses the overall prediction using error curve learning and a hybrid model. Actual energy consumption data of Jeju island, South Korea, has been used for experimental purposes. We have used a hybrid ML model consisting of Catboost, Xgboost, and Multi-layer perceptron for the prediction. Then we analyze the factors that affect the week-ahead (WA) and 48 h prediction results. Mean error on weekday... [more]

Nowadays, environmental and energy issues attract a lot of attention in the civil buildings sector, leading to the emergence of new technologies and new targets, which include Net Zero Energy Buildings (NZEBs). However, despite the great response in scientific research, the spread of NZEBs in Europe is quite limited. This is due not only to the lack of transposition of the related European Directives into the various national legislations, but also to the high initial cost of such high-performance buildings. The aim of this paper is to demonstrate how different energy retrofit strategies on existing buildings can lead to the achievement of the NZEB target if encouraged by tax incentives, at zero or almost zero cost. The introduction of tax incentives by individual EU member states would allow the spread of NZEBs that are still underdeveloped, especially in highly urbanized contexts. A suitable building energy dynamic simulation software has been used. The case study refers to a villa l... [more]

The presented review gives reliable information about the currently used measurement instrumentation in parabolic trough fields and recent monitoring approaches. The usually built-in measurement equipment in the solar field, clamp-on systems for flexible measurements of temperature and flow, solar irradiance measurements, standard meteorological equipment, laboratory devices for heat transfer fluid analyses and instruments related to the tracking of solar collector assemblies are presented in detail. The measurement systems are reported with their measurement uncertainty, approximate costs and usual installation location for the built-in instrumentation. Specific findings related to the installation and operation of the measurement devices are presented. The usually installed instrumentation delivers a lot of measurements all over the field at the expense of measurement accuracy, compared to special test facility equipment. Recently introduced measurement approaches can improve the sta... [more]

A cantilever beam, manufactured from a steel-carrying substrate and two patches of Macro Fiber Composite of P2 type, was a subject of laboratory research. MFC patches were glued on both sides of the carrying substrate and were parallelly connected. An experimental determination of an optimal resistance for both energy harvesting and vibration passive damping of the cantilever beam was the purpose of the conducted laboratory research. The research contained 10 experiments in which courses of the energy-harvesting process and resistive passive damping of vibration were estimated. Energy harvesting was estimated by measurements of the generated current for the given load-resistance values. Resistive passive damping of vibration was assessed by using a vision method that enabled the displacements’ measurements of 10 selected points in the beam structure for the given shunt-resistance values. Values of both load resistance and shunt resistance were chosen on the basis of analytically calcul... [more]

This paper applies a voltage instability monitoring method based on voltage and current measurements from a transmission bus PMU on the Hellenic Interconnected System using both unstable and marginally stable scenarios, derived from the historical 12 July 2004 blackout of the Athens area. The effectiveness, selectivity and reliability of the proposed monitoring method is clearly demonstrated, allowing its integration into a System Protection Scheme with direct load shedding. It is shown that the proposed instability detection and control scheme could have prevented the voltage collapse if applied at the time of the event.

We aim to contribute to in-depth comprehension of the factors and preferences behind the reuses of large-scale underused or abandoned former collective farms from the 1950s−1980s for biogas plants and solar photovoltaic power plants. As a case study, three regions in the southern part of the Czech Republic have been selected. Our findings signal that the residents’ attitudes towards the mentioned energy sources are rather negative. Similarly, farmers’ interest in photovoltaic power plants is low. More interest has been detected in the case of biogas production; this is especially true for large agricultural companies and farmers, who own underused or abandoned premises. Biogas plants are frequently located in agricultural areas with warmer or just slightly colder climates as a consequence of the potential to process locally grown maize. On the other hand, photovoltaic power plants are found on more fertile plains with high levels of insolation, but, surprisingly, also in mountain regio... [more]

Fuel cell electric vehicles (FCEV) are emerging as one of the prominent zero emission vehicle technologies. This study follows a deterministic modeling approach to project two scenarios of FCEV adoption and the resulting hydrogen demand (low and high) up to 2050 in California, using a transportation transition model. The study then estimates the number of hydrogen production and refueling facilities required to meet demand. The impact of system scale-up and learning rates on hydrogen price is evaluated using standalone supply chain models: H2A, HDSAM, HRSAM and HDRSAM. A sensitivity analysis explores key factors that affect hydrogen prices. In the high scenario, light and heavy-duty fuel cell vehicle stocks reach 12.5 million and 1 million by 2050, respectively. The resulting annual hydrogen demand is 3.9 billion kg, making hydrogen the dominant transportation fuel. Satisfying such high future demands will require rapid increases in infrastructure investments starting now, but especial... [more]

Different operations make the borehole temperature change and cause periodic stresses, which often cause variations in the stress state of the sheath or damage. In this paper, the effect of temperature on sheath integrity is investigated. First, the mechanical model of sheath is established and analyzed by shakedown theory. Then, compression experiments of well cement at different temperatures are carried out, and the law of mechanical properties with temperature is obtained. Finally, combining the theoretical analysis and mechanical experiments, the results show that (1) when only the temperature inside the sheath cyclically varies, the negative influence of temperature caused by the practical operations can be negligible. (2) When the internal pressure and temperature act together, the effect of temperature on the sheath is reflected in temperature stress and the change of the cement properties. (3) With the increase of temperature difference (∆T), the cohesion of cement decreases wh... [more]

The CSEM method, which is frequently used as a risk-reduction tool in hydrocarbon exploration, is finally moving to a new frontier: reservoir monitoring and surveillance. In the present work, we present a CSEM time-lapse interpretation workflow. One essential aspect of our workflow is the demonstration of the linear relationship between the anomalous transverse resistance, an attribute extracted from CSEM data inversion, and the SoPhiH attribute, which is estimated from fluid-flow simulators. Consequently, it is possible to reliably estimate SoPhiH maps from CSEM time-lapse surveys using such a relationship. We demonstrate our workflow’s effectiveness in the mature Marlim oilfield by simulating the CSEM time-lapse response after 30 and 40 years of seawater injection and detecting the remaining sweet spots in the reservoir. The Marlim reservoirs are analogous to several turbidite reservoirs worldwide, which can also be appraised with the proposed workflow. The prediction of SoPhiH maps... [more]

Nowadays, fuel cells are becoming a real alternative to power several applications, from portable electronic devices to cars, buses, or stationary facilities. Usually, a basic analysis of a fuel cell includes polarization curve test, as this method is excellent to characterize the behavior of a fuel cell as a whole, because it integrates all the different physical process that happens inside in current and voltage signals. On the other hand, it does not provide accurate information of these physical processes as individual. In this research, we relate the results of polarization curve test and EIS (Electrochemical Impedance Spectroscopy) test through two mathematical expressions. Then, using equivalent electrical circuit elements to model EIS curves, and applying the developed expressions, we correlate the EIS and polarization curve results, allowing us to interpret the physical meaning of these circuit elements and obtain a deeper vision of the internal processes that happen.