Generating aerodynamic downforce for the wheels on the front axle of a car is a much more difficult task than for the rear axle. This paper, submitted to the special issue of Energies “Future of Road Vehicle Aerodynamics”, presents an unusual solution to increase the aerodynamic downforce of the front axle for cars with covered wheels, with the use of an elastic splitter. The effect of the inflatable splitter on the aerodynamic forces and moments was studied in a DrivAer passenger car and a fast sports car, Arrinera Hussarya. Providing that the ground clearance was low enough, the proposed solution was successful in increasing the front axle downforce without a significant increase in drag force. The possibility of emergency application of such a splitter in the configuration of the body rotated by up to 2 degrees with the front end raised was also analyzed. An elastic, deformed splitter remained effective for the nonzero pitch case. The results of the calculations are presented in the... [more]

Unsustainable rice straw management causes environmental impacts; hence, utilisation of rice straw for bioenergy is a promising strategy for sustainable rice straw management. Although rice straw has a high potential for bioenergy generation, the whole production cycle and application may cause environmental damage that is not fully understood. Hence, environmental performance studies are required to determine the most effective rice straw utilisation options. A comprehensive approach, such as life-cycle assessment (LCA), can give comprehensive information on the possible environmental effects of rice straw utilisation for bioenergy. Therefore, this study briefly overviews the LCA of rice straw utilisation for bioenergy production. It is found that utilisation of rice straw for bioenergy could reduce global warming potential compared to energy production from fossil fuels. However, it is suggested that other impact categories in LCA be evaluated in the bioenergy production from rice st... [more]

The scientific judgement of the structural abrupt transition characteristics of the carbon market price is an important means to comprehensively analyze its fluctuation law and effectively prevent carbon market risks. However, the existing methods for identifying structural changes of the carbon market based on carbon price data mostly regard the carbon price series as a deterministic time series and pay less attention to the uncertainty implied by the carbon price series. We propose a framework for identifying abrupt transitions in the carbon market from the perspective of a complex network by considering the influence of random factors on the carbon price series, expressing the carbon price series as a sequence of probability density functions, using the distribution of probability density to reveal the uncertainty information implied by carbon price series and constructing a recurrence network of carbon price probability density. Based on the community structure, the break index and... [more]

The identification of fault types and their locations is crucial for power system protection/operation when a fault occurs in the lines. In general, this involves a human-in-the-loop analysis to capture the transient voltage and current signals using a common format for transient data exchange for power systems (COMTRADE) file. Then, protection engineers can identify the fault types and the line locations after the incident. This paper proposes intelligent and novel methods of faulty line and location detection based on convolutional neural networks in the power system. The three-phase fault information contained in the COMTRADE file is converted to an image file and extracted adaptively by the proposed CNN, which is trained by a large number of images under various kinds of fault conditions and factors. A 500 kV power system is simulated to generate different types of electromagnetic fault transients. The test results show that the proposed CNN-based analyzer can classify the fault ty... [more]

Potential analyses identify possible locations for renewable energy installations, such as wind turbines and photovoltaic arrays. The results of previous potential studies for Germany, however, are not consistent due to different assumptions, methods, and datasets being used. For example, different land-use datasets are applied in the literature to identify suitable areas for technologies requiring open land. For the first time, commonly used datasets are compared regarding the area and position of identified features to analyze their impact on potential analyses. It is shown that the use of Corine Land Cover is not recommended as it leads to potential area overestimation in a typical wind potential analyses by a factor of 4.7 and 5.2 in comparison to Basis-DLM and Open Street Map, respectively. Furthermore, we develop scenarios for onshore wind, offshore wind, and open-field photovoltaic potential estimations based on land-eligibility analyses using the land-use datasets that were pro... [more]

The cultivation of energy crops on degraded soils contributes to reduce the risks associated with land use change, and the biomass may represent an additional revenue as a feedstock for bioenergy. Switchgrass and giant reed were tested under 300 and 600 mg Cr kg−1, 110 and 220 mg Ni kg−1, and 4 and 8 mg Cd kg−1 contaminated soils, in a two year pot experiment. Switchgrass yields (average aerial 330 g.m−2 and below ground 430 g.m−2), after the second year harvest, were not affected by Cd contamination and 110 mg Ni kg−1, but 220 mg Ni kg−1 significantly affected the yields (55−60% reduction). A total plant loss was observed in Cr-contaminated pots. Giant reed aboveground yields (control: 410 g.m−2), in the second year harvest, were significantly affected by all metals and levels of contamination (30−70% reduction), except in 110 mg Ni kg−1 pots. The belowground biomass yields (average 1600 g.m−2) were not affected by the tested metals. Contamination did not affect the high heating value... [more]

To maximize the benefits of microgrid clusters, a general model and analysis method for studying the optimized operation of AC/DC microgrid clusters using non-cooperative games is proposed. This paper first establishes the optimized objective function of an AC/DC microgrid for economic operations. Based on the supply and demand theory, the dynamic adjustment mechanism of electricity price is introduced into microgrid clusters, and a game model for the optimal operation of multiple microgrids is established. The Nash equilibrium solution of the established model is obtained by iterative search algorithm, and the convergence of the Nash equilibrium solution is also proven. Finally, the validity and economy of the proposed model are verified by the actual case.

Motor diagnostics is an important subject for consideration. Electric motors of different types are present in a multitude of object, from consumer goods through everyday use devices to specialized equipment. Diagnostic assessment of motors using acoustic signals is an interesting field, as microphones are present everywhere and are relatively easy sensors to process. In this paper, we analyze acoustic signals for the purpose of motor diagnostics using functional data analysis. We represent the spectrum (FFT) of the acoustic signals on a B-Spline basis and construct a classifier based on that representation. The results are promising, especially for binary classifiers, while multiclass (softmax regression) shows more sensitivity to dataset size. In particular, we show that while we are able to obtain almost perfect classification for binary cases, multiclass classifiers can struggle depending on the training/testing split. This is especially visible for determining the number of broken... [more]

Energy consumption in buildings is a significant cost to the building’s operation. As faults are introduced to the system, building energy consumption may increase and may cause a loss in occupant productivity due to poor thermal comfort. Research towards automated fault detection and diagnostics has accelerated in recent history. Rule-based methods have been developed for decades to great success, but recent advances in computing power have opened new doors for more complex processing techniques which could be used for more accurate results. Popular machine learning algorithms may often be applied in both unsupervised and supervised contexts, for both classification and regression outputs. Significant research has been performed in all permutations of these divisions using algorithms such as support vector machines, neural networks, Bayesian networks, and a variety of clustering techniques. An evaluation of the remaining obstacles towards widespread adoption of these algorithms, in bo... [more]

Close-distance coal seams are widely distributed in China, and the mining of overlying coal seams leads to floor damage. To grasp the properties and the fracture spans of the damaged main roof in the underlying coal seam, combining the calculation of the floor damage depth with rock damage theory and the formulas for calculating the first and periodic weighting intervals of the damaged main roof and the instability conditions of the damaged key blocks are obtained. Three interaction stability mechanics models are proposed for key blocks with different properties of the upper and lower main roof, and the instability conditions of the lower damaged key blocks are obtained when the fracture lines overlap. When combined with a specific example, the field monitoring verified the calculation results. The research results are as follows: (1) The first and periodic weighting intervals, horizontal thrust between blocks, and critical load of instability of the damaged main roof are significantly... [more]

The main objective of this paper is to design a robust multi-objective H2/H∞ delayed feedback controller for load frequency control of a multi-area interconnected power system by taking into account all theoretical and practical constraints. To achieve more precise modelling and analysis, the limitation of valve position, governor, and transmission delay are considered to guarantee of LFC system’s stability in practical applications. The nonlinear delayed system is approximated by the Takagi−Sugeno fuzzy model. Then, a parallel distributed compensation scheme is utilized for designing the control system of the overall system. The proposed multi-objective and robust H2/H∞ controller simultaneously minimizes the H2 and H∞ control performance indexes. Finally, simulation results verify the robustness and effectiveness of the proposed scheme in dealing with the impact of load disturbances, model uncertainties, transmission time delays, and nonlinearities in the model.

(1) Background: Gas hydrates are historically notable due to their prevalence and influence on operational difficulties in the oil and gas industry. Recently, new technologies involving the formation of gas hydrates to accomplish various applications have been proposed. This has created new motivation for the characterization of rheological and mechanical properties and the study of molecular phenomena in gas hydrates systems, particularly in the absence of oil and under pre-nucleation conditions. (2) Methodology: This work reviews advances in research on the promotion, inhibition, rheology, and mechanical properties of gas hydrates obtained through an integrated material synthesis-property characterization-multi-scale theoretical and computational platform at McGill University. (3) Discussion: This work highlights the findings from previous experimental work by our group and identifies some of their inherent physical limitations. The role of computational research methods in extending... [more]

To improve the predicting accuracy of wind power, this paper proposes a forecasting model of wind power based on the IPSO−LSTM model and classified fusion, which not only overcomes the shortcoming of the artificially determined parameters of LSTM, but also solves the problem that the fused accuracy may be reduced by the environment when adopting a single fusion model. Firstly, some wind speed sub-series were obtained by decomposing the original wind speed according to the wavelet packet decomposition (WPD), and the data sets formed by combining these sub-series with meteorological elements. Subsequently, the wind power components formed by wind speed decomposition are predicted through the long short-term memory neural network (LSTM), which is optimized by the improved particle swarm optimization (IPSO). Consequently, the predicting value of the final wind power was acquired by adopting the method of classified fusion to calculate the wind power components. Several case studies were ca... [more]

Rising climate change issues are prompting engineers and scientists to focus more on improving renewable energy conversion systems [...]

With the rapid development of lithium-ion battery technology, powertrain electrification has been widely applied in vehicles. However, if thermal runaway occurs in a lithium-ion battery pack, the venting gas in the cells will spread and burn rapidly, which poses a great threat to safety. In this study, a 2D CFD simulation of the combustion characteristics of cell venting gas in a lithium-ion battery pack is performed, and the possibility of detonation of the battery pack is explored. First, a numerical model for the premixed combustion of venting gas is established using a two-step combustion mechanism. The combustion characteristics are then simulated in a 2D channel for the stoichiometric combustible mixture, and the variations in the flame velocity and pressure increment in the flow channel are analyzed. Next, the effects of the initial conditions inside the battery pack, including the pressure, temperature, and excess air coefficient, on the flame propagation process and pressure v... [more]

With vehicle electrification and employment of X-by-wire technology, mechanical systems are being replaced by motor drives which improve the efficiency and performance of vehicular systems. However, motor drives have a lower power density and reliability compared to mechanical solutions. Multi-motor drives have the potential of mitigating both these drawbacks. In this paper, a state-of-the-art review of multi-motor drives and their application to vehicular systems is carried out. Firstly, the case of multi-motor systems in automotive applications is laid out by presenting the different vehicular systems comprising multiple motors. Secondly, multi-motor drive topologies with improved power density, reliability and fault tolerance capabilities are thoroughly analyzed. Finally, the topologies are assessed and compared in the context of automotive applications. The assessment verifies that multi-motor drives allow for fault tolerant and cost-effective solutions that are suitable for automo... [more]

The concept of “smart cities” plays a positive role in the overall green and sustainable development of a nation. However, it is still debated whether smart cities can restrain the carbon emission intensity at the micro-level and promote the green transformation of enterprises. To this end, based on China’s smart city policy (SCP) and regional enterprise data from 2008 to 2015, we study the impact of SCP on the carbon emission intensity of local enterprises, using the difference-in-differences method. The results show that SCP significantly reduces the carbon emission intensity of enterprises, and the estimated results remain significant after the propensity score matching. The mechanism analysis finds that digital transformation, innovation by enterprises, and urban green innovation all strengthen the impact of SCP on the carbon emission intensity of enterprises. The conclusions extend the scope of the existing research and provide suggestions for micro-enterprises to take advantage o... [more]

China faces a difficult choice of maintaining socioeconomic development and carbon emissions mitigation. Analyzing the decoupling relationship between economic development and carbon emissions and its driving factors from a regional perspective is the key for the Chinese government to achieve the 2030 emission reduction target. This study adopted the logarithmic mean Divisia index (LMDI) method and Tapio index, decomposed the driving forces of the decoupling, and measured the sector’s decoupling states from carbon emissions in Xinjiang province, China. The results found that: (1) Xinjiang’s carbon emissions increased from 93.34 Mt in 2000 to 468.12 Mt in 2017. Energy-intensive industries were the key body of carbon emissions in Xinjiang. (2) The economic activity effect played the decisive factor to carbon emissions increase, which account for 93.58%, 81.51%, and 58.62% in Xinjiang during 2000−2005, 2005−2010, and 2010−2017, respectively. The energy intensity effect proved the dominant... [more]

Bio-hydrogen from residual biomass may involve energy-intensive pre-treatments for drying and size management, as in the case of wet agro-industrial residues. This work assesses the performance of an alternative process layout for bio-hydrogen production from citrus peel gasification, with the aim of cogenerating heat and power along with hydrogen, using minimal external energy sources. The process consists of an air-steam fluidized bed reactor, a hydrogen separation unit, a hydrogen compression unit, and a combined heat and power unit fed by the off-gas of the separation unit. Process simulations were carried out to perform sensitivity analyses to understand the variation in bio-hydrogen production’s thermodynamic and environmental performance when the steam to biomass ratios (S/B) vary from 0 to 1.25 at 850 °C. In addition, energy and exergy efficiencies and the integrated renewability (IR) of bio-hydrogen production are evaluated. As main results, the analysis showed that the highes... [more]

Solar energy forecasting is considered an essential scientific aspect in supporting efforts to integrate solar energy into power grids. Moreover, solar energy forecasting plays an essential role in mitigating greenhouse gas emissions and conserving energy for future use. This study conducted a bibliometric analysis to assess solar energy forecasting research studies evolution at the continental (Africa) and southern Africa levels. Key aspects of analysis included (i) scientific research trends, (ii) nature of collaboration networks, (iii) co-occurrence of keywords and (iv) emerging themes in solar energy forecasting over the last two decades, between the years 2000−2021. The results indicate that solar energy forecasting research has, on average, expanded by 6.4% and 3.3% in Africa and southern Africa, respectively. Based on the study context, solar energy forecasting research only gained momentum in 2015, peaking in 2019, but it is generally still subtle. The scientific mapping illust... [more]

In recent years, large-capacity, high-head pump−turbine units have been developed for pumped storage power plants to effectively utilise water energy and store large amounts of electricity. Compared with the traditional Francis turbine unit, the radial distance between the trailing edge of the guide vanes and the leading edge of runner blades of high-head pump−turbine unit is smaller, so the rotor−stator interaction and the corresponding pressure fluctuations in the vaneless space of pumped storage units are more intense. The pressure fluctuations with high amplitudes and high frequencies induced by rotor−stator interaction (RSI) become the main hydraulic excitation source for the structures of the unit and may cause violent vibration and fatigue damage to structural components, and seriously affect the safe operation of the units. In this paper, the RSI of a high-head pump−turbine in turbine mode of operation is studied in detail by means of site measurement and full three-dimensional... [more]

Greenhouse gas emissions anywhere across the value chain cause the global temperature to rise. A responsible net-zero strategy is reducing and removing direct and indirect greenhouse gas emissions. The current net-zero actions aim to offset rather than reduce or remove life cycle greenhouse gas emissions (GHG). Unless the demands/consumptions are reduced, net-zero actions will merely be a burden-shifting practice. Scope 3 emissions are considered in the life cycle assessment (LCA) of goods and services and account for direct and indirect emissions with imported goods and services. Scope 3 emission tariff seems an effective way to shift consumption patterns to carbon-neutral options. This article explores tools and systems for ‘just transition’ using three buckets of scientific questions: (1) Technical: which GHG to remove, when, where, and by what mechanism; (2) Social-Policy: how to share GHG obligations between stakeholders to deliver the UN SDGs; (3) Data: how to create robust, trus... [more]

Machine learning (ML) could be used to overcome one of the largest sources of uncertainty in wind resource assessment: to accurately predict the wind speed (WS) at the wind turbine hub height. Therefore, this research defined and evaluated the performance of seven ML supervised algorithms (regressions, decision tree, support vector machines, and an ensemble method) trained with meteorological mast data (temperature, humidity, wind direction, and wind speeds at 50 and 75 m), and mesoscale data below 80 m (from the New European Wind Atlas) to predict the WS at the height of 102 m. The results were compared with the conventional method used in wind energy assessments to vertically extrapolate the WS, the power law. It was proved that the ML models overcome the conventional method in terms of the prediction errors and the coefficient of determination. The main advantage of ML over the power-law was that ML performed the task using either only mesoscale data (described in scenario A), only... [more]

Superior fuel economy, higher torque and durability have led to the diesel engine being widely used in a variety of fields of application, such as road transport, agricultural vehicles, earth moving machines and marine propulsion, as well as fixed installations for electrical power generation. However, diesel engines are plagued by high emissions of nitrogen oxides (NOx), particulate matter (PM) and carbon dioxide when conventional fuel is used. One possible solution is to use low-carbon gaseous fuel alongside diesel fuel by operating in a dual-fuel (DF) configuration, as this system provides a low implementation cost alternative for the improvement of combustion efficiency in the conventional diesel engine. An initial step in this direction involved the replacement of diesel fuel with natural gas. However, the consequent high levels of unburned hydrocarbons produced due to non-optimized engines led to a shift to carbon-free fuels, such as hydrogen. Hydrogen can be injected into the in... [more]

Nowadays, air conditioning consumes, on average, around one-fifth of the total power used in buildings globally. The present paper aims to provide the present status on the employment of Earth-to-Air Heat eXchangers (EAHX) to contain the consumption of energy and to reduce the effect on the environment in response to the Montreal and Kyoto protocols in a way to achieve cleaner energy production with a low Global Warming Potential (GWP) and a low ozone depletion potential (ODP). Different peculiarities and applications (direct or hybrid) are critically analyzed and reviewed. Specifically, in this paper, the different hybrid applications presented in the literature, where the Earth-to-Air Heat eXchangers are coupled to advanced systems, are reviewed. Finally, an IoT-based EAHX control system plan is reported and discussed to optimize energy efficiency and thermal comfort to suit operating conditions under different time zones.