An active prechamber turbulent ignition system is a forced ignition method for internal combustion engines fueled with low reactivity fuels, i.e., natural gas and gasoline, which could expand the lean-burn limit, promote flame propagation, and ensure cyclic stability. In the present study, the effects of charge concentration stratifications inside the prechamber on the jet characteristics and combustion process were numerically investigated using CONVERGE software coupled with a reduced methane mechanism by the coupling control of spark timing and prechamber global equivalence ratio. The results show that the jet characteristics and ignition mechanisms can be regulated by controlling the prechamber global equivalence ratio and spark timing. On the one hand, as the prechamber global equivalence ratio increases, the velocity of the jet increases firstly and then decreases, the temperature drops, and OH and CH2O radicals are reduced, but the stable combustion intermediates, CO and H2, are... [more]

This paper develops a multi-objective co-design optimization framework for the optimal sizing and selection of battery and power electronics in hybrid battery energy storage systems (HBESSs) connected to the grid. The co-design optimization approach is crucial for such a complex system with coupled subcomponents. To this end, a nondominated sorting genetic algorithm (NSGA-II) is used for optimal sizing and selection of technologies in the design of the HBESS, considering design parameters such as cost, efficiency, and lifetime. The interoperable framework is applied considering three first-life battery cells and one second-life battery cell for forming two independent battery packs as a hybrid battery unit and considers two power conversion architectures for interfacing the hybrid battery unit to the grid with different power stages and levels of modularity. Finally, the globally best HBESS system obtained as the output of the framework is made up of LTO first-life and LFP second-life... [more]

In this paper, a new type of microencapsulated phase change materials (MPCMs) with docosane as the core and titanium dioxide (TiO2) as the shell was prepared by in situ polymerization. Its phase transition temperature was approximately 40 °C, and it can be used as a phase change material (PCM) in a low-temperature solar heat collection system. The properties of the new material were examined including the microstructure, the chemical elements on the surface of the microcapsules, and thermal conductivity. In addition, to obtain the optimized formula of the microcapsules, single-factor analysis on the emulsifier type, its mass fraction, ultrasonic oscillation time, pH, and core−shell ratio were performed. The results showed that the MPCMs prepared in this paper had a particle size of 2−5 μm and were spherical. Its surface was uniform and smooth without cracks, and the TiO2 was well dispersed around the docosane, completely coating the docosane without impurities. The MPCMs had good perfo... [more]

This paper studies secure consensus control for multi-agent systems subject to denial-of-service (DoS) attacks. The DoS attacks cause changes in topologies, which will destroy the channels of communication and result in network paralysis. Unlike the existing publications with Markov switching, this paper mainly studies the topological structure changes of the subsystem models after DoS attacks. To ensure the consensus of systems, this paper designs an event triggered to reduce the use of the controller and decrease the influence of channel breaks off caused by DoS attacks. On this basis, different Lyapunov functions are established in each period of attack. Then, stochastic and Lyapunov stable theory is used to form the consensus criteria. Moreover, Zeno behavior is excluded by theoretical analysis. Finally, the simulation experiment proves the effectiveness of the proposed protocol.

The continuous health monitoring of PV modules is mandatory to maintain their high efficiency and minimize power losses due to faults or failures. In this work, a low-cost embedded tracer is developed to measure the I−V curve of a PV module in less than 0.2 s. The data are used to extract the five parameters of the single-diode model and its main characteristics (open-circuit voltage, short-circuit current, and maximum power). Experimental data are used to validate the analytical model and evaluate the two fault diagnosis methods, using as fault features the parameters of the single-diode model or the main characteristics of the I−V curve. The results, based on field data under different temperatures and irradiances, show that the degradation of series and shunt resistances could be detected more accurately with the main characteristics rather than with the parameters. However, the estimated parameters could still be used to monitor the long-term degradation effects.

As research on wind energy has progressed, it has broadened from a focus on the wind turbine to include the entire wind farm. In particular, methods to mitigate the negative effects of upstream wakes on downstream turbines have received significant attention. One such mitigation method is axial induction control (AIC) in which upstream turbines are derated to reduce the momentum deficits in their wakes, leaving higher speed flow for downstream turbines. If performed correctly, it is theorized that the power production gains in downstream turbines can compensate for the power sacrificed by derating upstream turbines. Previous work has indicated that the “excess” energy left in the wake of the derated turbine is along the edges of the wake such that a turbine placed directly downstream will see little to no increase in power. To address this hypothesis, we performed a control and treatment experiment with model-scale turbines in a wide flume. Five turbines were arranged in three successi... [more]

In recent years, there has been an upsurge of studies on sustainable development. The majority of research focuses on developed countries and issues that are incompatible with developing nations. This study addresses a gap in the literature by reviewing the research on developed and developing economies, as well as their social and environmental boundaries, under the renewable energy and sustainable development (RESD) nexus. It also explores how RESD may be applied in extreme situations such as population increase, energy supply disruptions, and transportation shortfalls. The fundamental contribution of this paper is to provide detailed debate from the perspective of economic growth hypotheses and their relationship with energy usage and renewable energy solutions for sustainable growth and development.

Electric vehicles have a promising development prospect. As its core component, lithium-ion power battery plays a crucial role in different application scenarios. Aiming at the availability and safety of square ternary lithium batteries at different ambient temperatures and different current rates, charge-discharge cycle experiments are carried out to study the voltage, temperature and capacity changes of lithium batteries. The voltage plateau characteristics of lithium batteries under different working conditions are explored. The results show that when discharging at current rates of 0.1C, 0.25C, 0.5C, 0.75C, and 1C under the ambient temperature of −5 °C, 10 °C, 25 °C, and 40 °C, the terminal voltage of the battery changes smoothly during the voltage plateau period, the rise of the surface temperature has not reached the peak value, and the discharge capacity accounts for about 50%. The battery has better working performance. While at the ambient temperature of −20 °C, the discharge... [more]

The main aim of this paper is to analyze the effect of industrial agglomeration on the degree of interorganizational cooperation and the innovative performance of firms of the electricity supply sector in Spain. For this purpose, the agglomeration coefficient in each of the 50 provinces of Spain is calculated, based on secondary data from SABI database. Subsequently, primary data are obtained from a sample of 197 companies through a structured questionnaire. In this case, the PLS-SEM technique is used. The results show that there is a positive and significant relationship between the variables analyzed. It is concluded that industrial agglomeration and cooperation are relevant external factors that boost the innovative performance of firms and that business associations foster interorganizational cooperation.

In this study, we present an analytical modeling framework for wind turbine wakes under an arbitrary pressure gradient imposed by the base flow. The model is based on the conservation of the streamwise momentum and self-similarity of the wake velocity deficit. It builds on the model proposed by Shamsoddin and Porté-Agel, which only accounted for the imposed pressure gradient in the far wake. The effect of the imposed pressure gradient on the near wake velocity is estimated by using Bernoulli’s equation. Using the estimated near wake velocity as the starting point, the model then solves an ordinary differential equation to compute the streamwise evolution of the maximum velocity deficit in the turbine far wake. The model is validated against experimental data of wind turbine wakes on escarpments of varying geometries. In addition, a comparison is performed with a pressure gradient model which only accounts for the imposed pressure gradient in the far wake, and with a model that does not... [more]

Organic solar cells (OSCs) are a kind of device that can convert light energy into electrical energy, they possess the advantages of being lightweight, flexible, processable printing, and large-area production, and they are an effective way to alleviate energy deficiency and environmental pollution [...]

This work is devoted to the formulation of innovative SCADA-based methods for wind turbine performance analysis and interpretation. The work is organized as an academia−industry collaboration: three test cases are analyzed, two with hydraulic pitch control (Vestas V90 and V100) and one with electric pitch control (Senvion MM92). The investigation is based on the method of bins, on a polynomial regression applied to operation curves that have never been analyzed in detail in the literature before, and on correlation and causality analysis. A key point is the analysis of measurement channels related to the blade pitch control and to the rotor: pitch manifold pressure, pitch piston traveled distance and tower vibrations for the hydraulic pitch wind turbines, and blade pitch current for the electric pitch wind turbines. The main result of this study is that cases of noticeable under-performance are observed for the hydraulic pitch wind turbines, which are associated with pitch pressure dec... [more]

To maximize food waste utilization, it is necessary to understand the effect of process variables on product distribution. To this day, there is a lack of studies evaluating the effects of the multiple variables of HTC on food waste. A Design of Experiment (DoE) approach has been used to investigate the influence of three process variables on the product distribution and composition of process streams from the HTC of food waste. This work evaluates the effect of hydrothermal carbonization process conditions on the composition and utilization capabilities of hydrochar from food waste. Parametric analysis was carried out with a design of experiments of central composite rotatable design (CCRD) and response surface methodology (RSM). Derringer’s desirability function was employed to perform a multi-response evaluation. The optimized process conditions were 260.4 °C, 29.5 min reaction time, and 19.6% solid load. The predicted optimized responses were EMC = 2.7%, SY = 57.1%, EY = 84.7%, ED... [more]

Manufacturing facilities use about 35% of the domestic energy in the United States every year. Implementing an effective energy management system (EnMS) is one of the most important approaches to improve energy efficiency. However, the implementation of EnMS is low for many countries (including the US) and even for energy-intensive sectors. The reasons for the low implementation rate of energy management systems had been investigated by multiple researchers, but very few studies have focused on the barriers and challenges of implementing ISO 50001-based energy management systems. To contribute to this understudied area, this paper discusses the implementation and outcomes of the first Better Plants 50001 Ready Virtual In-plant Training. This paper first provides an overview of 50001 Ready and the 50001 Ready Navigator Tool. Then, it provides details on this training event and its outcomes. Finally, it discusses findings from the responses to 40 live polling questions about the status o... [more]

In this study, we considered a bridging strategy between qualitative and quantitative research with the aim of achieving complementarity. A pilot case study using the Sheffield Elicitation Framework “SHELF” to estimate appropriate inputs for a quantitative energy systems model (based on a qualitative energy future scenario) was used to gain insights. Of novelty are the ethnographic insights of an example translation procedure as well as the methodological approach of the translation procedure itself. This paper reports the findings from this exercise concerning the practicalities of applying such a technique and the observations from the expert elicitation process itself. Based on this pilot, we make two recommendations. The first is the importance of devising a strategy in projects, and research programmes, where bridging between qualitative and quantitative research activities would be most effective. The second is that observations of discussions during the expert elicitation proces... [more]

The growing impact of consumption on the environment has been attracting much attention from academics for the last couple of decades and has caused inquiries into the antecedents of responsible consumption. Previous studies focused on analyzing different antecedents of responsible consumption in various areas and contexts. However, very few studies investigated the antecedents of responsible consumption in the energy sector, and only a few referred to emerging European countries. The aim of the paper is to examine the effect of environmental awareness on responsible energy consumption. Data for this study have been collected using the survey methodology. A total of 1407 households were selected as a sample for the CAWI methods of gathering data. The territory of the study population is Poland. The methodology of research involves several measurement scales of theoretical constructs. The constructs′ reliability coefficients, as well as discriminant and convergent validity indices, show... [more]

In this paper, an algorithm for the maximum extraction of energy generated by photovoltaic (PV) systems was presented. The tracking of the global maximum point of the system is complex due to the non-linearity of the current-voltage (I-V) characteristic curve of the photovoltaic modules, as they vary according to the temperature and solar irradiation in the module. To obtain the best energy efficiency in these systems, it is important that the generation is delivering the maximum power available through the arrangement. In order to solve such problems, in this work an efficient MPPT-FA method was proposed, which showed good traceability when compared to traditional methods. Most traditional MPPT techniques are not able to find the global maximum point to extract the maximum power provided by the PV system. Finally, the Firefly Metaheuristic MPPT method proved to be robust against several partial shading scenarios. Simulations were presented to demonstrate the effectiveness of the propo... [more]

Photovoltaic power generation has high variability and uncertainty because it is affected by uncertain factors such as weather conditions. Therefore, probabilistic forecasting is useful for optimal operation and risk hedging in power systems with large amounts of photovoltaic power generation. However, deterministic forecasting is the mainstay of photovoltaic generation forecasting; there are few studies on probabilistic forecasting and feature selection from weather or time-oriented features in such forecasting. In this study, prediction intervals were generated by the lower upper bound estimation (LUBE) using neural networks with two outputs to make probabilistic modeling for predictions. The objective was to improve prediction interval coverage probability (PICP), mean prediction interval width (MPIW), continuous ranked probability score (CRPS), and loss, which is the integration of PICP and MPIW, by removing unnecessary features through feature selection. When features with high ga... [more]

This paper proposes the application of generation adequacy analysis for reliability evaluation of an insulated power generation system that supplies a FPSO (Floating Production Storage and Offloading) oil and gas production platform. The frequency and duration method was adopted for generating system reliability evaluation. The historical reliability data of the floating production storage and offloading platform power system and the continuous Markov process are used to determine the generator’s reliability model. The load model was also based on the platform daily peak load variation curve. The system risk indexes were obtained using Monte Carlo simulation. Two system scenarios were simulated using different failure data for one of the generators and the software PowerFactory© has been used as a tool for this simulation. For a complete generation system modeling, frequency and duration methods were developed to calculate the probabilities, frequencies and duration of the system state... [more]

In the traditional coal-mine gas-concentration prediction process, problems such as low timeliness of data and low efficiency of the prediction model in learning data features result in low accuracy of the final prediction. To solve these problems, a gas-concentration prediction method driven by the Spark Streaming framework is proposed. In this research study, the Spark Streaming framework, autoregressive integrated moving average (ARIMA) model and support vector machine (SVM) model are used to construct a new prediction model called the SPARS model. The Spark Streaming framework is used to process large batches of real-time streaming data in a short period of time, and the model can be used to intermittently update and optimize the prediction model so that the model can fully learn the characteristics of the data. At the same time, the advantages of the ARIMA model and SVM model for processing linear data and nonlinear data are combined to improve the model’s prediction efficiency an... [more]

The scramjet of hypersonic vehicles faces severe high-temperature challenges, but the heat sink available for scramjet cooling is extremely finite. It is necessary to optimize its power and thermal management system (PTMS) with a finite heat sink of hydrocarbon fuel. This paper proposes a two-level optimization method for the PTMS of hypersonic vehicles at Mach 6. The PTMS is based on a supercritical carbon dioxide (SCO2) closed Brayton cycle, and its heat sink is airborne hydrocarbon fuel. System-level optimization aims to obtain the optimal system parameters for the PTMS. The minimum fuel weight penalty and the minimum heat sink consumption of fuel are the optimization objectives. The segmental (SEG) method is used to analyze the internal temperature distribution of fuel−SCO2 heat exchangers in the system-level optimal solution set. This ensures the selected optimal solutions meet the requirement of a pinch temperature difference greater than or equal to 10 °C. Further, the component... [more]

An accurate understanding of molecular structure evolution during pyrolysis is essential for the clean utilization of coal. In this study, middle-rank coal was taken as the research subject, and vitrinite and inertinite samples were stripped from coal using a hand picking and sink−float separation process. In situ Fourier transform infrared (FTIR) spectroscopy and in situ X-ray diffraction (XRD) were performed to compare the macromolecular structure changes between vitrinite and inertinite during pyrolysis. The results show that the aromaticity (I), the polycondensation degree of aromatic rings (DOC), the average lateral sizes (La) of basic structure unit (BSU), and the stacking heights (Lc) of BSU in both vitrinite and inertinite during pyrolysis increase continuously with increasing temperature. The values of these parameters for inertinite are higher than those of vitrinite, suggesting that the aromatization degree of inertinite has always been higher than that of vitrinite. In situ... [more]

Considering the battery-failure-induced catastrophic events reported frequently, the early fault warning of batteries is essential to the safety of electric vehicles (EVs). Motivated by this, a novel data-driven method for early-stage battery-fault warning is proposed in this paper by the fusion of the short-text mining and the grey correlation. In particular, the short-text mining approach is exploited to identify the fault information recorded in the maintenance and service documents and further to analyze the categories of battery faults in EVs statistically. The grey correlation algorithm is employed to build the relevance between the vehicle states and typical battery faults, which contributes to extracting the key features of corresponding failures. A key fault-prediction model of electric buses based on big data is then established on the key feature variables. Different selections of kernel functions and hyperparameters are scrutinized to optimize the performance of warning. Th... [more]

Aiming to accurately identify the state of health (SOH) and the remaining useful life (RUL) of lithium-ion batteries, in this paper, we propose an algorithm for the health factor extraction and SOH prediction of the batteries based on discrete wavelet transform and the Cauchy−Gaussian variation tent sparrow search algorithm (DWT-CGTSSA). Firstly, concerning the inconsistent data length, discrete wavelet transform (DWT) was adopted to decompose the battery’s signals and extract features. Then, the Cauchy−Gaussian variation tent sparrow search algorithm (CGTSSA) was utilized to extract features and obtain the optimal feature subset after encoding. Finally, the optimal feature subset was used to establish a prediction model based on CatBoost for predicting the SOH of lithium-ion batteries. Experiments were conducted for verification. The experimental results showed that the model established in this research is capable of realizing the prediction between different battery packs. The B0005... [more]

Thermal insulation bio-composites made of plant origin by-products as bio-aggregates are one of the ways to decrease the impact of the building and construction sector on CO2 emissions. In this study, three bio-aggregates were analysed for their potential use in the production of bio-composites with potato starch binder. Technologically important properties, such as particle size, shape and compacted bulk density, as well as properties of the resulting bio-composites were identified. The main characteristics of the aggregates are relatively similar: density of 80−100 kg/m3, thermal conductivity of 0.042−0.045 W/m∙K, specific heat capacity of 1240−1330 J/g∙K, kinetic water absorption from 456−584%. This leads to similar basic properties of the produced bio-composites: density around 200 kg/m3, thermal conductivity 0.053−0.062 W/m∙K, specific heat capacity 1250−1450 J/kg∙K, with a difference in compressive strength ranging from 0.2 to 0.8 MPa. Created starch binder and agricultural by-pr... [more]