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]

Enterprise risk management (ERM) is an important element of an efficient and comprehensive corporate governance system. It represents a combination of activities that minimise the negative impacts of the risk exposures on the company’s value and long-term corporate sustainability. Recently, there has been a growing awareness on the role and importance of the risk management function. Such trends are partly driven by the consequences of the last economic and financial crisis on the one hand, and on the other by legal and regulatory requirements. The economic downturn caused by the COVID-19 pandemic, volatility in the energy markets and increased uncertainty expected in the upcoming period reiterate the importance of timely risk management practices, because organisations with developed risk management systems are more resilient in case of crisis. This paper analyses the organisation and level of development of ERM systems in the ten largest European electric power companies. The compani... [more]

Within the last few decades, the issue of the environmental performance of European financial institutions has become a significant feature of their strategic plans. Financial institutions can contribute through their own activities and investments, and also through their relationship with economic sectors and consumers, in decreasing environmental footprint. The purpose of this research is to investigate the determinants that affect the environmental performance of European financial institutions. Financial markets have been selected as the main research field for this study, as it presents an opportunity for environmental policy and is useful in view of the need for a wider range of policy instruments. Moreover, on a more practical level, financial institutions can interact with the environment in several ways, such as investors, innovators, valuers, powerful stakeholders, and polluters. The study is based on a mixed methodology approach, which integrates: (i) bibliometric analysis b... [more]

This work is a survey of current trends in applications of PMUs. PMUs have the potential to solve major problems in the areas of power system estimation, protection, and stability. A variety of methods are being used for these purposes, including statistical techniques, mathematical transformations, probability, and AI. The results produced by the techniques reviewed in this work are promising, but there is work to be performed in the context of implementation and standardization. As the smart grid initiative continues to advance, the number of intelligent devices monitoring the power grid continues to increase. PMUs are at the center of this initiative, and as a result, each year more PMUs are deployed across the grid. Since their introduction, myriad solutions based on PMU-technology have been suggested. The high sampling rates and synchronized measurements provided by PMUs are expected to drive significant advancements across multiple fields, such as the protection, estimation, and... [more]

The noncontact heating technology of IH targets heat directly where it is needed through the electromagnetic energy adsorption and conversion of magnetic materials. Unlike conventional heating methods, the heat generated by electromagnetic induction of magnetic materials can be applied directly into the reactor without heating the entire device; this new heating method is not only more energy efficient but also safer, cleaner and more sustainable if renewable electricity is adopted; moreover, magnetic catalysts can be recovered and reused by separating chemical reactants and products from the catalyst by the application of a magnetic field, and it can provide the required heat source for the reaction without altering its catalytic properties. Magnetic catalysts with an electric field have been applied to some industrial areas, such as the preparation of new materials, catalytic oxidation reactions, and high-temperature heat absorption reactions. It is a trend that is used in the hydrog... [more]

Quantitative characterisation through mineral liberation analysis is required for effective minerals processing in areas such as mineral deposits, tailings and reservoirs in industries for resources, environment and materials science. Current practices in mineral liberation analysis are based on 2D representations, leading to systematic errors in the extrapolation to 3D volumetric properties. The rapid development of X-ray microcomputed tomography (μCT) opens new opportunities for 3D analysis of features such as particle- and grain-size characterisation, determination of particle densities and shape factors, estimation of mineral associations, and liberation and locking. To date, no simple non-destructive method exists for 3D mineral liberation analysis. We present a new development based on combining μCT with micro-X-ray fluorescence (μXRF) using deep learning. We demonstrate successful semi-automated multimodal analysis of a crystalline magmatic rock by obtaining 2D μXRF mineral maps... [more]

In the coming decades, the number of end-of-life (EoL) traction battery systems will increase sharply. The disassembly of the system to the battery module is necessary to recycle the battery modules or to be able to use them for further second-life applications. These different recovery paths are important pathways to archive a circular battery supply chain. So far, little knowledge about the disassembling of EoL batteries exists. Based on a disassembly experiment of a plug-in hybrid battery system, we present results regarding the battery set-up, including their fasteners, the necessary disassembly steps, and the sequence. Upon the experimental data, we assess the disassembly duration of the battery system under uncertainty with a fuzzy logic approach. The results indicate that a disassembling time of about 22 min is expected for the battery system in the field study if one worker conducts the process. An estimation for disassembling costs per battery system is performed for a plant i... [more]

The horizontal-axis ocean current turbine under investigation is a three-blade rotor that uses the flow of water to rotate its blade. The mechanical energy of a turbine is converted into electrical energy using a generator. The horizontal-axis ocean current turbine provides a nongrid robust and sustainable power source. In this study, the blade design is optimized to achieve higher efficiency, as the blade design of the hydrokinetic turbine has a considerable effect on its output efficiency. All the simulations of this turbine are performed on ANSYS software, based on the Reynolds Averaged Navier−Stokes (RANS) equations. Three-dimensional (CFD) simulations are then performed to evaluate the performance of the rotor at a steady state. To examine the turbine’s efficiency, the inner diameter of the rotor is varied in all three cases. The attained result concludes that the highest Cm value is about 0.24 J at a tip-speed ratio (TSR) of 0.8 at a constant speed of 0.7 m/s. From 1 TSR onward,... [more]

The Ri-Qing-Wei basin is located in the central Sulu Orogeny on the eastern side of the Tanlu fault zone in eastern Shandong province. To the north, the Jiaonan uplift separates it from the Jiaolai basin, where drilling in the lower Cretaceous sedimentary rock of the Laiyang group has indicated good oil and gas reserves. Drilling in the Ri-Qing-Wei basin, in contrast, is in the preliminary exploration stage. Lingke 1, the only scientific well, is on Lingshan Island on the basin boundary, and it encountered a large set of source rocks 700 m thick. The two basins were comprehensively compared and analyzed based on comprehensive fieldwork, drilling, core data, seismic profiling, sedimentary filling sequence, tectonic evolution history, basin burial history, geothermal history, and geochemical characteristics of the source rocks. The results showed three things: (1) from the late Jurassic to the early Cretaceous (the Laiyang period), subduction of the paleo-Pacific plate under the Eurasian... [more]

This investigation shows the results of a coupled numerical and experimental study on the solidification and melting of spherical capsules and the development of correlations for solidification time and melting time with parameters that impact the complete phase change time of nanofluids and water with and without polyethylene glycol inside plastic spherical capsules. Experiments included the investigation of different configurations of plastic spherical capsule diameters, external temperature, the initial temperature of phase change material (PCM), and PCMs. The PCMs used were water, water with a concentration of polyethylene glycol from 10% to 50%, and multi-wall carbon nanotubes functionalized with carboxylic acid group (COOH-MWCNT) with MWCNT at 0.125, 0.25, 0.5, and 1.0%. The simplified model was validated with available experimental results from the present work and from the literature, showing maximum deviations in the range of 0.25 to 12%. The simulation results showed that the... [more]