bluuebunny/crossref_metadata_2025 huggingface dataset:
Grey-Wolf-Based Wang’s Demons for Retinal Image Registration
Authors: Chakraborty Sayan , Pradhan Ratika , S. Ashour Amira , Moraru Luminita , Dey Nilanjan
Published: June 2020

Image registration has an imperative role in medical imaging. In this work, a grey-wolf optimizer (GWO)-based non-rigid demons registration is proposed to support the retinal image registration process. A comparative study of the proposed GWO-based demons registration framework with cuckoo search, firefly algorithm, and particle swarm optimization-based demons registration is conducted. In addition, a comparative analysis of different demons registration methods, such as Wang’s demons, Tang’s demons, and Thirion’s demons which are optimized using the proposed GWO is carried out. The results established the superiority of the GWO-based framework which achieved 0.9977 correlation, and fast processing compared to the use of the other optimization algorithms. Moreover, GWO-based Wang’s demons performed better accuracy compared to the Tang’s demons and Thirion’s demons framework. It also achieved the best less registration error of 8.36 × 10−5.
Towards Lean Teaching: Non-Value-Added Issues in Education
Authors: Martínez Sanahuja Silvia
Published: June 2020

Lean Thinking is a methodology based on improving the efficiency of productive processes by removing non-value-added issues. This methodology was firstly applied in the manufacturing industry, but it has also been applied to many service companies, bringing very good results. In the last decade, some works have tried to research the adaptation of Lean principles and practices to teaching, especially in technology and other STEAM subjects. In this sense, the aim of this work is to deepen this new trend by establishing what issues are non-value-added (waste) ones in education and classifying these kinds of waste in order to be able to analyze how to eliminate them. For this purpose, we adapt the classification made in other kinds of processes and extend other authors’ findings regarding this topic.
The Improvement Switching Technique for High Step-Up DC-DC Boost Converter
Authors: Truong Viet-Anh , Luong Xuan-Truong , Nguyen Phan-Thanh , Quach Thanh-Hai
Published: June 2020

This paper proposes the non-isolated DC-DC converter with high boost ratios and efficiency. We suggest boosting methods including voltage multiplier cells or coupled inductors. However, both techniques have a limited constant voltage multiplier coefficient according to the fixed configuration. Therefore, in the proposed method, we change the multiplier factor (as the number of activity levels) and combine it with the turn of the appropriate duty cycle; these factors are considered at the same time in order to increase the energy conversion efficiency and expand the control area of the duty cycle. A mathematical analysis of the losses of the components in operation modes shows that the boost ratio and efficiency are functions of the number of activity levels and duty cycle. Therefore, this paper proposes an algorithm for tracking the activity levels and duty cycle in order to obtain the maximum efficiency. The simulations produced with the Powersim-PSIM software, and the experiments with load capacities of 250 W, 500 W and 1000 W, boosting the ratio by more than ten times, were conducted in order to clarify the capabilities of the proposed configuration.
Building an Energy-Efficient Ad-Hoc Network for Wildlife Observation
Authors: Camal Luis , Aksanli Baris
Published: June 2020

This study evaluated the design of an energy-efficient ad-hoc network used for wildlife observations, particularly in order to understand the social relationships in an animal group, where the distance between individuals, i.e., proximity, can be used to measure a relationship. Our proposed network consists of a full mesh topology and contains nodes that communicate via Bluetooth Low Energy (BLE) in advertisement mode. The initial hardware configuration and software algorithm duty cycles the BLE communication to on and off states using a parameter called the BLE active triggering interval. The algorithm is improved by placing the BLE subsystem and CPU in deep sleep when there are no BLE or CPU tasks to process. This improves the power performance by up to 94.48%. To scale up power optimization and track the trade-off between power and throughput, we created a simulator that modeled our network with dynamic wireless sensor nodes. The simulator verified the base case hardware results. It also showed a median power performance increase of 97.79% in comparison to the base case, yet throughput decreased by 66.65%. The highest power performance increased by 98.89% when a wireless sensor node was configured with a BLE active triggering interval of 50 s and its CPU was set to 14 MHz; however, the simulator showed a throughput drop of 79.97%. Depending on the application, a design may tolerate the decline in throughput to achieve higher power performance.
Low-Cost LoRaWAN Node for Agro-Intelligence IoT
Authors: Valente Antonio , Silva Sérgio , Duarte Diogo , Cabral Pinto Filipe , Soares Salviano
Published: June 2020

Intelligent agriculture in general, but especially when agricultural fields are very heterogeneous, requires a large number of sensors in order to obtain an effective control and thus increase productivity. This need becomes more evident in vineyards on the farms of the demarcated Douro region due to the specificities of the territory and the vineyards themselves. Thus, it is necessary to have low cost sensors which are, essentially, easy to install and maintain. In the present work, a node with these characteristics was developed, which, in addition, is low consumption and communicates wirelessly through a Long Rang Wide Area Network (LoRaWAN) network. To obtain an easy installation, a library of clusters was created for the LoRaWAN network and dedicated to sensors used in agriculture, especially those using an asynchronous serial protocol for intelligent sensors. Three nodes were developed and tested with sensors used in agriculture to measure several environmental parameters (soil and air temperature; wind speed, gust and direction; soil water content, water tension and electrical conductivity; solar radiation; precipitation; atmospheric and vapor pressure; relative humidity; and lightning strikes count). The three nodes send data to a server through an existing gateway on the farm. The data are decoded and sent to an Internet-of-Things analytics platform where it is aggregated, viewed and analyzed. Samples of the data collected are presented. The developed nodes are of small dimensions ( 85 × 65 × 35 m m ), thus making them easy to handle and install. Energy consumption depends on the distance to the gateway, and the number and type of sensors connected to each node. In the implemented cases, the maximum consumption was ≈ 400 μ A . The development of a cluster based library makes the node plug-and-play. The developed nodes will be a great step forward for the use of wireless sensors in smart agriculture in Douro vineyards.
Cyclostationary Impulsive Noise Mitigation in the Presence of Cyclic Frequency Offset for Narrowband Powerline Communication Systems
Authors: Chien Ying-Ren , Lin Jian-Liang , Tsao Hen-Wai
Published: June 2020

Cyclostationary impulsive noise (CSIN) is the dominant source of additive noise in narrowband powerline communication (NB-PLC) systems. Frequency-shift (FRESH) filters have been applied to NB-PLC systems based on orthogonal frequency division multiplexing (OFDM) to mitigate CSIN and enhance the OFDM signals by leveraging the difference in cyclic frequency associated with CSIN and OFDM data symbols. Note that under the effects of frequency fluctuation in the mains voltage, the cyclic frequency offset associated with CSIN can degrade the performance of FRESH-filter receivers. To alleviate such an impact on the FRESH-filter receivers, this paper presents a method for the estimation of the cyclic frequency offset by observing phase variations in the coefficients of the FRESH filter. Computer simulations based on IEEE 1901.2 specifications demonstrate the effectiveness of the proposed scheme in suppressing the cyclic frequency relative error by at least 15.45 dB. Following compensation for the cyclic frequency offset, the proposed scheme achieved a bit error rate of 10 − 4 with an E b / N 0 loss of only 0.7 dB, compared with the ideal case. Compared to the case without the cyclic frequency offset compensation, the proposed scheme achieved an E b / N 0 gain of 2.7 dB.
Progress in Violet Light-Emitting Diodes Based on ZnO/GaN Heterojunction
Authors: Macaluso Roberto , Lullo Giuseppe , Crupi Isodiana , Sciré Daniele , Caruso Fulvio , Feltin Eric , Mosca Mauro
Published: June 2020

Progress in light-emitting diodes (LEDs) based on ZnO/GaN heterojunctions has run into several obstacles during the last twenty years. While both the energy bandgap and lattice parameter of the two semiconductors are favorable to the development of such devices, other features related to the electrical and structural properties of the GaN layer prevent an efficient radiative recombination. This work illustrates some advances made on ZnO/GaN-based LEDs, by using high-thickness GaN layers for the p-region of the device and an ad hoc device topology. Heterojunction LEDs consist of a quasicoalesced non-intentionally doped ZnO nanorod layer deposited by chemical bath deposition onto a metal–organic vapor-phase epitaxy -grown epitaxial layer of p-doped GaN. Circular 200 μm-sized violet-emitting LEDs with a p-n contact distance as low as 3 μm exhibit a turn-on voltage of 3 V, and an emitting optical power at 395 nm of a few microwatts. Electroluminescence spectrum investigation shows that the emissive process can be ascribed to four different recombination transitions, dominated by the electron-hole recombinations on the ZnO side.
Comparison of Design Characteristics and Customization Protocols for Swimming Goggles
Authors: Park Jangwoon , Mehrubeoglu Mehrube , Kim Jungyoon , Park Jaehyun
Published: June 2020

Swimming goggles are important tools for swimmers; however, most of the commercialized swimming goggles are designed as one-size-fits-all, which may cause improper fit to a wearer’s facial shape. The present study is intended to review and compare the design characteristics of the existing swimming goggles and the published customization protocols of swimming goggles. The detailed design characteristics of lens, strap, gasket, and nose bridge of 26 commercialized swimming goggles were reviewed, and the dimensions (length, width, and depth) of five swimming goggles are summarized in this paper. Next, the customization protocols of swimming goggles were investigated, which consisted of three major steps: first step involves collecting a wearer’s 2D or 3D facial shape including eye and nasal root areas by using a hand-held scanner, and then using this scanned data to create a 3D contour shape of customized swimming goggles in a computer-aided design (CAD) environment. Second step requires the fabrication of the designed 3D CAD model of the customized swimming goggles by using a 3D printer using transparent and flexible materials. Third step includes conducting validation tests to evaluate the performance of the customized swimming goggles in terms of waterproofness and wearing comfort by comparing with the other existing goggles. To the best of our knowledge, this is the first paper that reviews the design characteristics of swimming goggles. The review results presented in this paper are particularly useful to develop not only swimming goggles, but also other types of wearable products such as safety goggles, military goggles, and any sort of sports goggles.
Novel Biased Normalized Cuts Approach for the Automatic Segmentation of the Conjunctiva
Authors: Dimauro Giovanni , Simone Lorenzo
Published: June 2020

Anemia is a common public health disease diffused worldwide. In many cases it affects the daily lives of patients needing medical assistance and continuous monitoring. Medical literature states empirical evidence of a correlation between conjunctival pallor on physical examinations and its association with anemia diagnosis. Although humans exhibit a natural expertise in pattern recognition and associative skills based on hue properties, the variance of estimates is high, requiring blood sampling even for monitoring. To design automatic systems for the objective evaluation of pallor utilizing digital images of the conjunctiva, it is necessary to obtain reliable automatic segmentation of the eyelid conjunctiva. In this study, we propose a graph partitioning segmentation approach. The semantic segmentation procedure of a diagnostically meaningful region of interest has been proposed for exploiting normalized cuts for perceptual grouping, thereby introducing a bias towards spectrophotometry features of hemoglobin. The reliability of the identification of the region of interest is demonstrated both with standard metrics and by measuring the correlation between the color of the ROI and the hemoglobin level based on 94 samples distributed in relation to age, sex and hemoglobin concentration. The region of interest automatically segmented is suitable for diagnostic procedures based on quantitative hemoglobin estimation of exposed tissues of the conjunctiva.
Multiband SHEPWM Control Technology Based on Walsh Functions
Authors: Li Song , Song Guizhi , Ye Manyuan , Ren Wei , Wei Qiwen
Published: June 2020

The drawback of modulation ratio limitation in selective harmonic elimination pulse width modulation (SHEPWM) technology based on Walsh function transformation. In order to solve this problem, a multiband SHEPWM control technology method for a multilevel inverter based on Walsh functions is proposed. By analyzing multiband SHEPWM for multilevel inverter voltage waveforms under a Fourier series transform, the unified nonlinear multiband SHEPWM equations for a multilevel inverter with a modulation index varying from 0 to 1 can be generalized. The equations can be solved by Walsh function transform. In this way, the difficulties faced in expanding the modulation index, online calculation, and real-time control are resolved simultaneously. A seven-level inverter is taken as the example, for which the piecewise linear equations of Walsh functions under different bands and the trajectories of switching angles are given. Meanwhile, the conditions for multiple sets of solutions at such a point where the modulation index is switched over are also taken into account. The feasibility of the proposed method is verified by simulation based on MATLAB and SIMULINK. Finally, the feasibility of the practical application is proved by the experiment based on Digital Signal Processor (DSP).
Innovative Deep Neural Network Modeling for Fine-Grained Chinese Entity Recognition
Authors: Liu Jingang , Xia Chunhe , Yan Haihua , Xu Wenjing
Published: June 2020

Named entity recognition (NER) is a basic but crucial task in the field of natural language processing (NLP) and big data analysis. The recognition of named entities based on Chinese is more complicated and difficult than English, which makes the task of NER in Chinese more challenging. In particular, fine-grained named entity recognition is more challenging than traditional named entity recognition tasks, mainly because fine-grained tasks have higher requirements for the ability of automatic feature extraction and information representation of deep neural models. In this paper, we propose an innovative neural network model named En2BiLSTM-CRF to improve the effect of fine-grained Chinese entity recognition tasks. This proposed model including the initial encoding layer, the enhanced encoding layer, and the decoding layer combines the advantages of pre-training model encoding, dual bidirectional long short-term memory (BiLSTM) networks, and a residual connection mechanism. Hence, it can encode information multiple times and extract contextual features hierarchically. We conducted sufficient experiments on two representative datasets using multiple important metrics and compared them with other advanced baselines. We present promising results showing that our proposed En2BiLSTM-CRF has better performance as well as better generalization ability in both fine-grained and coarse-grained Chinese entity recognition tasks.
Research and Prospects for the Development of Alternative Fuels in the Transport Sector in Poland: A Review
Authors: Burchart-Korol Dorota , Gazda-Grzywacz Magdalena , Zarębska Katarzyna
Published: June 2020

The aim of this publication is to review the current state and possibilities of developing electromobility and alternative fuels in Poland. It was found that the current market for alternative fuels in Poland is insufficiently developed. At the end of 2019 in Poland, liquefied petroleum gas-powered cars accounted for approximately 3.3 million pieces, which amounts to 14.3% all passenger vehicles up to 3.5 tonnes of gross vehicle weight. There were over 9000 electric cars on the road, the share of which accounted for 0.04% of domestic passenger transport. The lack of a sufficient number of charging points, inhibiting the development of electromobility, was also noted. There were approximately 4000 (0.02%) passenger cars powered by compressed natural gas. Liquefied gas-powered vehicles were exclusively public transport vehicles or trucks. The share of biofuels in the Polish transport sector stands at 4%, while European Union requirements are at a level of 10%. Although there is huge potential for the use of hydrogen as an alternative to conventional transport fuels in Poland, just one hydrogen-powered vehicle has been registered in the country so far, with no filling station in existence for this fuel. The synthetic fuel sector is in the planning stage.
Impact of Climate Change on Wave Energy Resource in the Mediterranean Coast of Morocco
Authors: Sierra Joan Pau , Castrillo Ricard , Mestres Marc , Mösso César , Lionello Piero , Marzo Luigi
Published: June 2020

The increasing demand for energy and the impacts generated by CO2 emissions make it necessary to harness all possible renewable sources of energy, like wave power. Nevertheless, climate change may generate significant variations in the amount of wave energy available in a certain area. The aim of this paper is to study potential changes in the wave energy resource in the Mediterranean coast of Morocco due to climate change. To do this, wave datasets obtained by four institutes during the Coordinated Regional Climate Downscaling Experiment in the Mediterranean Region (Med-CORDEX) project are used. The future conditions correspond to the RCP4.5 and RCP8.5 scenarios from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. The results show that projected future wave power is very similar to that of the present considering the whole area, although at some specific points there are slight changes that are more evident for the RCP8.5 scenario. Another remarkable result of this study is the significant increase of the temporal variability of wave power in future scenarios, in particular for RCP8.5. This will be detrimental for the deployment of wave energy converters in this area since their energy output will be more unevenly distributed over time, thus decreasing their efficiency.
A Novel Approach for the Determination of Sorption Equilibria and Sorption Enthalpy Used for MOF Aluminium Fumarate with Water
Authors: Laurenz Eric , Füldner Gerrit , Schnabel Lena , Schmitz Gerhard
Published: June 2020

Adsorption chillers offer an environmentally friendly solution for the valorisation of waste or solar heat for cooling demands. A recent application is high efficiency data centre cooling, where heat from CPUs is used to drive the process, providing cooling for auxiliary loads. The metal organic framework aluminium fumarate with water is potentially a suitable material pair for this low temperature driven application. A targeted heat exchanger design is a prerequisite for competitiveness, requiring, amongst other things, a sound understanding of adsorption equilibria and adsorption enthalpy. A novel method is employed for their determination based on small isothermal and isochoric state changes, applied with an apparatus developed initially for volume swing frequency response measurement, to samples with a binder-based adsorbent coating. The adsorption enthalpy is calculated through the Clausius–Clapeyron equation from the obtained slopes of the isotherm and isobar, while the absolute uptake is determined volumetrically. The isotherm confirms the step-like form known for aluminium fumarate, with a temperature dependent inflection point at p rel ≈ 0.25, 0.28 and 0.33 for 30 °C, 40 °C and 60 °C. The calculated differential enthalpy of adsorption is 2.90 ± 0.05 MJ/kg (52.2 ± 1.0 kJ/mol) on average, which is about 10–15% higher than expected by a simple Dubinin approximation.
Multiple Site Intraday Solar Irradiance Forecasting by Machine Learning Algorithms: MGGP and MLP Neural Networks
Authors: Mendonça de Paiva Gabriel , Pires Pimentel Sergio , Pinheiro Alvarenga Bernardo , Gonçalves Marra Enes , Mussetta Marco , Leva Sonia
Published: June 2020

The forecasting of solar irradiance in photovoltaic power generation is an important tool for the integration of intermittent renewable energy sources (RES) in electrical utility grids. This study evaluates two machine learning (ML) algorithms for intraday solar irradiance forecasting: multigene genetic programming (MGGP) and the multilayer perceptron (MLP) artificial neural network (ANN). MGGP is an evolutionary algorithm white-box method and is a novel approach in the field. Persistence, MGGP and MLP were compared to forecast irradiance at six locations, within horizons from 15 to 120 min, in order to compare these methods based on a wide range of reliable results. The assessment of exogenous inputs indicates that the use of additional weather variables improves irradiance forecastability, resulting in improvements of 5.68% for mean absolute error (MAE) and 3.41% for root mean square error (RMSE). It was also verified that iterative predictions improve MGGP accuracy. The obtained results show that location, forecast horizon and error metric definition affect model accuracy dominance. Both Haurwitz and Ineichen clear sky models have been implemented, and the results denoted a low influence of these models in the prediction accuracy of multivariate ML forecasting. In a broad perspective, MGGP presented more accurate and robust results in single prediction cases, providing faster solutions, while ANN presented more accurate results for ensemble forecasting, although it presented higher complexity and requires additional computational effort.
The Application of the Bispectrum Analysis to Detect the Rotor Unbalance of the Induction Motor Supplied by the Mains and Frequency Converter
Authors: Ewert Pawel
Published: June 2020

This article presents the effectiveness of bispectrum analysis for the detection of the rotor unbalance of an induction motor supplied by the mains and a frequency converter. Two diagnostic signals were analyzed, as well as the stator current and mechanical vibrations of the tested motors. The experimental tests were realized for two low-power induction motors, with one and two pole pairs, respectively. The unbalance was modeled using a test mass mounted on a specially prepared disc and directly on the rotor and the influence of this unbalance location was tested and discussed. The results of the bispectrum analysis are compared with results of Fourier transform and the effectiveness of unbalance detection are discussed and compared. The influence of the registration time of the analyzed signal on the quality of fault symptom analyses using both transforms was also tested. It is shown that the bispectrum analysis provides an increased number of fault symptoms in comparison with the classical spectral analysis as well as it is not sensitive to a shorter registration time of the diagnostic signals.
A Novel Voltage Injection Based Offline Parameters Identification for Current Controller Auto Tuning in SPMSM Drives
Authors: Long Jiang , Yang Ming , Chen Yangyang , Xu Dianguo , Blaabjerg Frede
Published: June 2020

This paper presents a comprehensive study on a novel voltage injection based offline parameter identification method for surface mounted permanent magnet synchronous motors (SPMSMs). It gives solutions to obtain stator resistance, d- and q-axes inductances, and permanent magnet (PM) flux linkage that are totally independent of current and speed controllers, and it is able to track variations in q-axis inductance caused by magnetic saturation. With the proposed voltage amplitude selection strategies, a closed-loop-like current and speed control is achieved throughout the identification process. It provides a marked difference compared with the existing methods that are based on open-loop voltage injection and renders a more simplified and industry-friendly solution compared with methods that rely on controllers. Inverter nonlinearity effect compensation is not required because its voltage error is removed by enabling the motor to function at a designed routine. The proposed method is validated through two SPMSMs with different power rates. It shows that the required parameters can be accurately identified and the proportional-integral current controller auto-tuning is achieved only with very limited motor data such as rated current and number of pole pairs.
Optimal Sizing of a Hybrid Wind-Photovoltaic-Battery Plant to Mitigate Output Fluctuations in a Grid-Connected System
Authors: Al Shereiqi Abdullah , Al-Hinai Amer , Albadi Mohammed , Al-Abri Rashid
Published: June 2020

A novel optimization strategy is proposed to achieve a reliable hybrid plant of wind, solar, and battery (HWSPS). This strategy’s purpose is to reduce the power losses in a wind farm and at the same time reduce the fluctuations in the output of HWSPS generation. In addition, the proposed strategy is different from previous studies in that it does not involve a load demand profile. The process of defining the HWSPS capacity is carried out in two main stages. In the first stage, an optimal wind farm is determined using the genetic algorithm subject to site dimensions and spacing between the turbines, taking Jensen’s wake effect model into consideration to eliminate the power losses due to the wind turbines’ layout. In the second stage, a numerical iterative algorithm is deployed to get the optimal combination of photovoltaic and energy storage system sizes in the search space based on the wind reference power generated by the moving average. The reliability indices and cost are the basis for obtaining the optimal combination of photovoltaic and energy storage system according to a contribution factor with 100 different configurations. A case study in Thumrait in the Sultanate of Oman is used to verify the usefulness of the proposed optimal sizing approach.
Energy Savings in an Office Building with High WWR Using Glazing Systems Combining Thermochromic and Electrochromic Layers
Authors: Detsi Michaela , Manolitsis Aris , Atsonios Ioannis , Mandilaras Ioannis , Founti Maria
Published: June 2020

This paper assesses energy savings in terms of heating, cooling, and artificial lighting achieved in an office building with a high Window to Wall Ratio (WWR), located in Athens and Stockholm. Six different configurations of triple pane windows combining thermochromic, electrochromic, and low-e coatings in Insulated Glass Units (IGUs) are examined to quantify the potential of increasing energy savings in office buildings. The combination of electrochromic and thermochromic layers on the outer pane of the triple IGU, achieved an 18.5% and 8.1% reduction in annual primary energy use for Athens and Stockholm, respectively. The used switching strategy ensured the visual comfort of the employees and provided adequate daylight in both cases. It was found that in Stockholm the cooling system can be downsized considerably, achieving important cost reduction in the HVAC system. The analysis also takes into account the reduction of thermal storage in the building envelope due to the switchable windows. This reduction is beneficial in the case of Athens, but it can reduce energy savings in Stockholm. Therefore, for colder climates, it is important to increase window heat gains through the development of layers with higher g-value in the clear state and through the application of appropriate switching strategies.
Ion Flow Field Calculation Considering the Influence of Water Drops and Wind Flow
Authors: Li Zhenyu , Zhao Xuezeng
Published: June 2020

In this work, an effective calculation method of the ion flow field that considers the impact of wind flow and water drops is presented. To be explicit, the nominal electric field is solved by the charge simulation method (CSM) whilst the space charge density is calculated adopting a second order upwind finite volume method. In addition, a method that determines the roughness factor of a conductor surface is used to enhance calculation accuracy. The influence of various properties of the water drops exerting on an ion flow field is analyzed. Eventually, a practical experiment is conducted to verify the calculated result, and the effectiveness and reliability of this method are then proved via comparing calculated and measured results.
Performance and Sustainability Analysis of an Organic Rankine Cycle System in Subcritical and Supercritical Conditions for Waste Heat Recovery
Authors: Saadon Syamimi , Mohd Nasir Nur Athirah
Published: June 2020

This study addresses the performance analysis of a subcritical and supercritical Organic Rankine Cycle (ORC) with the addition of a preheater or superheater integrated with a turbofan engine. This analysis will try to explore the heat transfer throughout the evaporator for the purpose of determining the ORC output power and thermal efficiency. A simplified numerical model of the ORC for waste heat recovery is presented. The model depicts the evaporator by using a distributed model, and includes parameters such as the effectiveness, heat capacity and inlet temperature of the waste heat and the organic fluid. For a given set of initial parameter values, the output power and thermal efficiency, as well as the mass flow rate of the working fluid are acquired by solving the system’s thermodynamic cycle with the aid of MATLAB software. The model is then verified by using data from an industrial waste heat recovery system. The connection between the turbofan engine and the ORC system was established and evaluated by means of Thrust-Specific Fuel Consumption (TSFC) as well as fuel burn. It was found that the supercritical ORC with a preheater and superheater exhibits lower TSFC than the subcritical ORC, whereas the impact of the ORC in terms of waste heat recovery in relation to the environment and sustainability indices is quite small, but still considerable depending on the engine’s weight.
Standard, Point of Use, and Extended Energy Return on Energy Invested (EROI) from Comprehensive Material Requirements of Present Global Wind, Solar, and Hydro Power Technologies
Authors: de Castro Carlos , Capellán-Pérez Iñigo
Published: June 2020

Whether renewable energy sources (RES) will provide sufficient energy surplus to entirely power complex modern societies is under discussion. We contribute to this debate by estimating the current global average energy return on energy invested (EROI) for the five RES technologies with the highest potential of electricity generation from the comprehensive and internally consistent estimations of their material requirements at three distinct energy system boundaries: standard farm-gate (EROIst), final at consumer point-of-use (EROIfinal), and extended (including indirect investments, EROIext). EROIst levels found fall within the respective literature ranges. Expanding the boundaries closer to the system level, we find that only large hydroelectricity would currently have a high EROIext ~ 6.5:1, while the rest of variable RES would be below 3:1: onshore wind (2.9:1), offshore wind (2.3:1), solar Photovoltaic (PV) (1.8:1), and solar Concentrated Solar Power (CSP) (<1:1). These results indicate that, very likely, the global average EROIext levels of variable RES are currently below those of fossil fuel-fired electricity. It remains unknown if technological improvements will be able to compensate for factors, which will become increasingly important as the variable RES scale-up. Hence, without dynamically accounting for the evolution of the EROI of the system, the viability of sustainable energy systems cannot be ensured, especially for modern societies pursuing continuous economic growth.
Understanding Sub and Supercritical Cryogenic Fluid Dynamics in Conditions Relevant to Novel Ultra Low Emission Engines
Authors: Gopal Jaya Madana , Tretola Giovanni , Morgan Robert , de Sercey Guillaume , Atkins Andrew , Vogiatzaki Konstantina
Published: June 2020

In this paper we provide insight into the thermophysical properties and the dynamics of cryogenic jets. The motivation of the work is to optimise the use of cryogenic fluids in novel ultra low emission engines. For demonstration, we use conditions relevant to an internal combustion engine currently being developed by Dolphin N2 and the University of Brighton, the CryoPower recuperated split cycle engine (RSCE). The principle of this engine is a split-cycle combustion concept which can use cryogenic injection in the compression cylinder to achieve isothermal compression and thus help maximise the efficiency of the engine. Combined experimental and numerical findings are presented and the effects of atomisation dynamics of the LN 2 are explored at both sub- and supercritical conditions in order to cover different pressure and temperature conditions representative of the engine compression cycle. For subcritical regimes, we observe that the appearance of the jet coincides with the predicted atomisation regimes based on the Weber, Ohnesorge and Reynolds numbers for other common fluids. For the modelling of supercritical jets, a new methodology within OpenFoam which accounts for Real Fluid Thermodynamics has been developed and the jet behaviour under various pressure and temperature conditions has been investigated. To our knowledge this is the first study where a cryogenic spray process evolution is examined for conditions relevant to the ones prevailing in a compression chamber accounting for both sub and supercritical conditions.
A Study on Fundamental Waveform Shapes in Microscopic Electrical Load Signatures
Authors: Younis Raneen , Reinhardt Andreas
Published: June 2020

The number of globally deployed smart meters is rising, and so are the sampling rates at which they can meter electrical consumption data. As a consequence thereof, the technological foundation is established to track the power intake of buildings at sampling rates up to several k Hz . Processing raw signal waveforms at such rates, however, imposes a high resource demand on the metering devices and data processing algorithms alike. In fact, the ensuing resource demand often exceeds the capabilities of the embedded systems present in current-generation smart meters. Consequently, the majority of today’s energy data processing algorithms are confined to the use of RMS values of the data instead, reported once per second or even less frequently. This entirely eliminates the spectral characteristics of the signal waveform (i.e., waveform trajectories of electrical voltage, current, or power) from the data, despite the wealth of information they have been shown to contain about the operational states of the operative appliances. In order to overcome this limitation, we pursue a novel approach to handle the ensuing volume of load signature data and simultaneously facilitate their analysis. Our proposed method is based on approximating the current intake of electrical appliances by means of parametric models, the determination of whose parameters only requires little computational power. Through the identification of model parameters from raw measurements, smart meters not only need to transmit less data, but the identification of individual loads in aggregate load signature data is facilitated at the same time. We conduct an analysis of the fundamental waveform shapes prevalent in the electrical power consumption data of more than 50 electrical appliances, and assess the induced approximation errors when replacing raw current consumption data by parametric models. Our results show that the current consumption of many household appliances can be accurately modeled by a small number of parameterizable waveforms.
Dominant Wave Energy Systems and Conditional Wave Resource Characterization for Coastal Waters of the United States
Authors: Ahn Seongho , Haas Kevin , Neary Vincent
Published: June 2020

Opportunities and constraints for wave energy conversion technologies and projects are evaluated by identifying and characterizing the dominant wave energy systems for United States (US) coastal waters using marginal and joint distributions of the wave energy in terms of the peak period, wave direction, and month. These distributions are computed using partitioned wave parameters generated from a 30 year WaveWatch III model hindcast, and regionally averaged to identify the dominant wave systems contributing to the total annual available energy ( A A E ) for eleven distinct US wave energy climate regions. These dominant wave systems are linked to the wind systems driving their generation and propagation. In addition, conditional resource parameters characterizing peak period spread, directional spread, and seasonal variability, which consider dependencies of the peak period, direction, and month, are introduced to augment characterization methods recommended by international standards. These conditional resource parameters reveal information that supports project planning, conceptual design, and operation and maintenance. The present study shows that wave energy resources for the United States are dominated by long-period North Pacific swells (Alaska, West Coast, Hawaii), short-period trade winds and nor’easter swells (East Coast, Puerto Rico), and wind seas (Gulf of Mexico). Seasonality, peak period spread, and directional spread of these dominant wave systems are characterized to assess regional opportunities and constraints for wave energy conversion technologies targeting the dominant wave systems.
Modeling the Supply of Renewable Electricity to Metropolitan Regions in China
Authors: Xiao Mengzhu , Wetzel Manuel , Pregger Thomas , Simon Sonja , Scholz Yvonne
Published: June 2020

The accelerated urbanization and industrialization in China is leading to major challenges due to rising energy demand and emissions. Cities in particular play an important role in the decision-making and implementation processes for the energy transition. However, they often have only limited local energy potential and are heavily dependent on supply regions. We therefore assess how a predominantly renewable power supply can be implemented based on the availability of local or imported renewable resources. We present a case study in which an advanced energy system model is parametrized and applied to address questions which are relevant to the transformation of the energy system in China. The model is capable of simultaneously optimizing investment decisions and hourly power balances of a scenario year, taking into account different storage technologies, regional power exchange and policy constraints such as carbon cap, carbon price and renewable portfolio standards. The study takes the Beijing-Tianjin-Hebei metropolitan region with Inner Mongolia as a supply region—considered as exemplary regions characterized by heterogeneous infrastructures, resources and consumption—as its model. Starting from a context-related normative energy scenario, we analyze a possible future electricity system under various assumptions using the Renewable Energy Mix (REMix) energy system model developed at the DLR (German Aerospace Center). Depending on the estimated potentials of renewable energies, technology costs and the projected electricity demand, the metropolitan region is mainly supplied with imported wind and solar power. A sensitivity analysis considers installed capacities, annual generation, CO2 emissions and costs. The results indicate that the assumption of storage costs is of great importance for the future total costs of an electricity system. Variations in other parameters led to different generation portfolios with similar system costs. Our results provide insights into future regional infrastructure needs, and underline the importance of regional coordination and governance for the energy transition in China.
Management and Performance Control Analysis of Hybrid Photovoltaic Energy Storage System under Variable Solar Irradiation
Authors: Louzazni Mohamed , Cotfas Daniel Tudor , Cotfas Petru Adrian
Published: June 2020

This paper introduces the management control of a microgrid comprising of photovoltaic panels, battery, supercapacitor, and DC load under variable solar irradiation. The battery is used to store the energy from the photovoltaic panels or to supply the load. The supercapacitor is used to reduce stress on batteries, improve their life cycle, and absorb the fluctuations in the energy produced. The generated photovoltaic power is optimized using Perturb and Observe and Incremental Conductance algorithms to extract the maximum power point tracking. The two algorithms are modified by adding an instantaneous step size to change the direction of the power, so as to reach the maximum power point tracking. The currents of the battery and supercapacitor are managed and controlled using the multi-loop proportional integral controllers. The obtained results show that the multi-loop proportionally integral controllers Perturb and Observe are better than the multi-loop proportional integral controllers Incremental Conductance in terms of stability of injected power. The storage system works perfectly for energy supply, system protection, and fluctuation absorption during the transitions in the solar irradiation. The proposed hybrid storage system can be installed in rural areas as an off-grid system for several uses.
On the Potential of Silicon Intermediate Band Solar Cells
Authors: López Esther , Martí Antonio , Antolín Elisa , Luque Antonio
Published: June 2020

Intermediate band solar cells (IBSCs) have an efficiency limit of 63.2%, which is significantly higher than the 40.7% limit for conventional single gap solar cells. In order to achieve the maximum efficiency, the total bandgap of the cell should be in the range of ~2 eV. However, that fact does not prevent other cells based on different semiconductor bandgaps from benefiting from the presence of an intermediate band (IB) within their bandgap. Since silicon (1.12 eV bandgap) is the dominant material in solar cell technology, it is of interest to determine the limit efficiency of a silicon IBSC, because even a modest gain in efficiency could trigger a large commercial interest if the IB is implemented at low cost. In this work we study the limit efficiency of silicon-based IBSCs considering operating conditions that include the use of non-ideal photon casting between the optical transitions, different light intensities and Auger recombination. The results lead to the conclusion that a silicon IBSC, operating under the conventional model in which the sub-bandgaps add to the total silicon gap, provides an efficiency gain if operated in the medium-high concentration range. The performance of these devices is affected by Auger recombination only under extremely high concentrations.
Unlocking the Effects of Fluid Optimization on Remaining Oil Saturation for the Combined Sulfate-Modified Water and Polymer Flooding
Authors: Tahir Muhammad , Hincapie Rafael E. , Ganzer Leonhard
Published: June 2020

Interfacial interactions and wettability alteration remain as the main recovery mechanism when modified water is applied seeking to obtain higher oil recoveries. Fluid-fluid interaction could lead to the development of the called viscoelastic layer at the interface in oil-brine systems. This interfacial layer stabilizes thanks to the slow chemical interaction between oil polar compounds and salts in the brine. This study investigates the role of sulfate presence in injection brine that could possible lead to develop the interfacial viscoelastic layer and hence to contribute to the higher oil recovery. Furthermore, polymer flooding is performed in tertiary mode after brine flood to investigate/unlock the synergies and potential benefits of the hybrid enhanced oil recovery. Brine optimization is performed using the composition of two formation brines and four injection brines. Moreover, interfacial tension measurements and oil drop snap-off volume measurements are performed in parallel with the core flooding experiments to define the role of interfacial viscoelasticity as the recovery mechanism other than wettability alteration. Synthetic seawater spiked with double amount of sulfate depicted potential results of interfacial viscoelastic layer development and hence to contribute the higher oil recovery. Total oil recovery after secondary-mode using sulfate-modified water and tertiary-mode polymer flood was higher than the combination of seawater brine in secondary-mode and polymer flood in tertiary-mode. Nevertheless, experiments helped us concluding that the amount of sulfate added is a critical factor to obtain maximum oil recovery and to avoid pore-plugging problems. We, therefore, demonstrate that executing a detailed fluid optimization leads to promising laboratory results, potentially linked with an improvement in the economics of the field applications.
Detailed Office Building Energy Information Based on In Situ Measurements
Authors: Song Seung-Yeong , Jin Hye-Sun , Ha Soo-Yeon , Kim Sung-Im , Kim You-Jeong , Lee Soo-Jin , Suh In-Ae
Published: June 2020

Energy consumption in the building sector has been continuously increasing, and energy conservation in this sector has become critical for achieving the national goal of reducing greenhouse gas emissions. In South Korea, information on energy sources (electricity, gas, district heating, etc.) is provided, but detailed energy use information, such as space heating, space cooling, domestic hot water (DHW) and lighting, is insufficient to establish a specific action plan for energy savings. Energy use information by end-use can be acquired through actual measurements in close proximity to actual energy use. This information reflects the effects of complex elements such as building operations and residential characteristics, but it is also insufficient. This study presents statistical data on energy use intensities (EUIs) and greenhouse-gas-emission intensities by end-use, derived by measured data collected from 48 sample office buildings in representative city from May 2017 to April 2018, and compares those with the U.S. commercial building energy consumption survey (CBECS) 2012 report. The average site EUIs by end-use were in the following order: space heating > electric appliances (typical floors) > space cooling > lighting > air movement > DHW > vertical transportation > city water supply. With regard to the average primary EUIs by end-use, the magnitude relationship between electric appliances (typical floors) and space heating was opposite that of the average site EUIs. Vertical transportation and DHW exhibited almost the same average greenhouse-gas-emission intensities as those of the average annual primary EUIs. The average site EUIs in the CBECS 2012 data were slightly different from those in this study: electric appliances, etc. > space heating > air movement > lighting > space cooling > DHW. The number of office buildings monitored in this study increased until 2019 (the number of total samples: 85), and the intensity data by end-use will be brought up to date through continuous measurement.