bluuebunny/crossref_metadata_2025 huggingface dataset:
An Efficient Parameter Estimation Algorithm for Proton Exchange Membrane Fuel Cells
Authors: Abdel-Basset Mohamed , Mohamed Reda , Chang Victor
Published: November 2021

The proton exchange membrane fuel cell (PEMFC) is a favorable renewable energy source to overcome environmental pollution and save electricity. However, the mathematical model of the PEMFC contains some unknown parameters which have to be accurately estimated to build an accurate PEMFC model; this problem is known as the parameter estimation of PEMFC and belongs to the optimization problem. Although this problem belongs to the optimization problem, not all optimization algorithms are suitable to solve it because it is a nonlinear and complex problem. Therefore, in this paper, a new optimization algorithm known as the artificial gorilla troops optimizer (GTO), which simulates the collective intelligence of gorilla troops in nature, is adapted for estimating this problem. However, the GTO is suffering from local optima and low convergence speed problems, so a modification based on replacing its exploitation operator with a new one, relating the exploration and exploitation according to the population diversity in the current iteration, has been performed to improve the exploitation operator in addition to the exploration one. This modified variant, named the modified GTO (MGTO), has been applied for estimating the unknown parameters of three PEMFC stacks, 250 W stack, BCS-500W stack, and SR-12 stack, used widely in the literature, based on minimizing the error between the measured and estimated data points as the objective function. The outcomes obtained by applying the GTO and MGTO on those PEMFC stacks have been extensively compared with those of eight well-known optimization algorithms using various performance analyses, best, average, worst, standard deviation (SD), CPU time, mean absolute percentage error (MAPE), and mean absolute error (MAE), in addition to the Wilcoxon rank-sum test, to show which one is the best for solving this problem. The experimental findings show that MGTO is the best for all performance metrics, but CPU time is competitive among all algorithms.
A Surrogate Weather Generator for Estimating Natural Gas Design Day Conditions
Authors: Kaftan David , Corliss George F. , Povinelli Richard J. , Brown Ronald H.
Published: November 2021

Natural gas customers rely upon utilities to provide gas for heating in the coldest parts of winter. Heating capacity is expensive, so utilities and end users (represented by commissions) must agree on the coldest day on which a utility is expected to meet demand. The return period of such a day is long relative to the amount of weather data that are typically available. This paper develops a weather resampling method called the Surrogate Weather Resampler, which creates a large dataset to support analysis of extremely infrequent events. While most current methods for generating weather data are based on simulation, this method resamples the deviations from typical weather. The paper also shows how extreme temperatures are strongly correlated to the demand for natural gas. The Surrogate Weather Resampler was compared in-sample and out-of-sample to the WeaGETS weather generator using both the Kolmogorov–Smirnov test and an exceedance-based test for cold weather generation. A naïve benchmark was also examined. These methods studied weather data from the National Oceanic and Atmospheric Administration and AccuWeather. Weather data were collected for 33 weather stations across North America, with 69 years of data from each weather station. We show that the Surrogate Weather Resampler can reproduce the cold tail of distribution better than the naïve benchmark and WeaGETS.
Benefit Evaluation Model of Prefabricated Buildings in Seasonally Frozen Regions
Authors: Zhao Qianqian , Li Junzhen , Fediuk Roman , Klyuev Sergey , Nemova Darya
Published: November 2021

In order to effectively develop the benefit evaluation model of prefabricated houses in seasonal frozen soil areas, and improve the comprehensive benefits of prefabricated buildings, this paper proposes a life cycle benefit evaluation model for prefabricated buildings in seasonally frozen regions. According to the climatic characteristics of the area, the impact of the seasonally frozen regions is listed as an evaluation index in the construction stage for comprehensive analysis. The 16 indicators that affect the comprehensive benefits of prefabricated buildings are grouped by the nearest neighbor element analysis method. Fuzzy cluster analysis and analytic hierarchy process are used to filter out the most influential index group to calculate the index weight. Then the model proposed in this paper is compared with the existing model to test the validity of the model. The research results show that research and development costs weight is 0.23, design cost weight is 0.10, construction cost weight is 0.22, resource consumption weight is 0.25, building demolition cost weight is 0.04, and seasonal freezing effect weight is 0.16. The calculation result passed the consistency test and the expert scoring result conformed to the normal distribution, which proved the accuracy of the conclusion. It is proposed that the calculation result of the comprehensive benefit score of the model is 1.8% lower than the previous results, which proves the validity of the model. The model can speed up the efficiency of comprehensive benefit evaluation of prefabricated buildings thereby improving the development level of prefabricated buildings.
Ratio Selection between Six Sectors in the Visegrad Group Using Parametric and Nonparametric ANOVA
Authors: Tomczak Sebastian Klaudiusz
Published: November 2021

The changes that have been triggered in market economies by COVID-19 have increased the importance of assessing the financial standing of companies and sectors. It is essential for managers, lenders, and investors to properly evaluate the financial condition of companies. Therefore, it is crucial to select indicators that show the differences in the values of market sectors before, and during, the COVID-19 pandemic (checking the stability of ratios over time). We used parametric and nonparametric analyses of variance (ANOVA) to single out indicators. The sample consists of listed companies in six sectors from the Visegrad group: manufacturing, construction, retail, wholesale trade, transportation and warehousing, and energy. We applied yearly and quarterly analyses in the periods from Q1 2017–Q1 2021. The analyses take into account 82 indicators. The results of the parametric ANOVA indicate that only the ratio of the company size shows the differences between the sectors in most of the periods of quarterly analysis. In comparison, the results of the nonparametric ANOVA demonstrate that five ratios show differences between the sectors in the quarterly analysis, and nine show differences in the yearly analysis. On the basis of the results, the construction and energy sectors are the least effective in managing their assets.
Investigation of AC Electrical Properties of MXene-PCL Nanocomposites for Application in Small and Medium Power Generation
Authors: Kołtunowicz Tomasz N. , Gałaszkiewicz Piotr , Kierczyński Konrad , Rogalski Przemysław , Okal Paweł , Pogrebnjak Alexander D. , Buranich Vladimir , Pogorielov Maksym , Diedkova Kateryna , Zahorodna Veronika , Balitskyi Vitalii , Serhiienko Vladyslav , Baginskyi Ivan , Gogotsi Oleksiy
Published: November 2021

The paper examined Ti3C2Tx MXene (T—OH, Cl or F), which is prepared by etching a layered ternary carbide Ti3AlC2 (312 MAX-phase) precursor and deposited on a polycaprolactone (PCL) electrospun membrane (MXene-PCL nanocomposite). X-ray Diffraction analysis (XRD) and Scanning Electron Microscopy (SEM) indicates that the obtained material is pure Ti3C2 MXene. SEM of the PCL-MXene composite demonstrate random Ti3C2 distribution over the nanoporous membrane. Results of capacitance, inductance, and phase shift angle studies of the MXene-PCL nanocomposite are presented. It was found that the frequency dependence of the capacitance exhibited a clear sharp minima in the frequency range of 50 Hz to over 104 Hz. The frequency dependence of the inductance shows sharp maxima, the position of which exactly coincides with the position of the minima for the capacitance, which indicates the occurrence of parallel resonances. Current conduction occurs by electron tunneling between nanoparticles. In the frequency range from about 104 Hz to about 105 Hz, there is a broad minimum on the inductance relationship. The position of this minimum coincides exactly with the position of the maximum of the phase shift angle—its amplitude is close to 90°. The real value of the inductance of the nanocomposite layer was determined to be about 1 H. It was found that the average value of the distance over which the electron tunnels was determined with some approximation to be about 5.7 nm and the expected value of the relaxation time to be τM ≈ 3 × 10−5 s.
Implementation of ANN-Based Embedded Hybrid Power Filter Using HIL-Topology with Real-Time Data Visualization through Node-RED
Authors: Rizwan Raffay , Arshad Jehangir , Almogren Ahmad , Jaffery Mujtaba Hussain , Yousaf Adnan , Khan Ayesha , Ur Rehman Ateeq , Shafiq Muhammad
Published: November 2021

Electrical power consumption and distribution and ensuring its quality are important for industries as the power sector mandates a clean and green process with the least possible carbon footprint and to avoid damage of expensive electrical components. The harmonics elimination has emerged as a topic of prime importance for researchers and industry to realize the maintenance of power quality in the light of the 7th Sustainable Development Goals (SDGs). This paper implements a Hybrid Shunt Active Harmonic Power Filter (HSAHPF) to reduce harmonic pollution. An ANN-based control algorithm has been used to implement Hardware in the Loop (HIL) configuration, and the network is trained on the model of pq0 theory. The HIL configuration is applied to integrate a physical processor with the designed filter. In this configuration, an external microprocessor (Raspberry PI 3B+) has been employed as a primary data server for the ANN-based algorithm to provide reference current signals for HSAHPF. The ANN model uses backpropagation and gradient descent to predict output based on seven received inputs, i.e., 3-phase source voltages, 3-phase applied load currents, and the compensated voltage across the DC-link capacitors of the designed filter. Moreover, a real-time data visualization has been provided through an Application Programming Interface (API) of a JAVA script called Node-RED. The Node-RED also performs data transmission between SIMULINK and external processors through serial socket TCP/IP data communication for real-time data transceiving. Furthermore, we have demonstrated a real-time Supervisory Control and Data Acquisition (SCADA) system for testing HSAHPF using the topology based on HIL topology that enables the control algorithms to run on an embedded microprocessor for a physical system. The presented results validate the proposed design of the filter and the implementation of real-time system visualization. The statistical values show a significant decrease in Total Harmonic Distortion (THD) from 35.76% to 3.75%. These values perfectly lie within the set range of IEEE standard with improved stability time while bearing the computational overheads of the microprocessor.
Influence of Equivalent Circuit Resistances on Operating Parameters on Three-Phase Induction Motors with Powers up to 50 kW
Authors: Torrent Marcel , Blanqué Balduí
Published: November 2021

This work shows the results obtained from studying the influence of equivalent circuit resistances on three-phase induction motors. The stator resistance, rotor resistance, and iron losses resistance affect the different motor operating variables (output power, current, speed, power factor, starting ratios, and maximum torque). These influences have been quantified, paying particular attention to the losses affected and their impact on efficiency. The study carried out does not apply optimization techniques. It evaluates the different influences of the equivalent circuit’s different resistances on its operation by evaluating applicable constructive modifications concerning available motors. The work has been limited to three-phase induction motors up to 50 kW and low voltage, with the nominal powers of the selected motors being 0.25 kW, 1.5 kW, 7.5 kW, 22 kW, and 45 kW. The tools used to carry out the study are analyzing the equivalent circuit and the simulation of the electromagnetic structure using a finite-element program. The variations proposed in each resistance for all the motors studied is not purely theoretical, as it is based on applying feasible constructive modifications, appropriately analyzed and simulated. These modifications are the variation of the conductor diameter in the stator coils, the change of the section of the rotor cage, and the selection of different ferromagnetic steel types.
Application of Gene Expression Programming (GEP) in Modeling Hydrocarbon Recovery in WAG Injection Process
Authors: Afzali Shokufe , Mohamadi-Baghmolaei Mohamad , Zendehboudi Sohrab
Published: November 2021

Water alternating gas (WAG) injection has been successfully applied as a tertiary recovery technique. Forecasting WAG flooding performance using fast and robust models is of great importance to attain a better understanding of the process, optimize the operational conditions, and avoid high-cost blind tests in laboratory or pilot scales. In this study, we introduce a novel correlation to determine the performance of the near-miscible WAG flooding in strongly water-wet sandstones. We conduct dimensional analysis with Buckingham’s π theorem technique to generate dimensionless numbers using eight key parameters. Seven dimensionless numbers are employed as the input variables of the desired correlation for predicting the recovery factor of a near-miscible WAG injection. A verified mathematical model is used to generate the required training and testing data for the development of the correlation using a gene expression programming (GEP) algorithm. The provided data points are then separated into two subsets: training (67%) to develop the model and testing (33%) to assess the models’ capability. Conducting error analysis, statistical measures and graphical illustrations are provided to assess the effectiveness of the introduced model. The statistical analysis shows that the developed GEP-based correlation can generate target data with high precision such that the training phase leads to R2 = 92.85% and MSE = 1.38 × 10−3 and R2 = 91.93% and MSE = 4.30 × 10−3 are attained for the testing phase. The relative importance of the input dimensionless groups is also determined. According to the sensitivity analysis, decreasing the oil–water capillary number results in a significant reduction in RF in all cycles. Increasing the magnitudes of oil to gas viscosity ratio and oil to water viscosity ratio lowers the RF of each cycle. It is found that oil to gas viscosity ratio has a higher impact on RF value compared to oil to water viscosity ratio due to a higher viscosity gap between the gas and oil phases. It is expected that the GEP, as a fast and reliable tool, will be useful to find vital variables including relative permeability in complex transport phenomena such as three-phase flow in porous media.
Non-Destructive Diagnostic Methods for Fire-Side Corrosion Risk Assessment of Industrial Scale Boilers, Burning Low Quality Solid Biofuels—A Mini Review
Authors: Hardy Tomasz , Arora Amit , Pawlak-Kruczek Halina , Rafajłowicz Wojciech , Wietrzych Jerzy , Niedźwiecki Łukasz , Vishwajeet  , Mościcki Krzysztof
Published: November 2021

The use of low-emission combustion technologies in power boilers has contributed to a significant increase in the rate of high-temperature corrosion in boilers and increased risk of failure. The use of low quality biomass and waste, caused by the current policies pressing on the decarbonization of the energy generation sector, might exacerbate this problem. Additionally, all of the effects of the valorization techniques on the inorganic fraction of the solid fuel have become an additional uncertainty. As a result, fast and reliable corrosion diagnostic techniques are slowly becoming a necessity to maintain the security of the energy supply for the power grid. Non-destructive testing methods (NDT) are helpful in detecting these threats. The most important NDT methods, which can be used to assess the degree of corrosion of boiler tubes, detection of the tubes’ surface roughness and the internal structural defects, have been presented in the paper. The idea of the use of optical techniques in the initial diagnosis of boiler evaporators’ surface conditions has also been presented.
A Blockchain-Supported Framework for Charging Management of Electric Vehicles
Authors: Dorokhova Marina , Vianin Jérémie , Alder Jean-Marie , Ballif Christophe , Wyrsch Nicolas , Wannier David
Published: November 2021

Profound changes driven by decarbonization, decentralization, and digitalization are disrupting the energy industry, bringing new challenges to its key stakeholders. In the attempt to address the climate change issue, increasing penetration of renewables and mobility electrification augment the complexity of the electric grid, thus calling for new management approaches to govern energy exchanges while ensuring reliable and secure operations. The emerging blockchain technology is regarded as one of the most promising solutions to respond to the matter in a decentralized, efficient, fast, and secure way. In this work, we propose an Ethereum-based charging management framework for electric vehicles (EVs), tightly interlinked with physical and software infrastructure and implemented in a real-world demonstration site. With a specifically designed solidity-based smart contract governing the charging process, the proposed framework enables secure and reliable accounting of energy exchanges in a network of trustless peers, thus facilitating the EVs’ deployment and encouraging the adoption of blockchain technology for everyday tasks such as EV charging through private and semi-private charging infrastructure. The results of a multi-actor implementation case study in Switzerland demonstrate the feasibility of the proposed blockchain framework and highlight its potential to reduce costs in a typical EV charging business model. Moreover, the study shows that the suggested framework can speed up the charging and billing processes for EV users, simplify the access to energy markets for charging station owners, and facilitate the interaction between the two through specifically designed mobile and web applications. The implementation presented in this paper can be used as a guideline for future blockchain applications for EV charging and other smart grid projects.
Comprehensive and Comparative Analysis of GAM-Based PV Power Forecasting Models Using Multidimensional Tensor Product Splines against Machine Learning Techniques
Authors: Matsumoto Takuji , Yamada Yuji
Published: November 2021

In recent years, as photovoltaic (PV) power generation has rapidly increased on a global scale, there is a growing need for a highly accurate power generation forecasting model that is easy to implement for a wide range of electric utilities. Against this background, this study proposes a PV power forecasting model based on the generalized additive model (GAM) and compares its forecasting accuracy with four popular machine learning methods: k-nearest neighbor, artificial neural networks, support vector regression, and random forest. The empirical analysis provides an intuitive interpretation of the multidimensional smooth trends estimated by the GAM as tensor product splines and confirms the validity of the proposed modeling structure. The effectiveness of GAM is particularly evident in trend completion for missing data, where it is able to flexibly express the tangled trend structure inherent in time series data, and thus has an advantage not only in interpretability but also in improving forecast accuracy.
Economic Evaluation of the Production of Perennial Crops for Energy Purposes—A Review
Authors: Olba-Zięty Ewelina , Stolarski Mariusz Jerzy , Krzyżaniak Michał
Published: November 2021

Biomass is widely used for the production of renewable energy, which calls for an economic evaluation of its generation. The aim of the present work was to review the literature concerning the economic evaluation of the production of perennial crop biomass for energy use. Statistical analysis of the bibliographic data was carried out, as well as an assessment of methods and values of economic indicators of the production of perennial crops for bioenergy. Most of the papers selected for the review were published in the years 2015–2019, which was probably stimulated by the growing interest in sustainable development, particularly after 2015, when the United Nations declared 17 sustainable development goals. The earliest articles concerned the economic analysis of plantations of short rotation coppice; the subsequent ones included the analysis of feedstock production in terms of the net present value and policy. The latest references also investigated transport and sustainability issues. The crops most commonly selected for production cost analysis were willow, poplar, and Miscanthus. The cost of production of willow and poplar were similar, 503 EUR ha−1 year−1 and 557 EUR ha−1 year−1, respectively, while the cost of Miscanthus production was significantly higher, 909 EUR ha−1 year−1 on average. By analogy, the distribution of revenue was similar for willow and poplar, at 236 EUR ha−1 year−1 and 181 EUR ha−1 year−1; Miscanthus production reached the value of 404 EUR ha−1 year−1. The economic conditions of perennial crop production differed in terms of geography; four areas were identified: Canada, the USA, southern Europe, and central and northern Europe.
Production and Evaluation of Fractionated Tamarind Seed Oil Methyl Esters as a New Source of Biodiesel
Authors: Mushtaq Ayesha , Hanif Muhammad Asif , Zahid Muhammad , Rashid Umer , Mushtaq Zahid , Zubair Muhammad , Moser Bryan R. , Alharthi Fahad A.
Published: November 2021

Biodiesel has attracted considerable interest as an alternative biofuel due to its many advantages over conventional petroleum diesel such as inherent lubricity, low toxicity, renewable raw materials, biodegradability, superior flash point, and low carbon footprint. However, high production costs, poor low temperature operability, variability of fuel quality from different feedstocks, and low storage stability negatively impact more widespread adoption. In order to reduce production costs, inexpensive inedible oilseed alternatives are needed for biodiesel production. This study utilized inedible tamarind (Tamarind indica) seed oil as an alternative biodiesel feedstock, which contained linoleic (31.8%), oleic (17.1%), and lauric (12.0%) acids as the primary fatty acids. A simple and cost-effective high vacuum fractional distillation (HVFD) methodology was used to separate the oil into three fractions (F1, F2, and F3). Subsequent transesterification utilizing basic, acidic, and enzymatic catalysis produced biodiesel of consistent quality and overcame the problem of low temperature biodiesel performance. The most desirable biodiesel with regard to low temperature operability was produced from fractions F2 and F3, which were enriched in unsaturated fatty acids relative to tamarind seed oil. Other properties such as density and cetane number were within the limits specified in the American and European biodiesel standards.
A Novel Air-Cooled Thermal Management Approach towards High-Power Lithium-Ion Capacitor Module for Electric Vehicles
Authors: Karimi Danial , Behi Hamidreza , Akbarzadeh Mohsen , Van Mierlo Joeri , Berecibar Maitane
Published: November 2021

This work presents an active thermal management system (TMS) for building a safer module of lithium-ion capacitor (LiC) technology, in which 10 LiCs are connected in series. The proposed TMS is a forced air-cooled TMS (ACTMS) that uses four axial DC 12 V fans: two fans are responsible for blowing the air from the environment into the container while two other fans suck the air from the container to the environment. An experimental investigation is conducted to study the thermal behavior of the module, and numerical simulations are carried out to be validated against the experiments. The main aim of the model development is the optimization of the proposed design. Therefore, the ACTMS has been optimized by investigating the impact of inlet air velocity, inlet and outlet positions, module rotation by 90° towards the airflow direction, gap spacing between neighboring cells, and uneven gap spacing between neighboring cells. The 3D thermal model is accurate, so the validation error between the simulation and experimental results is less than 1%. It is proven that the ACTMS is an excellent solution to keep the temperature of the LiC module in the desired range by air inlet velocity of 3 m/s when all the fans are blowing the air from both sides, the outlet is designed on top of the module, the module is rotated, and uneven gap space between neighboring cells is set to 2 mm for the first distance between the cells (d1) and 3 mm for the second distance (d2).
Energy Efficiency Indicators for Water Pumping Systems in Multifamily Buildings
Authors: de Souza Danilo Ferreira , da Guarda Emeli Lalesca Aparecida , Sauer Ildo Luis , Tatizawa Hédio
Published: November 2021

With the current concerns about sustainable development and energy consumption in buildings, water pumping systems have become essential for reducing energy consumption. This research aims to develop guidelines for the energy assessment of water pumping systems in multifamily buildings. The methodological procedures are: (i) definition of the efficiencies of electric motors; (ii) definition of pump efficiency levels; (iii) determination of energy consumption; and (iv) construction of the efficiency scale and guidelines for projects and assessments. The results obtained were that centrifugal pumps with 40% efficiency have higher energy consumption, regardless of the efficiency class of the electric motors, showing a 20% increase in electrical energy consumption. Lower efficiencies directly impact the energy efficiency rating of the water pumping system. Thus the 40% efficiency obtained energy efficiency rating “Very Low—VL” for all motor efficiency classes (between IE1 and IE5). At 60% efficiency, the energy efficiency level of the system was “Average—A”, gradually increasing to “Very High—VH”, as the energy consumption in the pumps decreased and the motors’ energy efficiency classes increased. It is concluded that designers and professionals in the area must consider the efficiency of the pumps, as they play a fundamental role in the classification of the system’s energy efficiency. It is also recommended to verify the energy efficiency of the water pumping system and implement design guidelines so that the pumping system achieves lower energy consumption, contributing to the building’s energy efficiency and sustainability.
Modelling Ground Collectors and Determination of the Influence of Technical Parameters, Installation and Geometry on the Soil
Authors: Gabániová Ľubomíra , Kudelas Dušan , Prčík Martin
Published: November 2021

The main objective of this work was to model ground collectors with different parameters and geometries in ANSYS R19.2 and to simulate their operation during the heating season in Slovakia in order to determine their impact on the soil. At the same time, four new geometries in the shape of vertical spirals with diameters of 6, 8 and 10 m were designed and simulated to occupy a smaller area while maintaining performance similar to classical geometries. Due to climate change, heat pumps are becoming an important proxy in the heating of buildings and are an important part of decarbonisation plans; thus, it is essential to adapt them to urban and metropolitan conditions. Ground source heat pumps possess high efficiency but require a lot of space for their collectors. The collector geometries proposed in this work are a combination of horizontal and vertical technologies and are feasible. Only one geometry achieved performance similar to classical geometries: spiral with 10 m diameter. Factors significantly influencing collector operation were confirmed, namely season, soil type, soil water content, geometry and collector placement.
Socioeconomic Factors Influencing the Prosumer’s Investment Decision on Solar Power
Authors: Rausch Patrick , Suchanek Michał
Published: November 2021

This paper identifies socioeconomic factors that are supposed to impact the investment decision of private households in Germany regarding small-scale solar PV (photovoltaic) systems. In 2022, the last nuclear power plant will phase out and the end of coal-fired power plants is fixed for 2038. Thus, the legislator is mandated to foster the addition of renewable energy capacities to close the gap fossil fuels and nuclear power leaves. Some share of the renewable energies could be from private households that mainly invest in small-scale solar PV systems. To stimulate investments, it is necessary to identify factors that are important for the investment decisions of private households. Within this paper, secondary socioeconomic data for the period from 2009–2018 was compiled. In order to identify the latent variables, a factor analysis was conducted. The results state five factors that are supposed to impact the investment decisions of the prosumer in Germany.
Identification of BDS Satellite Clock Periodic Signals Based on Lomb-Scargle Power Spectrum and Continuous Wavelet Transform
Authors: Kudrys Jacek , Prochniewicz Dominik , Zhang Fang , Jakubiak Mateusz , Maciuk Kamil
Published: November 2021

Onboard satellite clocks are the basis of Global Navigation Satellite Systems (GNSS) operation, and their revolution periods are at the level of 2 per day (about 12 h) in the case of the Medium Earth Orbit (MEO) satellites. In this work, the authors analysed the entire BeiDou Navigation Satellite System (BDS) space segment (BDS-2 and BDS-3) in terms of the occurrence of periodic, repetitive signals in the clock products, and checked if they coincide with the orbital periods or their multiples. The Lomb-Scargle (L-S) power spectrum was used as a tool to determine the periods present in the BDS clock products, allowing for analyses based on incomplete input data; in this case, the incomplete data were the phase data with jumps and outliers removed. In addition, continuous wavelet transform (CWT) was used to produce a time−frequency representation showing the more complex behaviour of the satellite clock products. As shown in the case of geostationary and geosynchronous inclined orbit satellites, the main period was 23.935 h, while for the Medium Earth Orbit it was 12.887 h, with the BDS satellite orbital period being 12 h 53 m (12.883 h). Some effects connected with reference clock swapping are also visible in the power spectrum. The conducted analyses showed that the BDS-2 satellite clocks have much higher noise than the BDS-3 satellite clocks, meaning that the number of designated periods is greater, but their reliability is significantly lower. BDS-3 satellites have only been in operation for a very short time, thus this is the first analysis to include this type of data. Moreover, such a wide and complex analysis has not been carried out to date.
Energy and Environmental Performance of Solar Thermal Collectors and PV Panel System in Renovated Historical Building
Authors: Zukowski Miroslaw , Kosior-Kazberuk Marta , Blaszczynski Tomasz
Published: November 2021

The major intent of this article was to determine the amount of energy received by two active systems used to convert solar radiation and to estimate their impact on reducing the emission of pollutants. Thermal solar collectors with an area of 51.36 m2 and photovoltaic panels with an area of 50.4 m2 were subject to comparative analysis. It was assumed that either of the two systems could be installed on the roof of an old tenement house located in Poznan (Poland), which is planned for renovation. Computer simulations made with DesignBuilder software were used as a research tool. Two main conclusions can be drawn from the analysis of the year-long operation of both systems in the conditions of a typical meteorological year. Thermal solar collectors can produce 469 kWh of heat from 1 m2 of the device annually, while PV panels can generate 136 kWh of electricity per year from 1 m2 of active area. However, it turned out that the use of photovoltaic systems can contribute to a higher reduction in pollutants emitted to the atmosphere as a result of the alternative combustion of fossil fuels. Additionally, the optimal angle of inclination of devices for solar radiation conversion located near Poznan was determined.
Low Carbon Scenario Analysis of a Hydrogen-Based Energy Transition for On-Road Transportation in California
Authors: Vijayakumar Vishnu , Jenn Alan , Fulton Lewis
Published: November 2021

Fuel cell electric vehicles (FCEV) are emerging as one of the prominent zero emission vehicle technologies. This study follows a deterministic modeling approach to project two scenarios of FCEV adoption and the resulting hydrogen demand (low and high) up to 2050 in California, using a transportation transition model. The study then estimates the number of hydrogen production and refueling facilities required to meet demand. The impact of system scale-up and learning rates on hydrogen price is evaluated using standalone supply chain models: H2A, HDSAM, HRSAM and HDRSAM. A sensitivity analysis explores key factors that affect hydrogen prices. In the high scenario, light and heavy-duty fuel cell vehicle stocks reach 12.5 million and 1 million by 2050, respectively. The resulting annual hydrogen demand is 3.9 billion kg, making hydrogen the dominant transportation fuel. Satisfying such high future demands will require rapid increases in infrastructure investments starting now, but especially after 2030 when there is an exponential increase in the number of production plants and refueling stations. In the long term, electrolytic hydrogen delivered using dedicated hydrogen pipelines to larger stations offers substantial cost savings. Feedstock prices, size of the hydrogen market and station utilization are the prominent parameters that affect hydrogen price.
Conversion of Post-Socialist Agricultural Premises as a Chance for Renewable Energy Production. Photovoltaics or Biogas Plants?
Authors: Navrátil Josef , Martinát Stanislav , Krejčí Tomáš , Klusáček Petr , Hewitt Richard J.
Published: November 2021

We aim to contribute to in-depth comprehension of the factors and preferences behind the reuses of large-scale underused or abandoned former collective farms from the 1950s–1980s for biogas plants and solar photovoltaic power plants. As a case study, three regions in the southern part of the Czech Republic have been selected. Our findings signal that the residents’ attitudes towards the mentioned energy sources are rather negative. Similarly, farmers’ interest in photovoltaic power plants is low. More interest has been detected in the case of biogas production; this is especially true for large agricultural companies and farmers, who own underused or abandoned premises. Biogas plants are frequently located in agricultural areas with warmer or just slightly colder climates as a consequence of the potential to process locally grown maize. On the other hand, photovoltaic power plants are found on more fertile plains with high levels of insolation, but, surprisingly, also in mountain regions which typically have low emissions. Both renewable energy solutions were found to be problematic as there is strong opposition to both types of installations among local inhabitants. This indicates the need for “soft” forms of planning. Stakeholder engagement and inclusive participation in all phases of the planning process are essential requirements for arriving at the best possible outcomes for the new renewable energy solutions and their acceptance by the public.
State-of-the-Art Measurement Instrumentation and Most Recent Measurement Techniques for Parabolic Trough Collector Fields
Authors: Brenner Alex , Hirsch Tobias , Röger Marc , Pitz-Paal Robert
Published: November 2021

The presented review gives reliable information about the currently used measurement instrumentation in parabolic trough fields and recent monitoring approaches. The usually built-in measurement equipment in the solar field, clamp-on systems for flexible measurements of temperature and flow, solar irradiance measurements, standard meteorological equipment, laboratory devices for heat transfer fluid analyses and instruments related to the tracking of solar collector assemblies are presented in detail. The measurement systems are reported with their measurement uncertainty, approximate costs and usual installation location for the built-in instrumentation. Specific findings related to the installation and operation of the measurement devices are presented. The usually installed instrumentation delivers a lot of measurements all over the field at the expense of measurement accuracy, compared to special test facility equipment. Recently introduced measurement approaches can improve the standard instrumentation in terms of accuracy, frequency, spatial distribution or can even extend the amount of measurands. The information about available measurands is the basis for future operation and maintenance solutions based on data-driven approaches.
Influencing Factors Evaluation of Machine Learning-Based Energy Consumption Prediction
Authors: Khan Prince Waqas , Kim Yongjun , Byun Yung-Cheol , Lee Sang-Joon
Published: November 2021

Modern computing resources, including machine learning-based techniques, are used to maintain stability between the demand and supply of electricity. Machine learning is widely used for the prediction of energy consumption. The researchers present several artificial intelligence and machine learning-based methods to improve the prediction accuracy of energy consumption. However, the discrepancy between actual energy consumption and predicted energy consumption is still challenging. Various factors, including changes in weather, holidays, and weekends, affect prediction accuracy. This article analyses the overall prediction using error curve learning and a hybrid model. Actual energy consumption data of Jeju island, South Korea, has been used for experimental purposes. We have used a hybrid ML model consisting of Catboost, Xgboost, and Multi-layer perceptron for the prediction. Then we analyze the factors that affect the week-ahead (WA) and 48 h prediction results. Mean error on weekdays is recorded as 2.78%, for weekends 2.79%, and for special days it is recorded as 4.28%. We took into consideration significant predicting errors and looked into the reasons behind those errors. Furthermore, we analyzed whether factors, such as a sudden change in temperature and typhoons, had an effect on energy consumption. Finally, the authors have considered the other factors, such as public holidays and weekends, to analyze the significant errors in the prediction. This study can be helpful for policymakers to make policies according to the error-causing factors.
Evaluation of Non-Classical Decision-Making Methods in Self Driving Cars: Pedestrian Detection Testing on Cluster of Images with Different Luminance Conditions
Authors: Junaid Mohammad , Szalay Zsolt , Török Árpád
Published: November 2021

Self-driving cars, i.e., fully automated cars, will spread in the upcoming two decades, according to the representatives of automotive industries; owing to technological breakthroughs in the fourth industrial revolution, as the introduction of deep learning has completely changed the concept of automation. There is considerable research being conducted regarding object detection systems, for instance, lane, pedestrian, or signal detection. This paper specifically focuses on pedestrian detection while the car is moving on the road, where speed and environmental conditions affect visibility. To explore the environmental conditions, a pedestrian custom dataset based on Common Object in Context (COCO) is used. The images are manipulated with the inverse gamma correction method, in which pixel values are changed to make a sequence of bright and dark images. The gamma correction method is directly related to luminance intensity. This paper presents a flexible, simple detection system called Mask R-CNN, which works on top of the Faster R-CNN (Region Based Convolutional Neural Network) model. Mask R-CNN uses one extra feature instance segmentation in addition to two available features in the Faster R-CNN, called object recognition. The performance of the Mask R-CNN models is checked by using different Convolutional Neural Network (CNN) models as a backbone. This approach might help future work, especially when dealing with different lighting conditions.
A Review of Transverse Flux Machines Topologies and Design
Authors: Ballestín-Bernad Víctor , Artal-Sevil Jesús Sergio , Domínguez-Navarro José Antonio
Published: November 2021

High torque and power density are unique merits of transverse flux machines (TFMs). TFMs are particularly suitable for use in direct-drive systems, that is, those power systems with no gearbox between the electric machine and the prime mover or load. Variable speed wind turbines and in-wheel traction seem to be great-potential applications for TFMs. Nevertheless, the cogging torque, efficiency, power factor and manufacturing of TFMs should still be improved. In this paper, a comprehensive review of TFMs topologies and design is made, dealing with TFM applications, topologies, operation, design and modeling.
State-Space Approach for SPMSM Sensorless Passive Algorithm Tuning
Authors: Carbone Lorenzo , Cosso Simone , Marchesoni Mario , Passalacqua Massimiliano , Vaccaro Luis
Published: November 2021

Sensorless algorithms for Permanent Magnet Synchronous Motors (PMSM) have achieved increasing interest in the technical literature over the last few years. They can be divided into active methods and passive methods: the first inject high-frequency signals exploiting rotor anisotropy, whereas the second are based on observers. Recently, a sensorless control based on a rotor flux observer has been presented in the technical literature, which gives very accurate results in terms of rotor position estimation and robustness. In this paper, the aforementioned observer is considered and a procedure for choosing stabilizing gains of the observer is proposed. The contribution of the paper is three-fold: the mathematical modelling of the rotor flux observer, the methodology for the definition of the observer gains, and the presentation of the experimental results.
Impact of a Punching Process on the SyRM Iron Loss: SPICE Model as an Effective Tool for Iron Loss Modeling
Authors: Gmyrek Zbigniew
Published: November 2021

Many technologies for cutting the magnetic laminations, from which electric motors cores are built, change material properties, among which are magnetizability and iron loss, thus affecting the motor parameters such as motor efficiency. This problem is particularly important for low-power motors, in which the dimensions of the magnetic circuit elements are relatively small. The correct estimation of the motor efficiency is important as early as at its design stage. This is possible when the correct material characteristics are used. This knowledge and analytical model enabling fast estimation of material properties (depending on the actual size) are necessary for engineers, who design electrical motors by analyzing many solution variants in a short time. The author proposes an analytical model of changing material properties, implemented in SPICE software. Its effectiveness was compared with measurement results while being a competitive solution in relation to other analytical models. The proposed SPICE model allowed evaluating material properties for lamination of any width. In the end, the knowledge concerning the material properties was used to calculate the iron loss in the stator of the SyRM motor, showing the need to use the material characteristics calculated for the specified width of the core piece.
Effect of HVAC’s Management on Indoor Thermo-Hygrometric Comfort and Energy Balance: In Situ Assessments on a Real nZEB
Authors: De Masi Rosa Francesca , Gigante Antonio , Festa Valentino , Ruggiero Silvia , Vanoli Giuseppe Peter
Published: November 2021

This paper proposes the analysis of real monitored data for evaluating the relationship between occupants’ comfort conditions and the energy balance inside an existing, nearly zero-energy building under different operational strategies for the heating, ventilation, and air-conditioning system. During the wintertime, the adaptive comfort approach is applied for choosing the temperature setpoint when an air-to-air heat pump provides both heating and ventilation. The results indicate that in very insulated buildings with high solar gains, the setpoint should be decided taking into consideration both the solar radiation and the outdoor temperature. Indeed, when the room has large glazed surfaces, the solar radiation can also guarantee acceptable indoor conditions when a low setpoint (e.g., 18.7 °C) is considered. The electricity consumption can be reduced from 17% to 43% compared to a conventional setpoint (e.g., 20 °C). For the summertime, the analysis suggests the adoption of a dynamic approach that should be based on the outdoor conditions and differentiated according to room characteristics. Considering the indoor comfort and the maximization of renewable integration, the direct expansion system has better performance than the heat pump; this last system should be integrated with a pre-handling unit to be energy convenient.
The North-South Gas Corridor in the Context of Poland’s Gas Transmission System—A Perfect Opportunity to Diversify Gas Resources
Authors: Hebda Wiktor
Published: November 2021

The energy sector in Poland is currently calling for dynamic redevelopment and cleaner energy. This country is world famous for its high level of coal production, from which it does not want to retreat in the next two decades. For this reason, it is safer to gradually reduce the use of coal while increasing the consumption of gas and simultaneously developing green energy. However, the Polish gas sector is still dependent on Russian gas supplied through the Yamal gas pipeline. Taking into consideration Polish geopolitics, this state of affairs poses a huge challenge and a threat to Poland’s energy security. That is why the concept of the North-South Gas Corridor was introduced. It is intended to be a network of gas pipelines that connect the countries of Central and South Europe to two gas terminals (in Poland and Croatia), which will supply gas from a chosen source. This article presents the current condition of the gas sector in Poland. It focuses on the North-South Gas Corridor project and its impact on the energy security of Poland. An analysis of documents and field research shows that the North-South Gas Corridor provides Poland with an opportunity to diversify the sources and directions of gas supply over the next few years.