Energies, Volume 14, Issue 5 (March-1 2021) – 300 articles

The metal fueled steam Rankine cycle has been successfully applied to Unmanned Underwater Vehicles. However, the suitable turbine configuration is yet to be determined for this particular application. In this paper, the mean-line design approach based on the existing empirical correlations is first described. The corresponding partial admission axial and radial inflow turbines are then preliminarily designed. To assess the performance of designed turbines, the three-dimensional Computational Fluid Dynamics (CFD) simulations and steady-state structural analysis are performed. The results show that axial turbines are more compact than radial inflow turbines at the same output power. In addition, since radial inflow turbines can reduce the exit energy loss, this benefit substantially offsets the increment of the rotor losses created by the low speed ratios and supersonic rotor inlet velocity. On the contrary, due to the large volume of dead gas and strong transient effects caused by the high rotor blade length of radial inflow turbines, the overall performance between axial and radial inflow turbines is comparable (within 4%). However, the strength of radial inflow turbines is slightly superior because of lower blade inlet height and outlet hub radius. This paper confirms that the axial turbine is the optimal configuration for underwater vehicles in terms of size, aerodynamics and structural performance. Full article

Seismic data and nuclear magnetic resonance (NMR) data are two of the highly trustable kinds of information in hydrocarbon reservoir engineering. Reservoir fluids influence the elastic wave velocity and also determine the NMR response of the reservoir. The current study investigates different pore types, i.e., micro, meso, and macropores’ contribution to the elastic wave velocity using the laboratory NMR and elastic experiments on coal core samples under different fluid saturations. Once a meaningful relationship was observed in the lab, the idea was applied in the field scale and the NMR transverse relaxation time (T₂) curves were synthesized artificially. This task was done by dividing the area under the T₂ curve into eight porosity bins and estimating each bin’s value from the seismic attributes using neural networks (NN). Moreover, the functionality of two statistical ensembles, i.e., Bag and LSBoost, was investigated as an alternative tool to conventional estimation techniques of the petrophysical characteristics; and the results were compared with those from a deep learning network. Herein, NMR permeability was used as the estimation target and porosity was used as a benchmark to assess the reliability of the models. The final results indicated that by using the incremental porosity under the T₂ curve, this curve could be synthesized using the seismic attributes. The results also proved the functionality of the selected statistical ensembles as reliable tools in the petrophysical characterization of the hydrocarbon reservoirs. Full article

Belt conveyors are used for the transportation of bulk materials in a number of different branches of industry, especially in mining and power industries or in shipping ports. The main component of a belt conveyor is its belt, which serves both as a support for the transported material along the conveyor route and as an element in the drive transmission system. Being crucial to the effective and reliable operation of the conveyor, the belt is also its most expensive and the least durable element. A conveyor belt comprises a core, covers and edges. A multiply textile belt, in which the core is constructed of synthetic fibers such as polyamide, polyester or aramid, is the oldest and still the most commonly used conveyor belt type. The plies are joined with a thin layer of rubber or another material (usually the material is the same as the material used in the covers), which provides the required delamination strength to the belt and allows the plies to move relative to each other as the belt is bent. Belts are installed on the conveyors in a closed loop in order to join belt sections, whose number and length depend on the length and type of the belt conveyor. Belts are joined with each other in a splicing procedure. The cutting of the belt core causes belt splices to be prone to concentrated stresses. The discontinued core also causes the belt to be the weakest element in a conveyor belt loop. The article presents the results of strength parameter tests that were performed on laboratory and industrial splices and indicated the reasons for the reduced strength of conveyor belt splices. Splice strength is reduced mainly due to incorrect preparation of the spliced surfaces and to different mechanical parameters of the spliced belts. Full article

The control system for a Doubly Fed Induction Generator (DFIG) supplied by a grid-connected Current Source Converter (CSC) is presented in this paper. Nonlinear transformation of DFIG model to the multi-scalar form is proposed. The nonlinear control strategy of active and reactive power of DFIG is realized by feedback linearization. In the proposed control scheme, the DFIG model and CSI parameters are included. Two Proportional-Integral (PI) controllers are dedicated for the control of the respective active and reactive powers. The control variables are the dc-link input voltage vector and the angular speed of the inverter output current. The proposed control approach is characterized by satisfactional dynamics and provides enhanced quality of the power transferred to the grid. In the simulation, evaluation of the characteristic operating states of the generator system, correctness of the feedback linearization and the dynamics of active and reactive power control loops are studied. Simulation results are adequately provided. Full article

Increasing usage of petroleum-based insulating oils in electrical apparatus has led to increase in pollution and, at the same time, the oils adversely affect the life of electrical apparatus. This increases the demand of Mineral Oil (MO), which is on the verge of extinction and leads to conducting tests on natural esters. This work discusses dielectric endurance of Marula Oil (MRO), a natural ester modified using Conductive Nano Particle (CNP) to replace petroleum-based dielectric oils for power transformer applications. The Al₂O₃ is a CNP that has a melting point of 2072 °C and a low charge relaxation time that allows time to quench free electrons during electrical discharge. Al₂O₃ is blended with the MRO and Mineral Oil (MO) in different concentrations. The measured dielectric properties are transformed into mathematical equations using the Lagrange interpolation polynomial functions and compared with the predicted values either using Gaussian or Fourier distribution functions. Addition of Al₂O₃ indicates that 0.75 g/L in MRO has an 80% survival rate and 20% hazard rate compared to MO which has 50% survival rate and 50% hazard rate. Considering the measured or interpolated values and the predicted values, they are used to identify the MRO and MO’s optimum concentration produces better results. The test result confirms the enhancement of the breakdown voltage up to 64%, kinematic viscosity is lowered by up to 40% at 110 °C, and flash/fire points of MRO after Al₂O₃ treatment enhanced to 14% and 23%. Hence the endurance of Al₂O₃ in MRO proves to be effective against electrical, physical and thermal stress. Full article

The process of reaching carbon neutrality by 2050 and cutting CO₂ emissions by 2030 by 55% compared to 1990 as per the EU Green Deal is highly complex. The energy mix must be changed to ensure long-term environmental sustainability, mainly by closing down coal sites, while preserving the energy-intensive short-term economic growth, ensuring social equity, and opening opportunities for regions diminishing in population and potential. Romania is currently in the position of deciding the optimal way forward in this challenging societal shift while morphing to evidence-based policy-making and anticipatory governance, mainly in its two coal-mining regions. This article provides possible future scenarios for tackling this complex issue in Romania through a three-pronged, staggered, methodology: (1) clustering Romania with other similar countries from the point of view of the Just Transition efforts (i.e., the energy mix and the socio-economic parameters), (2) analyzing Romania’s potential evolution of the energy mix from the point of the thermal efficiency of two major power plants (CEH and CEO) and the systemic energy losses, and (3) providing insights on the socio-economic context (economic development and labor market transformations, including the component on the effects on vulnerable consumers) of the central coal regions in Romania. Full article

The melting flow and heat transfer of copper-oxide coconut oil in thermal energy storage filled with a nonlinear copper metal foam are addressed. The porosity of the copper foam changes linearly from bottom to top. The phase change material (PCM) is filled into the metal foam pores, which form a composite PCM. The natural convection effect is also taken into account. The effect of average porosity; porosity distribution; pore size density; the inclination angle of enclosure; and nanoparticles’ concentration on the isotherms, melting maps, and the melting rate are investigated. The results show that the average porosity is the most important parameter on the melting behavior. The variation in porosity from 0.825 to 0.9 changes the melting time by about 116%. The natural convection flows are weak in the metal foam, and hence, the impact of each of the other parameters on the melting time is insignificant (less than 5%). Full article

Pressure is a physical quantity that is indispensable in the study of transport phenomena. Previous studies put forward a pressure constitutive law and constructed a partial differential equation on pressure to study the convection with or without heat and mass transfer. In this paper, a numerical algorithm was proposed to solve this pressure equation by coupling with the Navier-Stokes equation. To match the pressure equation, a method of dealing with pressure boundary condition was presented by combining the tangential and normal direction pressure relations, which should be updated dynamically in the iteration process. Then, a solution to this pressure equation was obtained to bridge the gap between the mathematical model and a practical numerical algorithm. Through numerical verification in a circular tube, it is found that the proposed boundary conditions are applicable. The results demonstrate that the present pressure equation well describes the transport characteristics of the fluid. Full article

In recent years, two dimensional (2D) hydraulic components have significantly flourished. After a brief development introduction of the 2D pump and 2D flowmeter, it could be concluded that the churning loss, which is caused by the rotational motion of 2D motion-converting mechanisms, has an increasing effect on reducing energy losses. This paper first presents a new 2D motion-converting mechanism and introduces its structure and working principles. To compare it with the former 2D motion-converting mechanism, the same working conditions were applied when designing the new one. Afterward, the generated churning loss by the active parts of the mechanism, such as the new rotor, was well studied by establishing a simplified CFD simulation model and was also verified to have a smaller churning loss than that of the former mechanism. As another key simulation result, the influence of the axial motion of the new rotor was found to be negligible for the churning loss even when the rotational speed was high enough. A test rig was subsequently built up to prove the simulation by monitoring the torque at various rotational speeds. As a result, the churning losses that took place in the new 2D motion-converting mechanism were certainly reduced, and the potential reasons for that were analyzed, as shown in the conclusion section. Full article

The increased use of renewable energy is imperative as a countermeasure to climate change. As with conventional electricity generation technologies, public acceptance of renewables is an important issue, and willingness to pay (WTP) is a widely used indicator to assess such public attitudes. Unfortunately, the literature to date mostly covers developed countries, with few WTP surveys in developing countries. Tackling climate change is an urgent issue for these developing countries; therefore, understanding of public attitudes toward renewables in developing countries is crucial. This study conducted the first survey on WTP for introducing renewable energy in Myanmar. Although Myanmar boasts abundant renewable energy resources, including solar power and biomass in addition to large-scale hydro plants, its resources are not being properly utilized to generate electricity. This study surveyed WTP for power generation by solar photovoltaics, small hydropower, and biomass facilities. The results showed the highest WTP for solar power (USD 1.92) with 10% share in the energy mix, and lower WTP for biomass and small hydropower electricity generations (USD 1.13 and USD 1.17, respectively). Careful public communication is thus crucial for expanding biomass and small-scale hydro power plants. Full article

Concern over the asymmetric phenomena in the core region has increased considering safety issues that are highly possible to reduce the thermal margin significantly in nuclear power plants. Since the seized reactor coolant pump (RCP) accident of an advanced power reactor 1400 (APR1400) can be regarded as a representative core asymmetric event with respect to core inlet flow, the departure from nucleate boiling ratio (DNBR), which is a regulatory acceptance criterion in nuclear safety, should be evaluated with consideration of the uncertainty range of the core inlet flow reflecting the actual geometry. This study investigates the DNBR quantitatively in the entire fuel assemblies in the core using several codes for system behavior, computational flow dynamics, sub-channel analysis, and uncertainty evaluation. Based on the results from a system thermal-hydraulic analysis of a seized RCP accident of APR1400, this study presents the uncertainty range calculated by computational fluid dynamics on the asymmetry of the core inlet flow. Damaged fuel rods are quantitatively identified through a sub-channel analysis, which presents statistic relevance to obtain the DNBR at 95% reliability and 95% accuracy level. Additionally, an optimized evaluation methodology of a non-loss of coolant accident (non-LOCA) is realized by several nuclear codes. Full article

Various equations are being developed and applied to predict photovoltaic (PV) module generation. Currently, quite diverse methods for predicting module generation are available, with most equations showing accuracy with ≤5% error. However, the accuracy can be determined only when the module temperature and the value of irradiation that reaches the module surface are precisely known. The prediction accuracy of outdoor generation is actually extremely low, as the method for predicting outdoor module temperature has extremely low accuracy. The change in module temperature cannot be predicted accurately because of the real-time change of irradiation and air temperature outdoors. Calculations using conventional equations from other studies show a mean error of temperature difference of 4.23 °C. In this study, an equation was developed and verified that can predict the precise module temperature up to 1.64 °C, based on the experimental data obtained after installing an actual outdoor module. Full article

The demand for clean energy is a key global issue requiring global ideas to be implemented through local action. This is particularly important in Poland’s energy transition, since the country produces energy mainly from conventional sources, i.e., coal, gas, and crude oil. Adverse climate change caused by high emissions of the economy based on the combustion of hydrocarbons as well as the growing public awareness have made it necessary to look for new environmentally friendly energy sources. The aim of the paper is to demonstrate that the use of alternative energy sources, biomass in particular, is compatible with sustainable development policy. Eight indicators for the EU-28 and for Poland were analysed in order to verify the progress in modifying the energy mix between 2010 and 2018 in the context of implementing Sustainable Development Goals (SDGs). The analysis showed that both in the EU-28 and in Poland, the aggregated indicator taking into account the positive and negative change in the values of individual indicators improved between 2010 and 2018. In the EU-28, this indicator is higher (180.1) than in Poland (152.3). The lower value for Poland is mainly due to the fact that the main source of energy in Poland remains hard coal and lignite. However, the noticeable increase in recent years in the share of energy from renewable sources, biomass included, allows us to look with hope to a rapidly growing indicator measuring progress towards a sustainable development goal, and to improving environmental standards. Full article

Bamboo-like nitrogen-doped carbon nanotubes (N-CNTs) were used to synthesize supported palladium catalysts (0.2–2 wt.%) for hydrogen production via gas phase formic acid decomposition. The beneficial role of nitrogen centers of N-CNTs in the formation of active isolated palladium ions and dispersed palladium nanoparticles was demonstrated. It was shown that although the surface layers of N-CNTs are enriched with graphitic nitrogen, palladium first interacts with accessible pyridinic centers of N-CNTs to form stable isolated palladium ions. The activity of Pd/N-CNTs catalysts is determined by the ionic capacity of N-CNTs and dispersion of metallic nanoparticles stabilized on the nitrogen centers. The maximum activity was observed for the 0.2% Pd/N-CNTs catalyst consisting of isolated palladium ions. A ten-fold increase in the concentration of supported palladium increased the contribution of metallic nanoparticles with a mean size of 1.3 nm and decreased the reaction rate by only a factor of 1.4. Full article

Modern wide-bandgap (WBG) devices, such as silicon carbide (SiC) or gallium nitride (GaN) based devices, have emerged and been increasingly used in power electronics (PE) applications due to their superior switching feature. The power losses of these devices become the key of system efficiency improvement, especially for high-frequency applications. In this paper, a generalized behavioral model of a switch-diode cell (SDC) is proposed for power loss estimation in the electromagnetic transient simulation. The proposed model is developed based on the circuit level switching process analysis, which considers the effects of parasitics, the operating temperature, and the interaction of diode and switch. In addition, the transient waveforms of the SDC are simulated by the proposed model using dependent voltage and current sources with passive components. Besides, the approaches of obtaining model parameters from the datasheets are given and the modelling method is applicable to various semiconductors such Si insulated-gate bipolar transistor (IGBT), Si/SiC metal–oxide–semiconductor field-effect transistor (MOSFET), and GaN devices. Further, a multi-dimensional power loss table in a wide range of operating conditions can be obtained with fast speed and reasonable accuracy. The proposed approach is implemented in PSCAD/ Electromagnetic Transients including DC, EMTDC, (v4.6, Winnipeg, MB, Canada) and further verified by the hardware setups including different daughter boards for different devices. Full article

It is necessary to monitor, acquire, preprocess, and classify microseismic data to understand active faults or other causes of earthquakes, thereby facilitating the preparation of early-warning earthquake systems. Accordingly, this study proposes the application of machine learning for signal–noise classification of microseismic data from Pohang, South Korea. For the first time, unique microseismic data were obtained from the monitoring system of the borehole station PHBS8 located in Yongcheon-ri, Pohang region, while hydraulic stimulation was being conducted. The collected data were properly preprocessed and utilized as training and test data for supervised and unsupervised learning methods: random forest, convolutional neural network, and K-medoids clustering with fast Fourier transform. The supervised learning methods showed 100% and 97.4% of accuracy for the training and test data, respectively. The unsupervised method showed 97.0% accuracy. Consequently, the results from machine learning validated that automation based on the proposed supervised and unsupervised learning applications can classify the acquired microseismic data in real time. Full article

This paper deals with the problem of the optimal rating of mineral-oil-immersed transformers in large wind farms. The optimal rating is derived based on the probabilistic analyses of wind power generation through the Ornstein–Uhlenbeck stochastic process and on thermal model of the transformer through the integration of stochastic differential equations. These analyses allow the stochastic characterization of lifetime reduction of the transformer and then its optimal rating through a simple closed form. The numerical application highlights the effectiveness and easy applicability of the proposed methodology. The proposed methodology allows deriving the rating of transformers which better fits the specific peculiarities of wind power generation. Compared to the conventional approaches, the proposed method can better adapt the transformer size to the intermittence and variability of the power generated by wind farms, thus overcoming the often-recognized reduced lifetime. Full article

It is important to examine in detail how the distribution of academic research topics related to renewable energy is structured and which topics are likely to receive new attention in the future in order for scientists to contribute to the development of renewable energy. This study uses an advanced probabilistic topic modeling to statistically examine the temporal changes of renewable energy topics by using academic abstracts from 2010–2019 and explores the properties of the topics from the perspective of future signs such as weak signals. As a result, in strong signals, methods for optimally integrating renewable energy into the power grid are paid great attention. In weak signals, interest in large-capacity energy storage systems such as hydrogen, supercapacitors, and compressed air energy storage showed a high rate of increase. In not-strong-but-well-known signals, comprehensive topics have been included, such as renewable energy potential, barriers, and policies. The approach of this study is applicable not only to renewable energy but also to other subjects. Full article

Due to the nonlinear and nonminimum phase characteristics of the buck-boost converter, the design of its controller has always been a challenging problem. In this paper, a multi-index feedback linearization control strategy is proposed to design the controller of the buck-boost converter. Firstly, by constructing an appropriate output function, the original nonlinear system is mapped into a combination of a linear subsystem and a nonlinear subsystem. Then, according to the structural characteristics of these two subsystems, the linear optimal control theory is adopted for the control design of the linear subsystem to make it have a good output performance, while for the nonlinear subsystem, the coefficient of the output function is adjusted to ensure its stability. Finally, based on the Hartman–Grobman theorem, the internal mechanism and coefficient adjustment basis of the proposed method are revealed; that is, by adjusting the coefficient of the output function and the feedback coefficient of the linear control law, the poles of the system are configured to achieve the purpose of adjusting the static and dynamic performance of the system. The simulation results show the feasibility and superiority of using the multi-index feedback linearization control strategy to design the nonlinear control law of the buck-boost converter. Full article

Due to the high switching speed of Gallium Nitride (GaN) transistors, parasitic inductances have significant impacts on power losses and electromagnetic interferences (EMI) in GaN-based power converters. Thus, the proper design of high-frequency converters in a simulation tool requires accurate electromagnetic (EM) modeling of the commutation loops. This work proposes an EM modeling of the parasitic inductance of a GaN-based commutation cell on a printed circuit board (PCB) using Advanced Design System (ADS^®) software. Two different PCB designs of the commutation loop, lateral (single-sided) and vertical (double-sided) are characterized in terms of parasitic inductance contribution. An experimental approach based on S-parameters, the Cold FET technique and a specific calibration procedure is developed to obtain reference values for comparison with the proposed models. First, lateral and vertical PCB loop inductances are extracted. Then, the whole commutation loop inductances including the packaging of the GaN transistors are determined by developing an EM model of the device’s internal parasitic. The switching waveforms of the GaN transistors in a 1 MHz DC/DC converter are given for the different commutation loop designs. Finally, a discussion is proposed on the presented results and the development of advanced tools for high-frequency GaN-based power electronics design. Full article

This paper addresses the solar thermochemical conversion of biomass or waste feedstocks based on pyro-gasification for the clean production of high-value and energy-intensive fuels. The utilization of solar energy for supplying the required process heat is attractive to lower the dependence of gasification processes on conventional energy resources and to reduce emissions of CO₂ and other pollutants for the production of high-value chemical synthetic fuels (syngas). Using concentrated solar energy to drive the endothermal reactions further allows producing more syngas with a higher gas quality, since it has not been contaminated by combustion products, while saving biomass resources. The solar-driven process is thus a sustainable and promising alternative route, enabling syngas yield enhancement and CO₂ mitigation, thereby potentially outperforming the performance of conventional processes for syngas production. This review presents relevant research studies in the field and provides the scientific/technical knowledge and background necessary to address the different aspects of the solar gasification process. An overview of the available solar concentrating technologies and their performance metrics is first introduced. The solar gasifier concepts and designs that were studied from lab to industrial scale are presented, along with their main benefits and limitations. The different management strategies proposed to deal with solar energy variations are also outlined, as well as the major pilot-scale applications and large-scale system level simulations. A specific emphasis is provided on the spouted bed technology that appears promising for the gasification process. Finally, the main modeling approaches of pyro-gasification and kinetics for simulation of gasifiers are described. This study thus provides a detailed overview of the efforts made to enhance the thermochemical performance of solar-assisted biomass gasification for synthetic fuel production. Full article

Accurate electric vehicle (EV) powertrain modeling, simulation and validation is paramount for critical design and control decisions in high performance vehicle designs. Described in this paper is a methodology for the design and development of EV powertrain through modeling, simulation and validation on a real-world vehicle system with detailed analysis of the results. Although simulation of EV powertrains in software simulation environments plays a significant role in the design and development of EVs, validating these models on the real-world vehicle systems plays an equally important role in improving the overall vehicle reliability, safety and performance. This modeling approach leverages the use of MATLAB/Simulink software for the modeling and simulation of an EV powertrain, augmented by simultaneously validating the modeling results on a real-world vehicle which is performance tested on a chassis dynamometer. The combination of these modeling techniques and real-world validation demonstrates a methodology for a cost effective means of rapidly developing and validating high performance EV powertrains, filling the literature gaps in how these modeling methodologies can be carried out in a research framework. Full article

The time of arrival (TOA) trilateration is one of the representative location detection technologies (LDT) that determines the true location of a mobile station (MS) using a unique intersection point of three circles based on three radii corresponding to distances between MS and base stations (BSs) and center coordinates of BSs. Since the distance between MS and BS is estimated by using the number of time delays, three circles based on the estimated radii are generally increased and they may not meet at a single point, resulting in the location estimation error. In order to compensate this estimation error and to improve estimation performance, we present two advanced TOA trilateration localization algorithms with detail mathematical expressions. The considered algorithms are the shortest distance algorithm, which calculates an average of three interior intersection points among an entire six intersection points from three intersecting circles, and the line intersection algorithm, which calculates an intersection point of three lines connecting two intersection points of two circles among the three circles, as the estimated location of the MS. In this paper, we present both algorithms with detailed mathematical expressions. The computer simulation results are provided to compare the location estimation performance of both algorithms. In addition, in this paper, mathematical analysis is provided to indicate the relation between the line intersection algorithm and the shortest distance algorithm. In this analysis, we verify that line equations based on the intersection points obtained from the shortest distance algorithm are identical to those obtained from the line intersection algorithm. Full article

The separation of resistances during their measurement is important because it helps to identify contributors in polymer electrolyte membrane (PEM) fuel cell performance. The major methodologies for separating the resistances are electrochemical impedance spectroscopy (EIS) and polarization curves. In addition, an equivalent circuit was selected for EIS analysis. Although the equivalent circuit of PEM fuel cells has been extensively studied, less attention has been paid to the separation of resistances, including protonic resistance in the cathode catalyst layer (CCL). In this study, polarization curve and EIS analyses were conducted to separate resistances considering the charge transfer resistance, mass transport resistance, high frequency resistance, and protonic resistance in the CCL. A general solution was mathematically derived using the recursion formula. Consequently, resistances were separated and analyzed with respect to variations in relative humidity in the entire current density region. In the case of ohmic resistance, high frequency resistance was almost constant in the main operating load range (0.038–0.050 Ω cm²), while protonic resistance in the CCL exhibited sensitivity (0.025–0.082 Ω cm²) owing to oxygen diffusion and water content. Full article

Under-frequency load shedding (UFLS) is a classic and a commonly accepted measure used to mitigate the frequency disturbances in case of loss-of-generation incidents in AC power grids. Triggering of UFLS is classically done at frequency thresholds when system frequency collapse is already close to happening. The renewed interest for synchronous condensers due to the global trends on massive commissioning of non-synchronous renewable power generation leading to reduction of system inertia gives an opportunity to rethink the approach used to trigger load-shedding activation. This question is especially relevant for the Baltic states facing a desynchronization from Russian power grid and a necessity to operate in an isolated island mode. The main goal of this paper is to introduce a predictive load shedding (LS) method without usage of either frequency or ROCOF measurements based on the monitoring of active power injections of synchronous condensers and to prove the efficiency of the concept through several sets of case study simulations. The paper shows that the proposed approach can provide a greatly improved frequency stability of the power system. The results are analyzed and discussed, the way forward for the practical implementation of the concept is sketched. Full article

The present study examines the effect of silicon dioxide (SiO₂) nano-additives on the performance and emission characteristics of a diesel engine fuelled with soybean biodiesel. Soybean biofuel was prepared using the transesterification process. The morphology of nano-additives was studied using scanning electron microscopy (SEM), X-ray diffraction (XRD) and energy-dispersive X-ray spectroscopy (EDS). The Ultrasonication process was used for the homogeneous blending of nano-additives with biodiesel, while surfactant was used for the stabilisation of nano-additives. The physicochemical properties of pure and blended fuel samples were measured as per ASTM standards. The performance and emissions characteristics of different fuel samples were measured at different loading conditions. It was found that the brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC) increased by 3.48–6.39% and 5.81–9.88%, respectively, with the addition of SiO₂ nano-additives. The carbon monoxide (CO), hydrocarbon (HC) and smoke emissions for nano-additive added blends were decreased by 1.9–17.5%, 20.56–27.5% and 10.16–23.54% compared to SBME25 fuel blends. Full article

In this paper, novel methods for the evaluation of digital-filter stability are investigated. The methods are based on phase analysis of a complex function in the characteristic equation of a digital filter. It allows for evaluating stability when a characteristic equation is not based on a polynomial. The operation of these methods relies on sampling the unit circle on the complex plane and extracting the phase quadrant of a function value for each sample. By calculating function-phase quadrants, regions in the immediate vicinity of unstable roots (i.e., zeros), called candidate regions, are determined. In these regions, both real and imaginary parts of complex-function values change signs. Then, the candidate regions are explored. When the sizes of the candidate regions are reduced below an assumed accuracy, then filter instability is verified with the use of discrete Cauchy’s argument principle. Three different algorithms of the unit-circle sampling are benchmarked, i.e., global complex roots and poles finding (GRPF) algorithm, multimodal genetic algorithm with phase analysis (MGA-WPA), and multimodal particle swarm optimization with phase analysis (MPSO-WPA). The algorithms are compared in four benchmarks for integer- and fractional-order digital filters and systems. Each algorithm demonstrates slightly different properties. GRPF is very fast and efficient; however, it requires an initial number of nodes large enough to detect all the roots. MPSO-WPA prevents missing roots due to the usage of stochastic space exploration by subsequent swarms. MGA-WPA converges very effectively by generating a small number of individuals and by limiting the final population size. The conducted research leads to the conclusion that stochastic methods such as MGA-WPA and MPSO-WPA are more likely to detect system instability, especially when they are run multiple times. If the computing time is not vitally important for a user, MPSO-WPA is the right choice, because it significantly prevents missing roots. Full article

This study compared the methods used to forecast increases in power consumption caused by the rising popularity of electric vehicles (EVs). An excellent model for each region was proposed using multiple scaled geographical datasets over two years. EV charging volumes are influenced by various factors, including the condition of a vehicle, the battery’s state-of-charge (SOC), and the distance to the destination. However, power suppliers cannot easily access this information due to privacy issues. Despite a lack of individual information, this study compared various modeling techniques, including trigonometric exponential smoothing state space (i.e., Trigonometric, Box–Cox, Auto-Regressive-Moving-Average (ARMA), Trend, and Seasonality (TBATS)), autoregressive integrated moving average (ARIMA), artificial neural networks (ANN), and long short-term memory (LSTM) modeling, based on past values and exogenous variables. The effect of exogenous variables was evaluated in macro- and micro-scale geographical areas, and the importance of historic data was verified. The basic statistics regarding the number of charging stations and the volume of charging in each region are expected to aid the formulation of a method that can be used by power suppliers. Full article

The presently observed rapid increase in photovoltaic (PV) micro-installation connections to low-voltage networks, resulting from numerous financial support programmes, European Union (EU) energy policy and growing social awareness of environmental and economic issues, raise the question if PV inverters widely available in EU market fulfil the numerous technical requirements specified in European and Polish regulations. The paper presents the results of an experimental study carried out on three PV Inverters widely available in the EU in accordance with the EU network code NC RfG, standard EN 50549-1:2019 and internal Polish distribution system operators’ (DSOs’) regulations, governing PV inverter cooperation with the low-voltage distribution network. The laboratory test stand scheme and its description are presented. In each test, at least one of the inverters encountered issues, either with the operation in required frequency ranges (one PV inverter), activating reactive power control modes (all three PV inverters), maintaining required power generation gradient after tripping (one PV inverter) or under-voltage ride through immunity (one PV inverter). The obtained results have shown that all tested PV inverters did not meet requirements that are the key to maintaining reliable and safe operation of transmission and distribution electrical networks. Full article

There has been an effort for a few decades to keep energy consumption at a minimum or at least within a low-level range. This effort is more meaningful and complex by including a customer’s satisfaction variable to ensure that customers can achieve the best quality of life that could be derived from how energy is used by different devices. We use the concept of Shapley Value from cooperative game theory to solve the multi-objective optimization problem (MOO) to responsibly fulfill user’s satisfaction by maximizing satisfaction while minimizing the power consumption, with energy constrains since highly limited resources scenarios are studied. The novel method uses the concept of a quantifiable user satisfaction, along the concepts of power satisfaction (PS) and energy satisfaction (ES). The model is being validated by representing a single house (with a small PV system) that is connected to the utility grid. The main objectives are to (i) present the innovative energy satisfaction model based on responsible wellbeing, (ii) demonstrate its implementation using a Shapley-value-based algorithm, and (iii) include the impact of a solar photovoltaic (PV) system in the energy satisfaction model. The proposed technique determines in which hours the energy should be allocated to maximize the ES for each scenario, and then it is compared to cases in which devices are usually operated. Through the proposed technique, the energy consumption was reduced 75% and the ES increased 40% under the energy constraints. Full article