The expansion of Internet of Things (IoT) services and the huge amount of data generated by different sensors signify the importance of cloud computing services such as Storage as a Service more than ever. IoT traffic imposes such extra constraints on the cloud storage service as sensor data preprocessing capability and load-balancing between data centers and servers in each data center. Furthermore, service allocation should be allegiant to the quality of service (QoS). In the current work, an algorithm is proposed that addresses the QoS in storage service allocation. The proposed hybrid multi-objective water cycle and grey wolf optimizer (MWG) considers different QoS objectives (e.g., energy, processing time, transmission time, and load balancing) in both the fog and cloud Layers, which were not addressed altogether. The MATLAB script is used to simulate and implement our algorithms, and services of different servers, e.g., Amazon, Dropbox, Google Drive, etc., are considered. The MWG... [more]

Global economic growth, demographic explosion, digitization, increased mobility, and greater demand for heating and cooling due to climate change in different world areas are the main drivers for the surge in energy demand. The increase in energy demand is the basis of economic challenges for power companies alongside several socio-economic problems in communities, such as energy poverty, defined as the insufficient coverage of energy needs, especially in the residential sector. Two main strategies are considered to meet this increased demand. The first strategy focuses on new sustainable and eco-friendly modes of power generation, such as renewable energy resources and distributed energy resources. The second strategy is demand-side oriented rather than the supply side. Demand-side management, demand response (DR), and energy efficiency (EE) programs fall under this category. On the other hand, the decentralization and digitization of the energy sector convoyed by the emersion of new... [more]

This paper presents the method for evaluation of the turns ratio correction of the inductive current transformer using the magnetization curves determined at the non-load state and in the load conditions. The presented method may be applied to determine even a fractional winding correction factor. The standard IEC 61869-2 provides the method to determine the turns ratio correction of the tested CT from the measured rms values of voltages on its primary and secondary winding in the non-load state. However, this approach is limited in determining the significant changes in the number of turns of the secondary winding. Moreover, the paper presents the influence of the applied turns ratio correction on the frequency characteristics of the current error and phase displacement of the inductive current transformers evaluated for the transformation of the distorted current.

Due to the development of dedicated software and the computing capabilities of modern computers, the application of numerical methods to analyse more complex geotechnical problems is becoming increasingly common. However, there are still some areas which, due to the lack of unambiguous solutions, require a more thorough examination, e.g., the numerical simulations of displacement pile behaviour in soil. Difficulties in obtaining the convergence of simulations with the results of static load tests are mainly caused by problems with proper modelling of the pile installation process. Based on the numerical models developed so far, a new process of static load test modelling has been proposed, which includes the influence of pile installation on the soil in its vicinity and modelling of contact between steel pile and the soil. Although the presented method is not new, this is relevant and important for practitioners that may want to improve the design of displacement piles. The results of... [more]

The application of secondary NOx control methods in medium to low-capacity furnaces is a relatively new topic on the energy market and thus requires further research. In this paper, the results of full-scale research of SNCR and hybrid SNCR + SCR methods applied into a 29 MWth solid fuel fired stoker boiler is presented. The tests were performed for a full range of boiler loads, from 33% (12 MWth) to 103% (30 MWth) of nominal load. A novel SNCR + SCR hybrid process was demonstrated based on an enhanced in-furnace SNCR installation coupled with TiO2-WO3-V2O5 catalyst, which provides extra NOx reduction and works as an excess NH3 “catcher” as well. The performance of a brand-new catalyst was evaluated in comparison to a recovered one. The emission of NOx was reduced below 180 mg NOx/Nm3 at 6% O2, with ammonia slip in flue gas below 10 mg/Nm3. Special attention was paid to the analysis of ammonia slip in combustion products: flue gas and fly ash. An innovative and cost-effective method of... [more]

Natural gas is one of the main energy sources in Poland and accounts for about 15% of the primary energy consumed in the country. Poland covers only 1/5 of its demand from domestic deposits. The rest is imported from Russia, Germany, Norway, the Czech Republic, Ukraine, and Central Asia. An important issue concerning the market of energy resources is the question of the direct impact of the prices of energy resources on the income of exporting and importing countries. It should also be remembered that unexpected and large fluctuations are detrimental to both exporters and importers of primary fuels. The article analyzes natural gas deposits in Poland, raw material trade and proposes a model for forecasting the volume of its consumption, which takes into account historical consumption, prices of energy resources and assumptions of Poland’s energy policy until 2040. A hybrid model was built by combining ARIMA with LSTM artificial neural networks. The validity of the constructed model was... [more]

Heavy-duty trucks contribute approximately 20% of fuel consumption in the United States of America (USA). The fuel economy of heavy-duty vehicles (HDV) is affected by several real-world parameters like road parameters, driver behavior, weather conditions, and vehicle parameters, etc. Although modern vehicles comply with emissions regulations, potential malfunction of the engine, regular wear and tear, or other factors could affect vehicle performance. Predicting fuel consumption per trip based on dynamic on-road data can help the automotive industry to reduce the cost and time for on-road testing. Data modeling can easily help to diagnose the reason behind fuel consumption with a knowledge of input parameters. In this paper, an artificial neural network (ANN) was implemented to model fuel consumption in modern heavy-duty trucks for predicting the total and instantaneous fuel consumption of a trip based on very few key parameters, such as engine load (%), engine speed (rpm), and vehicle... [more]

Polymer electrolyte membrane fuel cells were analyzed to investigate changes in the structure of the flow field and operating conditions. The cell performance, which was controlled by adjusting the width of the cathodic channel, improved as the backpressure increases. With the anodic and cathodic flow channels mismatched, the maximum power densities at 3.0 bar for a narrow cathodic channel were 1115 and 1024 mW/cm2, and those for a wide cathodic channel were 959 and 868 mW/cm2, respectively. The diffusion characteristics were investigated using the non-dimensional numbers Re (Reynolds), Sc (Schmidt), and Sh (Sherwood) to confirm the improvement of mass transport. The narrower the channel or the higher the operating pressure, the larger Re was and the smaller Sc and Sh became. In particular, the wider the anodic channel, the larger the value of Sh.

In this paper, we study how uncertainties weighing on the climate system impact the optimal technological pathways the world energy system should take to comply with stringent mitigation objectives. We use the TIAM-World model that relies on the TIMES modelling approach. Its climate module is inspired by the DICE model. Using robust optimization techniques, we assess the impact of the climate system parameter uncertainty on energy transition pathways under various climate constraints. Unlike other studies we consider all the climate system parameters which is of primary importance since: (i) parameters and outcomes of climate models are all inherently uncertain (parametric uncertainty); and (ii) the simplified models at stake summarize phenomena that are by nature complex and non-linear in a few, sometimes linear, equations so that structural uncertainty is also a major issue. The use of robust optimization allows us to identify economic energy transition pathways under climate constra... [more]

This numerical investigation presents the effects of the position of baffles in the shape of a circle’s segment placed inside a circular channel to improve the thermal and flow performance of a solar air heater. Three different baffles’ positions with Reynolds number varying between 10,000 to 50,000 were investigated computationally. The k-omega SST model was used for solving the governing equations. Air was taken as the working fluid. Three pitch ratios (Y = 3, 4, and 5) were considered, while the height of the baffles remained fixed. The result showed an enhancement in Nusselt number, friction factor, j-factor, and thermal performance factor. Staggered exit-length baffles showed maximum enhancement in heat transfer and pressure drop, while inline inlet-length baffles showed the least enhancement. For a pitch ratio of Y = 3.0, the enhancement in all parameters was the highest, while for Y = 5.0, the enhancement in all parameters was the least. The highest thermal performance factor of... [more]

Well-logging is an important formation characterization and resource evaluation method in oil and gas exploration and development. However, there has been a shortage of well-logging data because Well-logging can only be measured by expensive and time-consuming field tests. In this study, we aimed to find effective machine learning techniques for well-logging data prediction, considering the temporal and spatial characteristics of well-logging data. To achieve this goal, the convolutional neural network (CNN) and the long short-term memory (LSTM) neural networks were combined to extract the spatial and temporal features of well-logging data, and the particle swarm optimization (PSO) algorithm was used to determine hyperparameters of the optimal CNN-LSTM architecture to predict logging curves in this study. We applied the proposed CNN-LSTM-PSO model, along with support vector regression, gradient-boosting regression, CNN-PSO, and LSTM-PSO models, to forecast photoelectric effect (PE) log... [more]

Recently, the use of new and renewable energy sources to reduce carbon dioxide emissions and minimize global warming has attracted attention. Among the different renewable energy sources, solar energy is utilized for energy reduction in buildings because of its ease of use and excellent maintenance and repair. In this study, an air-based photovoltaic/thermal (PVT) system that improves solar energy utilization was developed, and its performance was experimentally compared with that of the existing photovoltaic (PV) system. The PVT system could increase the amount of generated power by decreasing the panel temperature raised by the air passing through the lower part of the panel. Moreover, it was possible to use the high-temperature air collected from the panel for heating or hot-water supply in the building. Based on the experimental results obtained for the PV and PVT panels subjected to the same weather conditions, the power generation efficiency of the PVT panel through which air was... [more]

This article discusses issues regarding electromagnetic interference generated unintentionally by transport telematics systems and electronic security systems (ESS) located within a railway area. These systems should operate correctly, since they ensure the safety of both vehicles and passengers. The electronic devices they use are exposed to electromagnetic interference that may lead to incorrect ESS functioning. In order to determine the impact of electromagnetic interference on ESS, the authors measured unintentional low-frequency electromagnetic field generated by MV—15 and 30 kV—power lines. This enabled determining the areas with maximum values of electromagnetic interference. The next stage of the research was to develop an ESS operating process model that takes into account the impact of unintentionally generated electromagnetic interference on the operating process. Introducing the electromagnetic interference impact coefficient enables a rational selection of solutions aimed... [more]

The flow rate of solids is subject to random disturbances of the changing feed and can significantly affect the quantitative and qualitative parameters of the coal flotation products. This quantity can be described as a stochastic process. The paper presents the results of the solids flow rate model for coal flotation identification calculations, treated as a disturbance to the process. This is an innovative approach to modelling those quantitative parameters of the flotation feed that are measurably available and whose random changes have a significant impact on the enhancement process under industrial conditions. These include the volumetric flow rate of the feed and, in particular, concentration of solids in the feed. Therefore, it is suggested that random changes of these two parameters of the feed should be mapped using a model of one quantity—the flow rate of solids. This solution is advantageous because this quantity, as a quantitative parameter of the feed, has a significant im... [more]

The main purpose of this special edition of “Advances in Fluid Power Systems” was to present new scientific work in the field of fluid power systems for the hydraulic and pneumatic control of machines and devices that are used in various industries [...]

Underground mining machines, such as wheel-tyre drilling rigs, are articulated and equipped with booms that project far beyond the undercarriage. Such a structure makes these machines prone to losing stability. Hence, it is necessary to analyse the distribution of masses and geometry as well as their broadly understood stability during the entire design process, taking into account many factors resulting from the manner and conditions of their operation. However, there are no appropriate computational models that would enable analytical tests to be carried out for machines with this kind of construction. This article is concerned with the author’s computational model, which allows the stability of single- and twin-boom drilling rigs to be quickly assessed. The model makes it possible to perform analyses without having to solve differential equations that are present in dynamic models or using specialist software based on CAD and CAE tools. The developed model allows determination of th... [more]

Nowadays, new challenges arise relating to the compensation of power quality problems, where the introduction of innovative solutions based on power electronics is of paramount importance. The evolution from conventional electrical power grids to smart grids requires the use of a large number of power electronics converters, indispensable for the integration of key technologies, such as renewable energies, electric mobility and energy storage systems, which adds importance to power quality issues. Addressing these topics, this paper presents an extensive review on power electronics technologies applied to power quality improvement, highlighting, and explaining the main phenomena associated with the occurrence of power quality problems in smart grids, their cause and effects for different activity sectors, and the main power electronics topologies for each technological solution. More specifically, the paper presents a review and classification of the main power quality problems and the... [more]

The increasing popularity of automated systems and the increased market share of producers of robotic feeding equipment for cows causes the need for a deeper study of energy demand in such technologies. This article provides an analysis of the inputs of energy accumulated in conventional (CFS) and automated feeding systems (AFS) for cattle. The aim of this is to determine the impact of robotic technologies for the preparation and feeding of fodder on the cumulative energy inputs. The aim of this paper is to investigate the effect of machinery and the equipment applied to the cumulative energy intensity in cattle farming facilities. The cumulative energy consumption for four technologies of automated cattle feeding (AFS) was tested and compared to the energy consumption for six technologies with a conventional feeding system (CFS). The research involved nine cow barn facilities for dairy cows and one for beef cattle. An evaluation has been made for cattle farming structures (milk and me... [more]

A 1.2 kV SiC MOSFET with an integrated heterojunction diode and p-shield region (IHP-MOSFET) was proposed and compared to a conventional SiC MOSFET (C-MOSFET) using numerical TCAD simulation. Due to the heterojunction diode (HJD) located at the mesa region, the reverse recovery time and reverse recovery charge of the IHP-MOSFET decreased by 62.5% and 85.7%, respectively. In addition, a high breakdown voltage (BV) and low maximum oxide electric field (EMOX) could be achieved in the IHP-MOSFET by introducing a p-shield region (PSR) that effectively disperses the electric field in the off-state. The proposed device also exhibited 3.9 times lower gate-to-drain capacitance (CGD) than the C-MOSFET due to the split-gate structure and grounded PSR. As a result, the IHP-MOSFET had electrically excellent static and dynamic characteristics, and the Baliga’s figure of merit (BFOM) and high frequency figure of merit (HFFOM) were increased by 37.1% and 72.3%, respectively. Finally, the switching ene... [more]

Polymer is an insulating substance that has become increasingly popular in recent years due to its benefits. Light density, superior dielectric and thermal properties, and water-resistant or hydrophobic properties are only a few of the benefits. The presence of impurities or pollutants on the insulator’s surface lowers its dielectric capacity, which can lead to current leakage. The influence of seawater and fly ash pollutants on the distribution of the electric field and the current density of the insulator was simulated in this study. The finite element method was used to execute the simulation (FEM). Polymer insulators are subjected to testing in order to gather current leakage statistics. The tested insulator is exposed to seawater pollution, which varies depending on the equivalent salt density deposit value (ESDD). The pollutant insulator for fly ash varies depending on the value of non-soluble deposit density (NSDD). The existence of a layer of pollutants increased the value of t... [more]

Complete pump characteristics (CPCs) are the key for establishing pump boundary conditions and simulating hydraulic transients. However, they are not normally available from manufacturers, making pump station design difficult to carry out. To solve this issue, a novel method considering the inherent operating characteristics of the centrifugal pump is therefore proposed to predict the CPCs. First, depending on the Euler equations and the velocity triangles at the pump impeller, a mathematical model describing the complete characteristics of a centrifugal pump is deduced. Then, based on multiple measured CPCs, the nonlinear functional relationship between the characteristic parameters of the characteristic operating points (COPs) and the specific speed is established. Finally, by combining the mathematical model with the nonlinear relationship, the CPCs for a given specific speed are successfully predicted. A case study shows that the predicted CPCs are basically consistent with the mea... [more]

Partial discharge detection is an important means of insulation diagnosis of electrical equipment. To effectively suppress the periodic narrowband and white noise interferences in the process of partial discharge detection, a partial discharge interference suppression method based on singular value decomposition (SVD) and improved empirical mode decomposition (IEMD) is proposed in this paper. First, the partial discharge signal with periodic narrowband interference and white noise interference x(t) is decomposed by SVD. According to the distribution characteristics of single values of periodic narrowband interference signals, the singular value corresponding to periodic narrowband interference is set to zero, and the signal is reconstructed to eliminate the periodic narrowband interference in x(t). IEMD is then performed on x(t). Intrinsic mode function (IMF) is obtained by EMD, and based on the improved 3σ criterion, the obtained IMF components are statistically processed and reconstr... [more]

Nowadays, every large enterprise is concerned about reducing CO2 emissions. Along with legislation, management, packaging, and transportation decisions, optimising the operation of automated systems in the industry is important. Overheating processes or large cooling systems of one machine during product assembly may seem minor but at the industry level it is quite significant. Either an optimisation of cooling systems or an intelligent machine control which will prevent heat strokes and allow the transition to passive cooling of the whole system is an important issue for improving machine tools efficiency and contributing therefore to CO2 reduction in the industry sector. This research is a transitional phase from the creation of a control system to solve the problems of resonance in the control of systems with parallel piezo kinematics, which were designed to automate the iterative process of non-circular drilling with a precise shape and the subsequent research on the implementation... [more]

Urban sprawl is a process that shapes contemporary urban spaces. Generally, this process is associated with negative effects due to the generation of high costs. However, not all the effects of urban sprawl should be considered in the context of the increasing costs of the use of space; some of them should be regarded as cost cutting factors, for example, the possibility of the use of roofed areas in generating energy from sunlight. Solar energy is believed to be one of the sources of clean energy that reduce pollution and greenhouse gas emissions into the atmosphere. However, solar energy generation necessitates the development of large areas for the purpose of installing photovoltaic modules and substantial funds for creating large solar farms. For this reason, a significant role in state energy policies is played by small dispersed installations mounted on the roofs of buildings. There is a gap in existing research on the assessment of urban sprawl in terms of the potential use of r... [more]

Particle Swarm Optimization (PSO) is a member of the swarm intelligence-based on a metaheuristic approach which is inspired by the natural deeds of bird flocking and fish schooling. In comparison to other traditional methods, the model of PSO is widely recognized as a simple algorithm and easy to implement. However, the traditional PSO’s have two primary issues: premature convergence and loss of diversity. These problems arise at the latter stages of the evolution process when dealing with high-dimensional, complex and electromagnetic inverse problems. To address these types of issues in the PSO approach, we proposed an Improved PSO (IPSO) which employs a dynamic control parameter as well as an adaptive mutation mechanism. The main proposal of the novel adaptive mutation operator is to prevent the diversity loss of the optimization process while the dynamic factor comprises the balance between exploration and exploitation in the search domain. The experimental outcomes achieved by solv... [more]