Thermal stabilities of selected ternary phases of industrial interest in the Ag-Cu-S system have been studied by the calorimetric and electromotive force techniques. The ternary compounds Ag1.2Cu0.8S (mineral mackinstryite) and AgCuS (mineral stromeyerite) were equilibrated through high-temperature reaction of the pure Cu2S and Ag2S in an inert atmosphere. The synthesized single solid sample constituting the two ternary phases was ground into fine powders and lightly pressed into pellets before calorimetric measurements. An electrochemical cell incorporating the two equilibrated phase and additional CuS as a cathode material was employed. The measurement results obtained with both techniques were analyzed and thermodynamic properties in the system have been determined and compared with the available literature values. Enthalpy of fusion data of the Ag-richer solid solution (Ag,Cu)2S have also been determined directly from the experimental data for the first time. The thermodynamic quan... [more]

Diesel generators (DGs) are set to work as a backup during power outages or support the load in remote areas not connected to the national grid. These DGs are working at a constant speed to produce reliable AC power, while electrical energy demand fluctuates according to instantaneous needs. High electric loads occur only for a few hours a day in remote areas, resulting in oversizing DGs. During a low load operation, DGs face poor fuel efficiency and condensation of fuel residues on the walls of engine cylinders that increase friction and premature wear. One solution to increase combustion efficiency at low electric loads is to reduce diesel engine (DE) speed to its ideal regime according to the mechanical torque required by the electrical generator. Therefore, Variable Speed Diesel Generators (VSDGs) allow the operation of the diesel engine at an optimal speed according to the electrical load but require additional electrical equipment and control to maintain the power output to elect... [more]

Developing biomass energy, seen as the most important renewable energy, is becoming a prospective solution in attempting to deal with the world’s sustainability-related challenges, such as climate change, energy crisis, and carbon emission reduction. As one of the most promising second-generation energy crops, giant silvergrass (Miscanthus × giganteus) is highly valued for its high potential for biomass production and low maintenance requirements. Mapping the potential global distribution of marginal land suitable for giant silvergrass is an essential prerequisite for the development of giant silvergrass-based biomass energy. In this study, a boosting regression tree was used to identify the marginal land resources for giant silvergrass cultivation using influencing factors, which include climate conditions, soil conditions, topography conditions, and land use. The results indicate that there are 3068.25 million hectares of land resources worldwide suitable for giant silvergrass cultiv... [more]

As renewable electricity generation continues to increase in the United States (US), considerable effort goes into matching heterogeneous supply to demand at a subhour time-step. As a result, some electric providers offer incentive-based programs for residential consumers that aim to reduce electric demand during high-demand periods. There is little research into determinants of consumer response to incentive-based programs beyond typical sociodemographic characteristics. To add to this body of literature, this paper presents the findings of a dichotomous choice contingent valuation (CV) survey targeting US ratepayers’ participation in a direct-load-control scheme utilizing a smart thermostat designed to reallocate consumer electricity demand on summer days when grid stress is high. Our results show approximately 50% of respondents are willing to participate at a median willingness-to-accept (WTA) figure of USD 9.50 (95% CI: 3.74, 15.25) per month that lasts for one summer (June throug... [more]

This paper proposes an auto-tuned constrained state-feedback controller (SFC) to attenuate periodic disturbances present in permanent magnet synchronous (PMSM) motor drives. An online auto-tuning process of SFC has been made using a powerful nature-inspired optimization algorithm—artificial bee colony (ABC)—to achieve high-performance operation of the drive. A novel performance index is proposed to minimize the impact of pulsating torque and obtain smooth-velocity of the drive. The proposed approach is a practical application of classic control theory with novel engineering-tools for improving the operational quality of a PMSM drive system. The obtained results are compared with a classical cascade control structure (CCS) based on proportional-integral (PI) regulators and disturbance observer-based control (DOBC). A detailed time- and frequency-domain analysis has been conducted in respect to periodic disturbances present in a PMSM drive system. Moreover, the robustness of SFC against... [more]

With every passing second, we witness the effect of the global environmental impact of fossil fuels and carbon emissions, to which nations across the globe respond by coming up with ambitious goals to become carbon-free and energy-efficient. At the same time, electric vehicles (EVs) are developed as a possible solution to reach this ambitious goal of making a cleaner environment and facilitating smarter transportation modes. This excellent idea of shifting towards an entirely EV-based mobility industry and economy results in a range of issues that need to be addressed. The issues range from ramping up the electricity generation for the projected increase in consumption to developing an infrastructure that is large enough to support the higher demand for electricity that arises due to the market penetration of EVs. Vehicle to grid (V2G) is a concept that is largely in a testing phase in the current scenario. However, it appears to offer a solution to the issues created by a mobility sec... [more]

Forecasting the industry’s electricity consumption is essential for energy planning in a given country or region. Thus, this study aims to apply time-series forecasting models (statistical approach and artificial neural network approach) to the industrial electricity consumption in the Brazilian system. For the statistical approach, the Holt−Winters, SARIMA, Dynamic Linear Model, and TBATS (Trigonometric Box−Cox transform, ARMA errors, Trend, and Seasonal components) models were considered. For the approach of artificial neural networks, the NNAR (neural network autoregression) and MLP (multilayer perceptron) models were considered. The results indicate that the MLP model was the one that obtained the best forecasting performance for the electricity consumption of the Brazilian industry under analysis.

The current climatic scenario requires the use of innovative solutions to increase the production of electricity from renewable energy sources. Multilevel Power Inverters are a promising solution to improve the penetration of renewable energy sources into the electrical grid. Moreover, the performance of MPIs is a function of the modulation strategy employed and of its features (modulation index and switching frequency). This paper presents an extended and experimental analysis of three-phase five-level Cascaded H-Bridges Multilevel Inverter performance in terms of efficiency and harmonic content considering several MC PWM modulation strategies. In detail, the CHBMI performance is analyzed by varying the modulation index and the switching frequency. For control purposes, the NI System On Module sbRIO-9651 control board, a dedicated FPGA-based control board for power electronics and drive applications programmable in the LabVIEW environment, is used. The paper describes the modulation s... [more]

In this study, the mixing power and the axial and radial velocity distributions were determined for the standard PBT45-6 impeller with inclined blades and for three NACA impellers with airfoil blades. On the basis of the velocity distributions obtained by means of PIV techniques, the pumping efficiency and the size of the secondary circulation for the tested impellers were determined. The next stage was to calculate the efficiency of the impeller operation, in which the comparative criteria were the values of the mixing energy in the form of a dimensional and dimensionless criterion. The lowest mixing energy was obtained for impellers with symmetrical profiled NACA0021 blades, which was 20% lower than the similar mixing energy obtained for the standard PBT45-6 impeller.

Flexibility is crucial to enable the penetration of high shares of renewables in the power system while ensuring the security and affordability of the electricity dispatch. In this regard, heat−electricity sector coupling technologies are considered a promising solution for the integration of flexible devices such as thermal storage units and heat pumps. The deployment of these devices would also enable the decarbonization of the heating sector, responsible for around half of the energy consumption in the EU, of which 75% is currently supplied by fossil fuels. This paper investigates in which measure the diffusion of district heating (DH) coupled with thermal energy storage (TES) units can contribute to the overall system flexibility and to the provision of operating reserves for energy systems with high renewable penetration. The deployment of two different DH supply technologies, namely combined heat and power units (CHP) and large-scale heat pumps (P2HT), is modeled and compared in... [more]

In this study, the effect of suction flow control on a centrifugal compressor at operation and stall flow rates was investigated using computational fluid dynamics (CFD). The compressor geometry was reconstructed from available open source profile data and the CFD analyses have been performed on this geometry using the appropriate mesh. To validate the CFD results, the compressor performance line was acquired and compared with the experimental results obtained at the design rotational speed. Then, suction flow control was employed at various suction slot positions with different suction flow rates to improve the performance of the compressor at operation and stall flow rates. As a result of the suction flow control trials, 0.85% increase in pressure ratio and 0.8% increase in adiabatic efficiency were achieved while the compressor was running at operation flow rate. The performance improvements corresponding to the stall flow rate of the compressor were 2.5% increase in pressure ratio... [more]

Faults and unintended conditions in grid-connected photovoltaic systems often cause a change of the residual current. This article describes a novel machine learning based approach to detecting anomalies in the residual current of a photovoltaic system. It can be used to detect faults or critical states at an early stage and extends conventional threshold-based detection methods. For this study, a power-hardware-in-the-loop approach was carried out, in which typical faults have been injected under ideal and realistic operating conditions. The investigation shows that faults in a photovoltaic converter system cause a unique behaviour of the residual current and fault patterns can be detected and identified by using pattern recognition and variational autoencoder machine learning algorithms. In this context, it was found that the residual current is not only affected by malfunctions of the system, but also by volatile external influences. One of the main challenges here is to separate th... [more]

The aim of this article was to assess the efficiency of the utilization of public funds for climate neutrality. It was concluded that the data gathered in public statistics are not adapted to current challenges and hinder the direct measurement of climate policy objective implementation progress. Due to that, an innovative approach to public intervention efficiency analysis was proposed for the sake of decreasing CO2 emission in 27 European Union (EU) countries, based on Data Envelopment Analysis (DEA) method and soft modeling. Statistical data are derived from the Eurostat database and pertain to the years 2005−2019. It was demonstrated that activity efficiency of the particular EU countries on climate neutrality varied and that together with the increase in public funds spent on environmental protection, the growth of effects in the field of reaching climate neutrality objectives was not observed. The greatest positive impact on achieving climate neutrality objectives was revealed fo... [more]

Protection of the natural environment is a key activity driving development in the transport discipline today. The use of simulators to train civil aviation pilots provides an excellent opportunity to maintain the balance between efficiency and limit the negative impact of transport on the environment. Therefore, we decided to determine the impact of selected simulations of air operations on energy consumption. The aim of the research was to determine the energy consumption of the flight simulator depending on the type of flight operation and configuration used. We also decided to compare the obtained result with the energy consumption of an aircraft of a similar class, performing a similar aviation operation and other means of transport. In order to obtain the results, a research plan was proposed consisting of 12 scenarios differing in the simulated aircraft model, weather conditions and the use of the simulator motion platform. In each of the scenarios, energy consumption was measur... [more]

Offshore wind turbines are becoming increasingly popular due to their higher wind energy harnessing capabilities and lower visual pollution. Researchers around the globe have been reporting significant scientific advancements in offshore wind turbines technology, addressing key issues, such as aerodynamic characteristics of turbine blades, dynamic response of the turbine, structural integrity of the turbine foundation, design of the mooring cables, ground scouring and cost modelling for commercial viability. These investigations range from component-level design and analysis to system-level response and optimization using a multitude of analytical, empirical and numerical techniques. With such wide-ranging studies available in the public domain, there is a need to carry out an extensive yet critical literature review on the recent advancements in offshore wind turbine technology. Offshore wind turbine blades’ aerodynamics and the structural integrity of offshore wind turbines are of pa... [more]

Nowadays, learning-based modeling methods are utilized to build a precise forecast model for renewable power sources. Computational Intelligence (CI) techniques have been recognized as effective methods in generating and optimizing renewable tools. The complexity of this variety of energy depends on its coverage of large sizes of data and parameters, which have to be investigated thoroughly. This paper covered the most resent and important researchers in the domain of renewable problems using the learning-based methods. Various types of Deep Learning (DL) and Machine Learning (ML) algorithms employed in Solar and Wind energy supplies are given. The performance of the given methods in the literature is assessed by a new taxonomy. This paper focus on conducting comprehensive state-of-the-art methods heading to performance evaluation of the given techniques and discusses vital difficulties and possibilities for extensive research. Based on the results, variations in efficiency, robustness... [more]

Multiple techniques continue to be simultaneously utilized in the condition monitoring and fault detection of electric machines, as there is still no single technique that provides an all-round solution to fault finding in these machines. Having various machine fault-detection techniques is useful in allowing the ability to combine two or more in a manner that will provide a more comprehensive application-dependent condition-monitoring solution; especially, given the increasing role these machines are expected to play in man’s transition to a more sustainable environment, where many more electric machines will be required. This paper presents a novel non-invasive optical fiber using a stray flux technique for the condition monitoring and fault detection of induction machines. A giant magnetostrictive transducer, made of terfenol-D, was bonded onto a fiber Bragg grating, to form a composite FBG-T sensor, which utilizes the machines’ stray flux to determine the internal condition of the... [more]

Suspended monorails are a common mode of transportation for materials and personnel in underground mines. The goal of the EU-funded project “Innovative High Efficiency Power System for Machines and Devices, Increasing the Level of Work Safety in Underground Mining Excavations (HEETII)” is to introduce a single-wire energy transmission system combined with a capacitive-coupling-based wireless transmission system to power the suspended tractor, along with a monitoring system that will monitor the energy network and additional environmental parameters of the mine. Additionally, the monitoring system acts as the wireless communication backbone, allowing for data transmission to surface headquarters, where the data are processed and logged in a central database. This enables operators to detect and take preemptive measures to prevent potential hazards in the mine, improving the overall efficiency of the energy transmission system. This paper describes the additional considerations required... [more]

This paper presents a novel capacitor voltage balancing control approach for cascaded multilevel inverters with an arbitrary number of series-connected H-Bridge modules (floating capacitor modules) with asymmetric voltages, tiered by a factor of two (binary asymmetric). Using a nearest-level reference waveform, the balancing approach uses a one-step-ahead approach to find the optimal switching-state combination among all redundant switching-state combinations to balance the capacitor voltages as quickly as possible. Moreover, using a Lyapunov function candidate and considering LaSalle’s invariance principle, it is shown that an offline calculated trajectory of optimal switching-state combinations for each discrete output voltage level can be used to operate (asymptotically stable) the inverter without measuring any of the capacitor voltages, achieving a novel sensorless control as well. To verify the stability of the one-step-ahead balancing approach and its sensorless variant, a demon... [more]

Energy consumption in buildings is expected to increase by 40% over the next 20 years. Electricity remains the largest source of energy used by buildings, and the demand for it is growing. Building energy improvement strategies is needed to mitigate the impact of growing energy demand. Introducing a smart energy management system in buildings is an ambitious yet increasingly achievable goal that is gaining momentum across geographic regions and corporate markets in the world due to its potential in saving energy costs consumed by the buildings. This paper presents a Smart Building Energy Management system (SBEMS), which is connected to a bidirectional power network. The smart building has both thermal and electrical power loops. Renewable energy from wind and photo-voltaic, battery storage system, auxiliary boiler, a fuel cell-based combined heat and power system, heat sharing from neighboring buildings, and heat storage tank are among the main components of the smart building. A const... [more]

The frequency of power systems is very sensitive to load variations. Additionally, with the increased penetration of renewable energy sources in electrical grids, stabilizing the system frequency becomes more challenging. Therefore, Load Frequency Control (LFC) is used to keep the frequency within its acceptable limits. In this paper, an adaptive controller is proposed to enhance the system performance under load variations. Moreover, the proposed controller overcomes the disturbances resulting from the natural operation of the renewable energy sources such as Wave Energy Conversion System (WECS) and Photovoltaic (PV) system. The superiority of the proposed controller compared to the classical LFC schemes is that it has auto tuned parameters. The validation of the proposed controller is carried out through four case studies. The first case study is dedicated to a two-area LFC system under load variations. The WECS is considered as a disturbance for the second case study. Moreover, to d... [more]

This study uses deep learning algorithms to predict the rotational speed of the turbine generator in an oscillating water column-type wave energy converter (OWC-WEC). The effective control and operation of OWC-WECs remain a challenge due to the variation in the input wave energy and the significantly high peak-to-average power ratio. Therefore, the rated power control of OWC-WECs is essential for increasing the operating time and power output. The existing rated power control method is based on the instantaneous rotational speed of the turbine generator. However, due to physical limitations, such as the valve operating time, a more refined rated power control method is required. Therefore, we propose a method that applies a deep learning algorithm. Our method predicts the instantaneous rotational speed of the turbine generator and the rated power control is performed based on the prediction. This enables precise control through the operation of the high-speed safety valve before the en... [more]

Electric vehicles represent an innovation in mobility that can help significantly reduce greenhouse emissions and mitigate climate change. However, replacing internal combustion with electric vehicles is not enough. This replacement needs to be complemented with a change in the energy mix of individual countries towards renewable energy sources and efficient use of electricity generated as a secondary product. Recuperative braking energy from trains can serve as one source of such secondary energy. Following an analysis of recuperative energy generated and analysis of charging requirements of individual electric vehicles, the paper proposes a model of a charging site near train stations. Using this energy to charge electric vehicles helps to reduce energy consumption from the electricity grid and thus reduce carbon emissions. Compared to other articles, the proposed model ensures the efficient use of recuperative braking energy from trains by using the variable charging power function;... [more]

Moonpool-type floaters were initially proposed for applications such as artificial islands or as protecting barriers around a small area enabling work at the inner surface to be carried out in relatively calm water. In recent years, a growing interest on such structures has been noted, especially in relation to their use as heaving wave energy converters or as oscillating water column (OWC) devices for the extraction of energy from waves. Furthermore, in the offshore marine industry, several types of vessels are frequently constructed with moonpools. The present paper deals with the hydrodynamics of bottomless cylindrical bodies having vertical symmetry axis and floating in a water of finite depth. Two computation methods were implemented and compared: a theoretical approach solving analytically the corresponding diffraction problem around the moonpool floater and a computational fluid dynamics (CFD) solver, which considers the viscous effects near the sharp edges of the body (vortex s... [more]

The article applies a three-stage Slacks-Based Measure-Data Envelopment Analysis (SBM-DEA) pattern to examine the relationship between energy consumption and unfavorable CO2 emissions on green sustainable development, for the 11 cities of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) during 2010−2016, by going through various violated factors and stochastic disturbance. Labor, capital and energy resource are chosen as input variables, while GDP and CO2 emission as output variables. During the three phases consisting of the SBM-DEA model (first stage and third stage) and SFA analysis (second stage), CO2 emission is considered as an unfavorable outcome, while stochastic statistical disturbances and external environmental influences are identified. The results show that the average efficiency of the GBA cities is 0.708, with only Shenzhen, Macao SAR and Hong Kong SAR having an efficiency of 1 during the whole study period. Based on the findings, suggestions are made for the GBA cit... [more]