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]

Monitoring the variation of the loading blades is fundamental due to its importance in the behavior of the wind turbine system. Blade performance can be affected by different loads that alter energy conversion efficiency and cause potential safety hazards. An example of this is icing on the blades. Therefore, the main objective of this work is to propose a proportional digital controller capable of detecting load variations in wind turbine blades together with a fault detection method. An experimental platform is then built to experimentally validate the main contribution of the article. This platform employs an automotive throttle device as a blade system emulator of a wind turbine pitch system. In addition, a statistical fault detection algorithm is established based on the point change methodology. Experimental data support our approach.

Advanced control system design for large wind turbines is becoming increasingly complex, and high-level optimization techniques are receiving particular attention as an instrument to fulfil this significant degree of design requirements. Multiobjective optimal (MOO) control, in particular, is today a popular methodology for achieving a control system that conciliates multiple design objectives that may typically be incompatible. Multiobjective optimization was a matter of theoretical study for a long time, particularly in the areas of game theory and operations research. Nevertheless, the discipline experienced remarkable progress and multiple advances over the last two decades. Thus, many high-complexity optimization algorithms are currently accessible to address current control problems in systems engineering. On the other hand, utilizing such methods is not straightforward and requires a long period of trying and searching for, among other aspects, start parameters, adequate objecti... [more]

Storing CO2 in geological formations is an important component of reducing greenhouse gases emissions. The Carbon Capture and Storage (CCS) industry is now in its establishing phase, and if successful, massive storage volumes would be needed. It will hence be important to utilize each storage site to its maximum, without challenging the formation integrity. For different reasons, supply of CO2 to the injection sites may be periodical or unstable, often considered as a risk element reducing the overall efficiency and economics of CCS projects. In this paper we present outcomes of investigations focusing on a variety of positive aspects of periodic CO2 injection, including pressure management and storage capacity, also highlighting reservoir monitoring opportunities. A feasibility study of periodic injection into an infinite saline aquifer using a mechanistic reservoir model has indicated significant improvement in storage capacity compared to continuous injection. The reservoir pressure... [more]

Smart building issues are critical for current energy and comfort managing aspects in built environments. Nevertheless, the diffusion of smart monitoring solutions via user-friendly graphical interfaces is still an ongoing issue subject to the need to diffuse a smart building culture and a low-cost series of solutions. This paper proposes a new low-cost IoT sensor network, exploiting Raspberry Pi and Arduino platforms, for collecting real-time data and evaluating specific thermal comfort indicators (PMV and PPD). The overall architecture was accordingly designed, including the hardware setup, the back-end and the Android user interface. Eventually, three distinct prototyping platforms were deployed for initial testing of the general system, and we analysed the obtained results for different building typologies and seasonal periods, based on collected data and users’ preferences. This work is part of a large educational and citizen science activity.

, a xylose-fermenting yeast, has the potential for converting cellulosic biomass to ethanol. Thermotolerant C. tropicalis X-17, which was isolated in Laos, was subjected to repetitive long-term cultivation with a gradual increase in temperature (RLCGT) in the presence of a high concentration of glucose, which exposed cells to various stresses in addition to the high concentration of glucose and high temperatures. The resultant adapted strain demonstrated increased tolerance to ethanol, furfural and hydroxymethylfurfural at high temperatures and displayed improvement in fermentation ability at high glucose concentrations and xylose-fermenting ability. Transcriptome analysis revealed the up-regulation of a gene for a glucose transporter of the major facilitator superfamily and genes for stress response and cell wall proteins. Additionally, hydropathy analysis revealed that three genes for putative membrane proteins with multiple membrane-spanning segments were also up-regulated. From the... [more]

Fly ash is the main by-product of coal combustion characterized by a large specific surface area. In addition to oxides, it also contains unburned coal and trace elements. This study aimed to investigate the possibility of using fly ash from pit-coal combustion (CFA) for the treatment of benzene-contaminated soil (S). The CFA was used as a mixture with Portland cement (PC) (70% PC + 30% CFA). The soil was treated with a PC-CFA mixture in amounts of 40, 60, and 80% of soil mass. During the process, the concentration of benzene was monitored with the flame-ionization detector. Produced monoliths (S+(PC-CFA)x) were tested for compressive strength and capillary water absorption. The experiment confirmed that the PC-CFA mixture limited benzene emission. The highest reduction in benzene concentration (34−39%) was observed for samples treated with the PC-CFA mixture in an amount of 80% (S+(PC-CFA)80). The average compressive strength of monoliths S+(PC-CFA)40, S+(PC-CFA)60, and S+(PC-CFA)80 w... [more]

This study aims to examine energy security in terms of crude oil and copper supply. While oil remains the leading energy commodity globally, copper is crucial for many new technologies, foremost for RES. Therefore, both oil and copper are extremely important for current and future energy security. This article contains a bivariate methodological approach to a comparative analysis of oil and copper supply: determining supply security with an Index of security of supply, and examines price stability with generalized autoregressive conditional heteroscedasticity (GARCH) models. This research provides evidence that there are many differences but also significant similarities between these two completely different commodities in terms of both supply security and price stability. Facing the future for RES, significant demand may cause a threat to energy security on a previously unknown scale. Therefore this instability, both supply- and price-related, appears to be the main threat to future... [more]