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In this work, we have developed a functional construction material from a cement material that can scavenge mechanical energy from surrounding environment into electricity. An energy harvesting device called "a triboelectric nanogenerator (TENG)" is fabricated from the cement–reduced graphene oxide (rGO) composite to convert mechanical energy into electrical power. The incorporation of rGO in cement is found to enhance the electrical output of the TENG through space charge polarization, resulting in the increase in triboelectric charge density. The maximum power density achieved from the cement–rGO composite TENG is 1.72 W/m2, which is six times greater than that of the unmodified cement TENG. Additionally, rGO improves the compressive strength of the cement composite by up to 50%. This enhancement is attributed to the large specific surface area of rGO, which creates nucleation sites, resulting in increased crystallization of cement hydration products. The findings of this work highlight the promising prospects for the development of functional construction material for smart energy building with improved mechanical strength. [ABSTRACT FROM AUTHOR]

Switchgear is a vital component of modern power systems, responsible for regulating the flow of electrical power. Contact issues, irregular loads, and other similar problems can cause switchgear to overheat, leading to unexpected disturbances and potential damage to the power equipment. Thermal imaging shows significant potential and is increasingly employed to detect faults in power equipment. However, the unique characteristics of thermal images often pose challenges to accurate fault detection. This research aims to study the effectiveness of transfer learning architectures for switchgear fault detection. This paper applies eleven transfer learning architectures, including SqueezeNet, GoogLeNet, InceptionV3, DenseNet201, ResNet50, Xception, InceptionResNetV2, ShuffleNet, EfficientNetB0, AlexNet, and VGG19. The results of the testing phase demonstrated that the application of transfer learning by fine-tuning pre-trained convolutional neural network architectures was highly effective in the classification of thermal images captured from switchgear units. The models achieved accuracy rates between 83.87% and 98.38%, and values of F 1 -Scores between 83.11% and 98.34% in the pre-trained architectures. [Display omitted] • Transfer learning is applied to address the unique characteristics of thermal images for switchgear fault detection. • A thermal image dataset is setup and augmented to improve the classification performance. • Establish standard comparisons among eleven transfer learning architectures. • Achieve rapid and precise classification with the proposed transfer learning architectures. [ABSTRACT FROM AUTHOR]

Electricity transmission lines constitute a vital element in any electrical power system. Nevertheless, the progressive collapse of these structures caused by accidental events and cascade failure can lead to a wide range of failures, including total collapse. The failure of power transmission line structures due to extreme wind and ice loads poses a substantial challenge for electrical power distribution companies globally. In this study, the progressive collapse behavior of a 230-kV electrical power transmission line in Fars Province, Iran was evaluated utilizing the alternative load path method within a nonlinear dynamic analysis framework. Finite element models of a tangent electricity tower (DC0), a terminal tower (DC90), and the conductors of the transmission line were created and simulated using SAP2000 software. The investigation focused on the impact of removing the legs of the transmission tower, and the simulation analyzed the progressive collapse behavior under various loading conditions, including wind load, snow-induced freezing, and simultaneous wind and ice load. By employing the nonlinear dynamic analysis of the progressive collapse, the stresses developed in the structural elements were evaluated, and the damaged elements were identified. The results demonstrated that following the failure of one leg, the tangent and terminal towers remained stable under gravitational loads. However, under extreme winds at a 90∘ angle, the failure of a leg resulted in significant damage to the towers. Further assessment of the tangent and terminal towers revealed that the terminal tower exhibited higher strength compared to the tangent tower. This was evident in the lower dispersion of displacements and a reduced number of damaged elements observed in the terminal tower when one leg was removed. [ABSTRACT FROM AUTHOR]

Electric Power Research Institute of Guangdong Power Grid Co., Ltd., Guangzhou, China, 2Guangdong Power Grid Co., Ltd., Guangzhou, China, 3China Southern Power Grid Co., Ltd., Guangzhou, China To achieve load management optimization and timely failure warning for power transformers, as well as improve the reliability of the power network, this paper proposes a multiple time scale prediction method for top oil temperature (TOT) based on an adaptive extended Kalman filter (AEKF) algorithm. This method combines the Kalman filter (KF) algorithm and the D. Susa thermal model. The TOT, oil exponent and oil time constant are taken as state variables, while the ambient temperature and load current are used as input variables. The iterative optimization of the oil exponent and oil time constant is realized by comparing the estimated and observed TOT values. Moreover, the proposed method utilizes an adaptive noise estimator to correct the noise statistics parameters, which simplifies the initial noise setting and thus further improves the TOT prediction accuracy. A case study is conducted with two 110 kV transformers. The results show that comparing the thermal equivalent circuit model and the extended KF algorithm, the proposed method has a higher accuracy in the intraday ultra-short-term prediction on a 15-min time scale and day-ahead short-term prediction on a 24-h time scale for the TOT. [ABSTRACT FROM AUTHOR]

The surge in global energy demand mandates a significant expansion of electric power substations. Nevertheless, the ecological consequences of electric power substation operation, particularly concerning the electromagnetic field, on soil microbial communities and nitrogen enrichment remain unexplored. In this study, we collected soil samples from six distinct sites at varying distances from an electric power substation in Xintang village, southeastern China, and investigated the impacts of electromagnetic field on the microbial diversity and community structures employing metagenomic sequencing technique. Our results showed discernible dissimilarities in the fungal community across the six distinct sites, each characterized by unique magnetic and electric intensities, whereas comparable variations were not evident within bacterial communities. Correlation analysis revealed a diminished nitrogen fixation capacity at the site nearest to the substation, characterized by low moisture content, elevated pH, and robust magnetic induction intensity and electric field intensity. Conversely, heightened nitrification processes were observed at this location compared to others. These findings were substantiated by the relative abundance of key genes associated with ammonium nitrogen and nitrate nitrogen production. This study provides insights into the relationships between soil microbial communities and the enduring operation of electric power substations, thereby contributing fundamental information essential for the rigorous environmental impact assessments of these facilities. [ABSTRACT FROM AUTHOR]

This work explores the potential of self-powered MEMS devices for application in the preventive conservation of cultural heritage. The main objective is to evaluate the effectiveness of piezoelectric aluminum nitride MEMS (AlN-MEMS) for monitoring vibrations and to investigate its potential for harvesting energy from vibrations, including those induced by visitors. A preliminary laboratory comparison was conducted between AlN-MEMS and the commercial device Tromino®. The study was then extended to the Picture Gallery of Ursino Castle, where joint measurements with the two devices were carried out. The analysis focused on identifying natural frequencies and vibrational energy levels by key metrics, including spectral peaks and the Power Spectral Density (PSD). The results indicated that the response of the AlN-MEMS aligned well with the data collected by the commercial device, especially observing high vibrational energy around 100 Hz. Such results validate the potential of AlN-MEMS for effective vibration measurement and for converting kinetic energy into electrical power, thereby eliminating the need for external power sources. Additionally, the vibrational analysis highlighted specific locations, such as the measurement point Cu4, as exhibiting the highest vibrational energy levels. These points could be used for placing MEMS sensors to ensure efficient vibration monitoring and energy harvesting. [ABSTRACT FROM AUTHOR]

Photovoltaic technology has become one of the major renewable ways to generate electric power. However, the mismatch between the incident solar spectrum and photo-electric response efficiency of solar cells severely constrains their performance. Hence, spectral modification technologies, e.g., up-conversion (UC), down-conversion (DC), and luminescent down-shifting (LDS) technologies have been applied widely in the photovoltaic field to reform the incident spectrum to match the best response band possible. In this paper, we review the latest developments of the three technologies above in terms of material selection, optical characteristics, and photovoltaic performance. It is found that the three most popular materials for conversion are NaYF4: Er3+, Yb3+, and Yb3+. The excitation bands for the three technologies are 800–1550 nm, 250–488 nm, and 250–488 nm, respectively, while the emission bands are 523–669 nm, 520–1031 nm, and 490–1010 nm, respectively. Furthermore, issues hindering the development of spectral modification technologies are pointed out, e.g., low absorption efficiency, poor quantum conversion efficiency, and hurdles in commercialization. Finally, suggestions and solutions to address the above-mentioned issues are provided. [ABSTRACT FROM AUTHOR]

Nowadays, the microgrid system is characterized by a diversification of power factors and a complex network structure. Existing studies on microgrid fault diagnosis and troubleshooting mostly focus on the fault detection and operation optimization of a single power device. However, for increasingly complex microgrid systems, it becomes increasingly challenging to effectively contain faults within a specific spatiotemporal range. This can lead to the spread of power faults, posing great harm to the safety of the microgrid. The topology optimization of the microgrid based on deep reinforcement learning proposed in this paper starts from the overall power grid and aims to minimize the overall failure rate of the microgrid by optimizing the topology of the power grid. This approach can limit internal faults within a small range, greatly improving the safety and reliability of microgrid operation. The method proposed in this paper can optimize the network topology for the single node fault and multi-node fault, reducing the influence range of the node fault by 21% and 58%, respectively. [ABSTRACT FROM AUTHOR]

Electrical vehicles are finding wide acceptance in the Jordanian transportation market; this has caused an accelerating shift in the emissions of greenhouse gases from the direct burning of fossil fuels consumed by the transportation sector towards the power generation sector. On the other hand, as electric vehicles gain more popularity, an extra load is added to the electrical power generation systems, raising essential concerns such as the capability of the power network to support this massive extra load and the increased emission of greenhouse gases caused by power plants. Studies show that Jordan's weather is known for being bright, sunny, and very suitable for the generation of electric power from solar energy sources. Therefore, with an infrastructure that can support convenient off-grid charging, a huge burden will be taken off the national grid and the environment. Therefore, this work proposes a basic design for an off-grid PV-covered carport and presents a study of the economics and effectiveness of using such a system to charge electric vehicles owned by the students and employees of the Applied Science Private University. The study is based on actual solar irradiance data collected on-site during university working hours (8 a.m.–5 p.m.) to allow students and employees to charge their electric vehicles from an off-grid carport system while on campus. Space limitations for carport design, initial design cost, return on investment, and annual electricity consumption are discussed to demonstrate the benefits of such a system for both the consumer (convenience and low charging cost) and the power company provider (less load to maintain). [ABSTRACT FROM AUTHOR]

In a conventional automotive manufacturing plant, the paint shop alone can represent 36% of the total energy consumption, making it the most demanding area in terms of electricity and fossil fuel energy consumption. This study explores the possibility of decentralizing the production of electrical power and heat simultaneously, using an Organic Rankine Cycle (ORC) system integrated with a Parabolic Trough Collector (PTC) in a paint shop. To date, no similar system has been explored or implemented by the automotive industry. To increase the efficiency of the integrated system, wasted heat generated during the paint manufacturing process is recovered and used to pre-heat the organic fluid in the ORC system. A 4E analysis (Energy, Exergy, Economic, and Environmental) is conducted to determine the practical viability of the proposed system. When applied to the southern region of the USA, this system's installed capacity is projected to be 11 times higher than the two unique SORC pieces of equipment currently running in Louisiana and Florida. The goals are to reduce the reliance on external primary energy sources and decrease the carbon emission footprint from production activity. The system is evaluated for a location in Alabama, USA. The designed SORC, using toluene, can produce 712.2 kWel net and 13,132 kg/h of hot water, with an overall energy efficiency of 31.02%; exergy efficiency of 34.23; and ORC efficiency of 27.70%. This leads to an electrical energy saving of 5.9% for the manufacturing plant. The regenerative thermal oxidizer (RTO) heat exchanger, the secondary heat source of the system, has the highest exergy destruction—3583 kW. The system avoids the emission of 4521 tCO2 per year. A payback period of 10.16 years for the proposed system is estimated. Considering a planning horizon of 10 years, the investment in the system is also justified by a benefit–cost analysis. [ABSTRACT FROM AUTHOR]

High temperatures in photovoltaic (PV) modules lead to the degradation of electrical efficiency. To address the challenge of reducing the temperature of photovoltaic modules and enhancing their electrical power output efficiency, a simple but efficient photovoltaic cooling system based on heat pipes (PV-HP) is introduced in this study. Through experimental and numerical investigations, this study delves into the temperature characteristics and power output performance of the PV-HP system. Orthogonal tests are conducted to discern the influence of different factors on the PV-HP system. The experimental findings indicate that the performance of the PV-HP system is superior to that of the single system without heat pipes. The numerical simulation shows the effects of system structural parameters (number of heat pipes, angle of heat pipe condensation section) on system temperature and power output performance. The numerical simulation results show that increasing the angle of the heat pipe condensation section and the number of heat pipes leads to a significant drop in system temperature and an increase in the efficiency of the photovoltaic cells. [ABSTRACT FROM AUTHOR]

This research proposes the utilization of Peltier modules to convert electrical energy from thermal energy to show its potential as a renewable energy source for residential and commercial application. The study, whose results are presented in this manuscript, was conducted in the city of Monterrey, located in the northeast of Mexico. The energy source was tested and analyzed utilizing a set of statistical metrics and further comparison against experimental test results. The Distrito Tec area in Monterrey city is an academic complex and it was chosen for this study, which consisted of the indirect measurement of the average annual heat energy stored within the buildings' cement structure. The aim was to obtain the annual accumulated electrical power in Wh per year that Peltier modules could provide in Distrito Tec, which is located in a city with solar irradiation levels above the world average. The proposal in this paper could encourage further investigation regarding this energy that is currently waste heat. More specifically, the results of this research highlight the importance of thermoelectric modules and seek to motivate research to improve their properties and make them more efficient and more viable as well. Thermoelectric modules have the potential to be part of the solution to sustainable development as presented in the United Nations SDG-7—ensure access to affordable, reliable, sustainable and modern energy for all. [ABSTRACT FROM AUTHOR]

It is essential to protect control, regulation and data storage units used in automated robotic manufacturing from the consequences of harmful electrical grid harmonics. In this paper, the effectiveness of active/passive harmonic filters built into LED lamps, test benches, and industrial robots was investigated (in the latter two cases, light and heavy load states were applied). Based on network analysis, it was found that the built-in passive harmonic filters of the luminaries were ineffective because the THD of the current was approximately two or three times the permissible value according to the IEEE 519-2022 standard. It was proved that the built-in active harmonic filter of the test bench at a heavy load worked properly, but at a light load it was not effective, while the magnitude of harmonic distortion of the industrial robot exceeded the allowed level (three times the limit at a light load, seven times the limit at a heavy load). Further measurements were also performed at three locations: an engineering room, a gearbox house machine tool, and an office room (where there were no built-in filters). The results proved that in each case, there was a significant exceedance of the limit value. Therefore, protection against harmonics needs to be installed, and then the measurements must be repeated. [ABSTRACT FROM AUTHOR]

Mechanical energy harvesters made from soft and flexible materials can be employed as energy sources for wearable and implantable devices. However, considering how human organs and joints expand and bend in many directions, the energy generated in response to a mechanical stimulus in only one direction limits the applicability of mechanical energy harvesters. Here, we report carbon nanotube (CNT) sheets/an elastomer bilayer harvesting electrode (CBHE) that converts two-axis mechanical stimulation into electrical energy. The novel microwinkled structure of the CBHE successfully demonstrates an electrochemical double-layer (EDL) capacitance change from biaxial mechanical stimulation, thereby generating electrical power (0.11 W kg−1). Additionally, the low modulus (0.16 MPa) and high deformability due to the elastomeric substrate suggest that the CBHE can be applied to the human body. [ABSTRACT FROM AUTHOR]

The demand for electric power has consistently been on the rise, owing to urbanisation and technological improvements. On the generation side, renewable sources have been favoured over their polluting, exhaustible, non‐renewable counterparts. These changes in the power system have necessitated a system for maintaining the supply‐demand balance, to maintain system stability. A complex power system is also more prone to blackouts and grid failure. Islanding helps in provision of supply to consumers in a microgrid, reducing the possibility of a blackout. Depending on the power demand and generation, loads need to be shed or restored to mitigate power imbalances. A wide area distribution management system (WADMS) is proposed to dynamically shed and restore loads in the islanded mode, with the aid of micro phasor measurement units (µPMUs). A priority and consumer‐based load shedding and restoration (PCLS) algorithm is proposed in the WADMS that preferentially sheds or restores loads based on their assigned load priority indices and number of consumers. The algorithm has been tested on a modified IEEE 13 bus system, incorporated with a solar photovoltaic (PV) system, diesel generators (DGs) and an energy storage system (ESS) in MATLAB Simulink. [ABSTRACT FROM AUTHOR]

Satellites engaged in observation missions often face severe pointing constraints, which can limit the ability of their solar panels optimize the generation of electrical power during payload operations. Some approaches to maximize power generation involve either using orientable solar panels, or performing orbital maneuvers to point fixed or deployable (non-orientable) solar panels towards the Sun, which can compromise the payload's ability to meet its pointing requirements. In this study, an alternative approach that enables high-consuming remote sensing payloads to operate for extended periods without requiring orientable solar panels is presented. The satellite under consideration is equipped with fixed or deployable (non-orientable) solar panels mounted on up to three different perpendicular faces. The on-board payload is required to remain within a fixed angle from a target direction, which can be either nadir or a specific geographical position. To derive an optimal tracking law, the projected solar array area at each instant is maximized, resulting in optimal electrical power generation. This methodology allows the satellite to maintain its pointing constraints and efficiently operate high-consuming payloads for longer periods. The proposed tracking law is validated using an actual mission scenario, comparing the power generation achieved by the proposed method against other techniques. The approach presented in this paper shows improved performance, enabling satellites equipped with non-orientable solar panels to fulfill their observation requirements while optimizing electrical power generation. This work offers significant benefits for satellite operators, reducing the need for costly orientable solar panels and enhancing the overall efficiency of satellite missions. • Guidance law for optimal power generation while complying with payload pointing constraints. • Simple and easy formulation, suitable for real-time systems. • Methodology validated and compared against other attitude strategies. • Integration and simulation of the guidance law into a control scheme. [ABSTRACT FROM AUTHOR]

The electric power industry is a high-risk industry with frequent accidents. To ensure the life safety of employees and reduce the probability of accidents, it is necessary to utilize certain technical means to identify the main causative factors in electric fatal accident reports. This research proposes an accident causation identification method that combines text categorization and catastrophe association analysis. First, an improved text feature extraction method (TF-IDF-GloVe-LDA) is proposed by fusing term frequency-inverse document frequency (TF-IDF), global vectors for word representation (GloVe), and latent dirichlet allocation (LDA) algorithms. Then, an SVM classifier was used to categorize the 473 accident report texts into five categories, ACCIDENT, PROCESS, CAUSE, PROBLEM, and RESPONSE, based on the extracted text feature vectors. Second, for the 461 CAUSEs categorized from the accident report texts, the TF-IDF algorithm is utilized to mine them to obtain 62 accident causative factors. Using the word cloud map and semantic network, a visualization analysis is performed to reveal the intrinsic connection between causative factors. The human factor analysis and classification system (HFACS) is combined to construct a framework and a Boolean dataset for electric power fatal accident causative factors. Finally, the catastrophe progression method is utilized to improve the FP-growth algorithm and propose a catastrophe association analysis method. It is utilized to mine the Boolean dataset to obtain 28 association rules and construct the accident causal network. The main causative factors were ultimately identified by analyzing the critical causal chains within the network and examining the frequency and sensitivity of each node. The findings of this study indicate that a lack of effective management, supervision, and training serves as the fundamental cause of fatal accidents in the electric power industry when compared to equipment and environmental factors. This paper offered a fresh perspective on identifying primary accident causative factors in non-standardized text and exploring their intricate mechanisms of interaction, which holds significant implications for the pre-control management of accidents in the power industry. [ABSTRACT FROM AUTHOR]

It is shown that the transformation of the energy sector based on the construction of new architectures of energy systems requires a joint consideration of three layers of two-way energy information exchange: economic, informationmanagement, and physical (energy), and the functioning of modern electric power systems requires the application of process monitoring with enhanced functionality. For such intelligent monitoring, defined as Smart-monitoring, the first and second level monitoring procedures are characterized, in particular, taking into account measurement with a change in signal type, operation with information with syntactic, semantic and pragmatic adequacy, diagnosis with identification and forecasting. It is shown that Smart-monitoring in electric power at the level of medium and low voltages (distribution and consumption systems) should be formed as a technological platform for diagnosis, audit, control, dispatching, energy management of electric power systems, formation of modern energy markets. [ABSTRACT FROM AUTHOR]

Copper-clad steel wire is widely used in electric power, railroads, automobiles, and other fields. However, how to balance production efficiency and wire quality is still a challenging task. In this paper, a continuous cladding composite casting method for copper-clad steel wire is proposed based on the hot-dip plating process, which adopts a removable graphite crucible and S-shaped wiring to control the thickness and eccentricity of the cladding metal, and at the same time adopts connecting the electrical resistance furnace with a water-cooled crystallizer to achieve rapid solidification, which in turn strengthens the mechanical properties of the copper-clad wire and thus realizes the rapid and continuous preparation of copper-clad steel wires with good quality. In this study, the optimum process parameters, including drawing speed and pure copper melt temperature, were provided to reveal the mechanism of metallurgical bonding at the solid–liquid composite interface. The circumferential uniformity, mechanical properties, and electrical conductivity of the prepared copper-clad steel wires were tested. The growth mechanism of the copper-coated structure and the mechanism of rapid solidification to strengthen the mechanical properties are described. The results have been plotted in graphs to describe the properties and characteristics of the materials. [ABSTRACT FROM AUTHOR]

Purpose. To obtain analytical dependencies for the precise calculation of the stator current of a frequency-regulated three-phase shortcircuited induction motor and to estimate the components of its main electrical power losses, which are spent on the transportation magnetic power losses (to the magnetization circuit) and additional power losses (through the motor air gap), as well as with using the obtained refined dependencies to research the electromagnetic processes and energy modes of the frequency-regulated induction motor when its speed and load change. Methodology. The method of generalized vectors is used for the refined calculation of the electromagnetic processes and energy modes of the frequency-regulated induction motor. Results. Based on the catalog data and parameters of the induction motor’s equivalent replacement circuit, also the specified values of its useful rotational torque and speed, refined analytical dependencies were obtained for the calculation of the main electromagnetic power losses of the frequency-regulated induction motor, which take into account the influence of all types of power losses, which present in it, as well as – power losses spent on transporting magnetic losses (to the magnetization circuit) and additional losses (through the air gap of the motor). With the help of the obtained dependencies, the energy modes (including main power consumption and electromagnetic power losses, efficiency factor, power factor) of the frequency-regulated induction motor in the driving and generator modes of its operation in relation to the first (at speeds not higher than the nominal) and the second (at speeds above the nominal) speed control zones for the operating ranges of the motor useful rotational torque and speed changes were calculated. Originality. A refined analytical calculation dependence has been obtained for determining the active projection of the generalized stator current vector of a frequency-regulated induction motor, which takes into account the presence of additional power losses and the component of electrical losses caused by the transportation of additional power losses through the air gap of the motor; an analytical dependence is also proposed for determining the increment of the mentioned active projection, which is due to the transportation of magnetic power losses to the motor magnetization circuit. Practical value. Analytical calculation dependencies are proposed for the quantitative assessment of errors (as a percentage of mentioned values) in steady-state modes for determining the main electromagnetic power losses of the frequency-regulated induction motor, caused by the absence (in comparison with relevant studies from known publications) of taking into account additional and magnetic power losses, as well as – the influence of electrical component losses caused by the transportation of the mentioned power losses through the air gap or to the magnetization circuit of the motor, respectively. References 16, tables 5, figures 2. [ABSTRACT FROM AUTHOR]

Introduction. Solar photovoltaic (PV) has recently become very important especially in electrical power applications for countries with high luminosity because it is an effectively unlimited available energy resource. Depending on solar radiation and temperature, the PV generator has a non-linear characteristic with a maximum power point (MPP). The novelty is the efficiency improvement of a PV energy module, it is necessary to track the MPP of the PV array regardless of temperature or irradiation circumstances. Purpose. This paper presents the modeling and the digitally simulation under MATLAB/Simulink of a Fuzzy Logic Controller based on Voltage Perturbation Algorithm (FLC-VPA) applied to PV battery charging system, which consists of PV module, DC-DC boost converter, MPP tracking (MPPT) unit and battery storage. Methods. The DSP1104 is then used to experimentally implement this MPPT algorithm for real-time driving. The obtained results show the high precision of the proposed FLC-VPA MPPT around the optimal point compared to the conventional VPA under stable and changing meteorological conditions. Practical value. The experimental results approve the effectiveness and validity of the proposed total control system in the PV system. References 30, tables 3, figures 17. [ABSTRACT FROM AUTHOR]

Purpose: Sawdust, a by-product of wood workplaces, poses environmental contamination and reduces workspace efficiency. This research aimed at recycling sawdust from rain tree by incorporating its extracts into gelatin films to create active films with antifungal properties against Aspergillus flavus. Research method: Sawdust was extracted by microwave with various solvents and electrical powers. The extract (0, 0.25, 0.5, 1, and 2%) were then tested for A. flavus inhibition. The extract was also incorporated with gelatin for making wrapped films and tested for inhibition potential on garlic inoculated with A. flavus. Findings: The optimal microwave extraction condition utilized a solvent mixture comprising distilled water and 95% ethanol in a 1:1 v/v ratio, applying 100 watts of electrical power for 30 seconds, repeated 5 times. This method yielded 23.26 mg/g of tannin. Furthermore, the 2% concentration of the extract significantly inhibited both mycelium growth and spore germination of A. flavus (P<0.05) when tested on a petri dish. Additionally, incorporating 2% of the crude extract into gelatin film resulted in the most favorable outcome. This treatment demonstrated the capability to prolong the shelf life of wounded-inoculated garlic for more than 12 days. Research limitations: No limitations were found. Originality/Value: Sawdust originating from a rain tree can be recycled biodegrable actine gelatin films against A. flavus, a field-bomepathogen in garlic. [ABSTRACT FROM AUTHOR]

The reliable operation of electrical power transmission systems is crucial for ensuring consumer's stable and uninterrupted electricity supply. Faults in electrical power transmission systems can lead to significant disruptions, economic losses, and potential safety hazards. A protective approach is essential for transmission lines to guard against faults caused by natural disturbances, short circuits, and open circuit issues. This study employs an advanced artificial neural network methodology for fault detection and classification, specifically distinguishing between single-phase fault and fault between all three phases and three-phase symmetrical fault. For fault data creation and analysis, we utilized a collection of line currents and voltages for different fault conditions, modelled in the MATLAB environment. Different fault scenarios with varied parameters are simulated to assess the applied method's detection ability. We analyzed the signal data time series analysis based on phase line current and phase line voltage. We employed SMOTE-based data oversampling to balance the dataset. Subsequently, we developed four advanced machine-learning models and one deep-learning model using signal data from line currents and voltage faults. We have proposed an optimized novel glassbox Explainable Boosting (EB) approach for fault detection. The proposed EB method incorporates the strengths of boosting and interpretable tree models. Simulation results affirm the high-efficiency scores of 99% in detecting and categorizing faults on transmission lines compared to traditional fault detection state-of-the-art methods. We conducted hyperparameter optimization and k-fold validations to enhance fault detection performance and validate our approach. We evaluated the computational complexity of fault detection models and augmented it with eXplainable Artificial Intelligence (XAI) analysis to illuminate the decision-making process of the proposed model for fault detection. Our proposed research presents a scalable and adaptable method for advancing smart grid technology, paving the way for more secure and efficient electrical power transmission systems. [ABSTRACT FROM AUTHOR]

Thermoelectric effects refer to the voltage generation from temperature gradients in condensed matter. Although various power generators are made from them, all the known effects, such as Seebeck effect, require macroscopic temperature gradients; since the sign of the generated voltage is reversed by reversing the temperature gradient, the net voltage disappears when the temperature distribution fluctuates temporarily or spatially with a macroscopic temperature gradient of zero. It is impossible to utilize such temperature fluctuations in the conventional thermoelectric effects, a situation which limits their application. Here we report the observation of a second-order nonlinear thermoelectric effect; we develop a method to measure nonlinear thermoelectricity and observe that a superconducting MoGe film on Y3Fe5O12 generates a voltage proportional to the square of the applied temperature gradient. The nonlinear thermoelectric generation demonstrated here provides a way for making power generators that produce electric power from temperature fluctuations. A second-order nonlinear thermoelectric effect can be used for making power generators using temperature fluctuations. Here, the authors report that a MoGe film on Y3Fe5O12 generates a voltage proportional to the square of the temperature gradient. [ABSTRACT FROM AUTHOR]

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The active power losses are dependent on the flowing electric power value through overhead and cable lines. The current flow through the conductor causes negative phenomena to occur, such as released heat. The source of the current harmonics is the non-linear loads. Hence, the skin effect occurs, and the current carrying capacity of cables is reduced. This results in the increase in and uneven distribution of the temperature inside the conductor. This paper presents a comparison of the temperature distribution inside a power cable for an ideal 50 Hz sine wave and highly distorted current (T H D I = 41 %) . The calculated active power losses for the IEC 60287-1-1:2006+A1:2014 standard and the method described in the literature were used as a basis for further calculations. The obtained results revealed the problem of the uneven distribution of the conductor temperature. Considering the skin effect, increasing the temperature in the outer layers leads to severe damage and faster insulation aging. The abovementioned phenomenon is a decrease in the permissible load capacity of the conductor. The table given in the IEC 60364-5-52 standard summarizes the percentage contribution of the third harmonic to the current waveform. For percentages between 15% and 33%, the current carrying capacity is reduced by up to 86% of the full-load current rating. In addition, consideration of thermal conditions forces the use of cables with larger cross-sections. This leads to their non-optimal use and makes the investment more expensive from an economic point of view. [ABSTRACT FROM AUTHOR]

The widespread use of static converters for controlling electrical machines and the concern for electrical power quality in industrial environments provide an opportunity for utilizing these devices to enhance the power quality. In this context, this work presents a back-to-back converter model for driving induction machines. The converter is designed to correct the power factor of the point common coupling (PCC), compensate for harmonic currents (acting as an active filter), and withstand voltage sags. The necessary control system models were developed, and an alternative implementation for these functions in the converter was proposed. The results demonstrate the technical feasibility of this solution, as the converter operated within its nominal limits by compensating for harmonics and reactive power. Moreover, the equipment showed resilience to severe voltage sags. The contribution of this paper focuses on the multifunctionality of the frequency converter for driving induction machines. It emphasizes the advantage of the inverter in improving power quality in industrial environments through reactive power compensation and harmonic current compensation, thus functioning as an active power filter. Additionally, it is worth highlighting its ability to handle voltage dips. In this regard, this paper contributes by providing an operational strategy for driving the induction machine during such transients. [ABSTRACT FROM AUTHOR]

With the higher penetration of intermittent renewable energy sources in the electric power grid, more flexibility is needed to cope with challenges related to stability and reliability. Consumers can be part of the solution through demand response, for example, by investing in residential batteries that can charge and discharge based on price signals (implicit flexibility) or externally controlled based on grid-related needs (explicit flexibility). In this study, we investigate the feasibility of deploying residential batteries through a case study consisting of 20 households located in south-eastern Norway. The potential annual savings from implicit flexibility are optimized based on the retail electricity price, a power-based tariff, and potential revenues by selling electricity to the grid. Real historical price and consumption data with hourly resolutions from the entire year of 2022 are used as input for the optimization, yielding a theoretical profit potential. Based on this, profitability analyses are performed. The results show that the battery investments will not reach an economic break-even point during their lifetime under today's electricity price conditions. However, future developments in profit increase from implicit flexibility, substantial investment support, or additional revenues from emerging flexibility markets could make the investment economically attractive for a regular consumer. [ABSTRACT FROM AUTHOR]

The paper addresses rare issue in cable ampacity calculations, namely the presence of discontinuities along the routes. One which occurs in almost all cable installations is the presence of joints. In a standard cable rating analysis, the joints are ignored, mostly because of difficulties in building analytical models that represent the heat transfer phenomena within them. However, they can be a limiting part of the cable rating and, therefore, there is a need to model them correctly. This paper introduces an analytical algorithm for cable rating calculations in the presence of discontinuities with an emphasis on cable joints. New developments are illustrated by several numerical examples. [ABSTRACT FROM AUTHOR]

The growing demand for high-power DC fast-charging (DCFC) stations for electric vehicles (EVs) is expected to lead to increased peak power demand and a reduction in grid power quality. To maximize the economic benefits and station utilization under practical constraints set by regulatory authorities, utilities and DCFC station operators, this study explores and provides methods for connecting DCFC stations to the grid, employing low-power interconnection rules and distributed energy resources (DERs). The system uses automotive second-life batteries (SLBs) and photovoltaic (PV) systems as energy buffer and local energy resources to support EV charging and improve the station techno-economic feasibility through load shifting and charge sustaining. The optimal sizing of the DERs and the selection of the grid interconnection topology is achieved by means of a design space exploration (DSE) and exhaustive search approach to maximize the economic benefits of the charging station and to mitigate high-power demand to the grid. Without losing generality, this study considers a 150 kW DCFC station with a range of DER sizes, grid interconnection specifications and related electricity tariffs of American Electric Power (AEP) Ohio and the Public Utility Commission of Ohio (PUCO). Various realistic scenarios and strategies are defined to account for the interconnection requirements of the grid to the DCFC with DERs. The system's techno-economic performance over a ten-year period for different scenarios is analyzed and compared using a multitude of metrics. The results of the analysis show that the the integration of DERs in DCFC stations has a positive impact on the economic value of the investment when compared to traditional installations. [ABSTRACT FROM AUTHOR]

The integration of nonconventional energy sources such as solar, wind, and fuel cells into electrical power networks introduces significant challenges in maintaining frequency stability and consistent tie-line power flows. These fluctuations can adversely affect the quality and reliability of power supplied to consumers. This paper addresses this issue by proposing a Proportional–Integral–Derivative (PID) controller optimized through a hybrid Particle Swarm Optimization–Artificial Hummingbird Algorithm (PSO-AHA) approach. The PID controller is tuned using the Integral Time Absolute Error (ITAE) as a fitness function to enhance control performance. The PSO-AHA-PID controller's effectiveness is evaluated in two networks: a two-area thermal tie-line interconnected power system (IPS) and a one-area multi-source power network incorporating thermal, solar, wind, and fuel cell sources. Comparative analyses under various operational conditions, including parameter variations and load changes, demonstrate the superior performance of the PSO-AHA-PID controller over the conventional PSO-PID controller. Statistical results indicate that in the one-area multi-source network, the PSO-AHA-PID controller achieves a 76.6% reduction in overshoot, an 88.9% reduction in undershoot, and a 97.5% reduction in settling time compared to the PSO-PID controller. In the dual-area system, the PSO-AHA-PID controller reduces the overshoot by 75.2%, reduces the undershoot by 85.7%, and improves the fall time by 71.6%. These improvements provide a robust and reliable solution for enhancing the stability of interconnected power systems in the presence of diverse and variable energy sources. [ABSTRACT FROM AUTHOR]

The study employed the water-based casting technique to prepare BST sheets, which were then combined with PDMS to BST composite sheets for wind energy harvesting. By adding 0.3–1.2 mol% Y 2 O 3 as an additive, the dielectric constant and the flexoelectric coefficient of the BST sheets were significantly enhanced. The Y 2 O 3 and BST powders were mixed to form a casting slurry with the appropriate viscosity, which was then cast into a sheet. After the sintering process, silver electrodes were coated on both surfaces of the sheet. To enhance the flexibility of the sheet, PDMS was applied to the silver-coated surfaces, creating a "sandwich structure" composite sheet. The flexoelectric properties of the composite sheets are characterized utilized the micro cantilever beam method. The energy harvesting experiments, conducted in a simulated wind tunnel environment, demonstrate that the composite sheets exhibit varying flexoelectric properties and energy conversion efficiencies, depending on their thickness. When the doping amount of Y 2 O 3 is 0.6mol%, the composite sheets with a BST layer thickness of 200 μm exhibit the highest flexoelectric coefficient of 1.1 μC/m; the composite sheets with a BST layer thickness of 100 μm exhibit the strongest current output capability of 4.2 nA. These findings indicate that the developed composite sheets could be promising for applications in renewable energy harvesting, particularly for capturing and converting wind energy into useable electrical power. [ABSTRACT FROM AUTHOR]

We introduce an enhanced light-harvesting MoS2-based nanocomposite exhibiting improved solar light induced photocurrent generation, both in solution and solid phases. The MoS2-CdS composite was synthesized via easy to achieve, cost effective, two-step solution process for the photocatalytic potassium dichromate [Cr(VI)] reduction and photocurrent generation in thin-film optoelectronic devices. Incorporating 10 wt% MoS2 into the composite increased the degradation efficiency of CdS from 43.9 to 91.9%. Furthermore, the MoS2-CdS composite demonstrated a 2.88-fold increase in the degradation rate constant and a 2.15% enhancement in the apparent quantum yield compared to controlled CdS. Additionally, the electrical power consumption per order decrease in Cr(VI) reduced from 25.74 kWh m−3 for controlled CdS to 9 kWh m−3 aimed at 10 wt% MoS2-CdS composite, indicating optimal synergy between the counterparts of MoS2-CdS in its composite. The resulting thin-film device with 10 wt% MoS2-CdS exhibited robust photocurrent generation and nonlinear I–V characteristics under solar illumination, attributed to the unique electronic properties of the MoS2-CdS heterojunction, influencing carrier transport via band alignment and interface carrier trapping effects. Moreover, photocurrent generation increased linearly with illumination intensity, and dynamic photo response studies revealed rapid photocurrent generation under illumination. Furthermore, the optoelectronic key parameters of CdS, including photosensitivity, photoresponsivity, and detectivity, were enhanced by factors of 5.09, 3.33, and 12.3, respectively, upon composite formation with MoS2. This study offers novel insights into developing high-performance and cost-effective bimetallic sulfide photocatalysts for efficient solar light-induced photocurrent generation in both solution and solid phases. [ABSTRACT FROM AUTHOR]

The virtual synchronous generator (VSG) has been widely used to improve the system inertia and damping in the renewable energy generation system. However, the in-depth understanding of VSG's stability under disturbances on different control parameters is lacked. In order to solve the problem, the small-signal model of single-VSG is established at first. The influences of key control parameters on the stability of system are analyzed by using the eigenvalue analysis method in detail. On this basis, a novel optimization strategy for control parameters is proposed based on the Particle Swarm Optimization (PSO) algorithm. The control parameters are optimized to realize excellent damping and stability of VSG system. Finally, the simulation and experimental results verify the effectiveness of stability analysis and parameter optimization strategy. [ABSTRACT FROM AUTHOR]

Within a city, there is a lack of space for the installation of photovoltaic panels, especially in cities with significant artistic heritage. Hence, there is a need to identify new spaces for the installation of renewable energy systems capable of supplying part of the city's energy demand. Large infrastructures for public use such as stadiums, because of their characteristics, can become an essential resource for surrounding communities by installing photovoltaic panels on their roofs. This innovative approach can supply renewable electricity to the local community, aligning with the concept of renewable energy communities (RECs). This study focuses on the Olympic Stadium in Rome, exploring a new way to produce and share the electricity generated. An energy simulation of the photovoltaic plant was carried out by means of a transient calculation tool System Advisor Model (SAM). Then, the energy output from photovoltaics was correlated with the stadium, streetlight, and household electrical energy demands. The results highlight the suitability of the photovoltaic plant and the energy, economic, and environmental advantages derived from its exploitation. [ABSTRACT FROM AUTHOR]

The stability of the operation of the power system is essential to ensure a continuous supply of electricity to meet the load of the system. In the operational process, voltage stability (VS) should be recognized and predicted as a basic requirement. In electrical systems, deep learning and machine learning algorithms have found widespread applications. These algorithms can learn from previous data to detect and predict future scenarios of potential instability. This study introduces long short-term memory (LSTM) technology to predict the stability of the nominal voltage of the power system. Based on the results, the recommended LSTM technology achieved the highest accuracy target of 99.5%. In addition, the LSTM model outperforms other machine learning (ML) and deep learning techniques, i.e., support vector machines (SVMs), Naive Bayes (NB), and convolutional neural networks (CNNs), when comparing the accuracy of the VS forecast. The results show that the LSTM method is useful to predict the voltage of an electrical system. The IEEE 33-bus system indicates that the recommended approach can rapidly and precisely verify the system stability category. Furthermore, the proposed method outperforms conventional assessment methods that rely on shallow learning. [ABSTRACT FROM AUTHOR]

In this paper, a new linear-based closed-loop control method for a Solid-State Transformer (SST) has been proposed. In this new control method, individual current and voltage loops for each of the power conversion stages (AC-DC, DC-DC, DC-AC) are implemented. The feedback between the input and output control signals for each loop is achieved through the voltage on the DC link capacitors and the current transferred between the converters. This enables the SST to be controlled easily in a linear-based closed-loop manner without the need for complex computations. In order to evaluate the performance analysis of the proposed control system, a simulation of an SST with approximately 10 kVA apparent power was performed. Based on the obtained simulation results, the response time of the proposed control method for dynamic load variations was proved to be in the range of 40 milliseconds, and it has been observed that this method allows electrical power to be transferred from the load to the grid. The power factor value of SST under inductive load is measured to be approximately 99%, and the overall system efficiency is 96% and above, indicating that this proposed new control method has very high performance. [ABSTRACT FROM AUTHOR]

A grid-forming voltage source converter with an integrated step-down transformer could be a promising solution for supplying low-voltage alternating current loads from a medium-voltage direct current supply. However, it may require a control system that gathers feedback signals from both the primary and secondary sides of the transformer, which in turn complicates the derivation of a standard form linear model. The absence of such a model complicates control tuning, as well as the assessment of dynamics and stability of the converter system. The objective of this paper is to address this gap in knowledge. For the case study, a conventional H-bridge converter with a step-down transformer and an α β -frame dual-loop grid-forming controller is considered. Initially, comprehensive guidelines on deriving a standard form linear model for this converter system are presented. Then, the impact of controlling the VSC in a d q frame and the changes in the transformer vector group on the small-signal model of the VSC are analyzed. The aspects of control tuning are also discussed in detail, and the model's accuracy and efficacy are validated both theoretically and through control hardware-in-the-loop (C-HIL) tests using a Typhoon HIL setup. [ABSTRACT FROM AUTHOR]

This paper proposes a new DC–DC bipolar resonance converter that combines a dual‐active‐bridge and a multi‐port resonance Buck‐Boost converter. This structure uses a resonance network between the input and output ports, which has the following advantages: it creates a constant current supply in the open‐loop mode; it keeps the current phase of the output ports constant under different loads; and it allows reversing the power from any output port by adjusting the phase shift of its switches, if the converter is connected to a DC microgrid. In this way, power can be exchanged among each of the output ports and input ports. The advantages of this converter are bidirectional power exchange, power exchange between output ports, soft switching, high efficiency, integration of transformer parasitic elements, and the modular capability to connect multiple resources at the input. Furthermore, the proposed structure of the bipolar converter has been implemented for verification purposes, and its results are presented in three modes: open loop, voltage control, and current control. Additionally, the results of different modes of power sharing and their bidirectionally are shown. [ABSTRACT FROM AUTHOR]

The power frequency electric field is the most important electromagnetic environmental factor in alternating current power transmission projects. The humidity has a negative influence on available electric field measuring devices, which may lead to discrepancies of up to seven times the actual value at a relative humidity exceeding 80%. The changes in the support and probe shell impedance may be the reason for the error. The optimization measures include modifying the communication mode, designing a suitable structure and circuit for the probe, and using composite insulating material with strong hydrophobicity for the support. A three‐axis omnidirectional electric field measuring device was developed based on wireless communication and composite support. The variation of the measured electric field strength value is less than 1% at relative humidities ranging from 45% to 90% in the laboratory, and the measured results obtained in high humidity at the high‐voltage test site and under the transmission line demonstrated high accuracy. The research demonstrates that the composite support can be used to improve the performance of conventional devices. The proposed device can better meet the needs for accurate measurement of electric field strength in a high‐humidity environment and overcome the technical problems raised by the IEC standard. [ABSTRACT FROM AUTHOR]

Context: This study primarily investigates the changes in carbon adsorption capacity and hydrogen adsorption capacity on the anode catalyst surface when using methane fuel and mixed gas fuel as the anode fuel for SOFC systems. To reduce the carbon adsorption capacity of the commonly used anode catalyst—nickel-based catalysts—towards hydrocarbon fuels, copper and gold are doped into the nickel-based catalysts to compare the effects on carbon and hydrogen adsorption capacities. Moreover, aside from calculating the carbon and hydrogen adsorption capacities, this project also evaluates the impact of mixed gas effects and doping effects on SOFC performance through the analysis of hydrogen diffusion coefficients and performance polarization curves. The findings reveal a noteworthy enhancement in the diffusion coefficient of syngas within the Au-doped Ni catalyst, showing an improvement of up to 45.46% at 973 K. Furthermore, the electrical power generated by syngas in the Au-doped Ni catalyst at 973 K demonstrates an increase of up to 12.06%. Methods: This study primarily employs DFT to calculate the carbon and hydrogen adsorption energies on methane, utilizing CASTEP for the calculations. During these calculations, the adsorption energy is determined through a three-layer surface approach, in conjunction with the Kohn–Sham equations, combining the Generalized Gradient Approximation and ultrasoft pseudopotentials for TS-search calculations. On the other hand, this project will analyze the diffusion coefficient of hydrogen on the anode catalyst using MD methods combined with the ReaxFF potential field, with GULP being utilized to complete all dynamics calculation theories. Finally, the project will analyze the performance of SOFC cells, incorporating relevant numerical equations with Matlab for numerical analysis. [ABSTRACT FROM AUTHOR]

To minimize total operating costs, emissions, and power losses, the optimum power generation and scheduling of renewable integrated hydro-thermal systems are one of the most significant objectives in short-term scheduling. The solution to these problems becomes more difficult with constraints and renewable uncertainties. The paper presents an improved cheetah optimizer (ICO) for solving the optimum wind-solar-hydro-thermal scheduling problem considering valve loading effects, ramp-rate limits, power loss, and prohibited operational zone constraints. The main objective is to optimize the total fuel cost and emissions for thermal power generators, where electric power can be fully harnessed from renewable generators. Different test systems are employed to evaluate the proposed ICO solution method's performance. The proposed ICO solution method is compared with other algorithms like grey wolf optimizer, and particle swarm optimizer, in terms of optimal fuel costs, emissions, convergence success rate, and computation time. The test systems are incorporated with wind farms, solar farm, hydropower generators, and thermal power generators scheduled for 24-h, 1-h subintervals. The simulation solutions of the renewable integrated system have been acquired by ICO, CO, GWO, and PSO. The total generation cost obtained by ICO is 0.0698%, and 0.1514% lower than the cost obtained by GWO, and PSO respectively. The total power loss was minimized by 1.8554% and 7.4002%. The total emissions can be reduced to 25% with increasing penetration of renewable energy sources. It is realized from the comparison that the proposed ICO method has the potential to provide better-quality solutions. [ABSTRACT FROM AUTHOR]

The electrical power system (EPS) has been heavily stressed due to high load demand. It operates close to the total capacity limits, resulting in voltage instability that can lead to voltage collapse. In this regard, incorporating flexible alternating current transmission system (FACTS) devices and renewable energy sources (RESs) to obtain the optimum values of the generator voltage, reactive compensation, and transformer tab in optimal reactive power dispatch (ORPD) is essential in increasing the reliability and safety of the system. ORPD involves discrete and continuous variables, which are nonlinear, noncontinuous, non-convex, and complex problems. The objective functions of ORPD are reduction in active power loss (Ploss), voltage deviation, and voltage profile enhancement. This paper presents a recent advancement of the ORPD problem, mathematical formulation of the objectives function, and a summary of various metaheuristic optimization methods (single and hybrid) used to solve the ORPD problems. The hybrid method combines two or more methods to improve the demerits of one method to obtain a quality solution to a problem. This review covered incorporating FACTS devices and RESs used in solving the ORPD problem to reduce the active Ploss and improve the voltage profile in the EPS. The benefits of FACTS devices and RESs are also discussed. Also, various metaheuristic algorithms (single, modified, and hybrid) employed to solve the ORPD problem were discussed. The future direction for researchers in this field was provided to give insight into the applicability and performance. Overall, this research explores different techniques used in solving ORPD problems from the optimization point of view to incorporating RESs and FACTS devices to obtain quality solutions. Some existing methods do not guarantee an optimum solution, but incorporating RESs and FACTS devices will help attain the best solution to the problem for better power system operation to improve system reliability and voltage profile. Based on the review journal, it can be concluded that hybrid techniques offer efficient quality solutions to the ORPD problem. [ABSTRACT FROM AUTHOR]

Energy harvesting from external Ultra-low frequency vibrations is currently attracting a lot of attention. However, for the same system, it is difficult to satisfy the need for more efficient energy harvesting in a variety of external environments. Accordingly, an adjustable gearing device connected to the energy harvesting system is used herein for adapting energy harvesting to a wide range of external environments. The device uses four symmetrical inclined springs. One end of the springs is connected to a gear and the other end to a mass element. The geometrical parameters of the system can be varied by rotating the gears, thus varying the dynamic stiffness of the system. The kinetic equations of the system are derived and their nonlinear terms are Taylor-expanded. The amplitude-frequency response curve of the system is obtained by solving using the harmonic balance method. Multi-color plots of RMS values of induced voltage and electric power are obtained using the fourth-order Runge-Kutta method. The results show that the device has excellent adjustable performance. Adjusting the rotation angle of the gears can change the soft and hard characteristics of the system's dynamic stiffness and the intrinsic frequency, thus improving the system's energy harvesting performance in different environments. [Display omitted] • An energy harvesting system using a gear unit for regulation is proposed. • The natural frequency of the system is varied by changing the angle of the gears. • The nonlinear form of the system is adjusted by changing the angle of the gears. • The potential energy of the system is adjusted by changing the angle of the gears. • The RMS value of the system is used to analyze its energy harvesting efficiency. [ABSTRACT FROM AUTHOR]

The smart grid is a promising solution for modernizing electrical power systems in a digital world. However, cybersecurity threats pose significant risks to the grid's integrity and resilience. False Data Injection Attacks (FDIA) have shown serious risks to disrupt the power system infrastructure. SHASARIMAX is a novel framework designed to address these challenges by combining distinct elements of Secure Hash Algorithm-256 (SHA256) and SARIMAX. Cryptographic hashing techniques and advanced modelling of SHA-SARIMAX actively detect and recover corrupted values in time series datasets affected by FDIA. This approach detects and recovers corrupted values in time series datasets affected by FDIA, leveraging cryptographic hashing techniques and advanced modelling. The proposed framework achieves a 99.90% accuracy rate from the original corrupted data. Thus, the SHA-SARIMAX demonstrates its applicability and suitability for implementation within smart grids, specifically for addressing the recovery of original data from the corrupted data affected by FDIA. [ABSTRACT FROM AUTHOR]

This research article details the design and implementation of a nonlinear adaptive filtering (NAF) technique using an exponential functional link network (EFLN) for a shunt hybrid active power filter (SHAPF) control to solve the current-associated power quality issues on the utility side at the distribution level of electrical power systems. Separation of the fundamental component from the harmonics, achieving unity power factor operation, reducing the reactive power drawn from the source, balancing the currents during transients, and reduction of total harmonic distortion (THD) of the source current are the issues considered to resolve. The proposed technique solves these issues by generating the sinusoidal reference current and separating the fundamental current from the harmonics. When compared to conventional and existing adaptive filtering techniques such as least mean square (LMS), least mean fourth (LMF), and variable step size LMS (VSS-LMS), the proposed EFLN-NAF method excels in terms of speedy convergence, adaptability in noise-specific environments and reduced steady-state coefficient error. MATLAB/Simulink software is utilized to perform the simulations to examine the suggested strategy for the chosen SHAPF topology both in static and dynamic scenarios. For a 15 kW and 3kVAr requirement of the nonlinear load, simulation results proved that the designed PPF for 2kVAr is able to share the reactive power with the APF, thereby reducing its rating and cost. The proposed method of filtering has been proven to be fast converging with 0.049 s, and the THD in steady state is brought to 1.32 % in steady-state and to 3.77 % during transient conditions, which are under standard limits. A hardware prototype of the experimental setup is constructed at the laboratory scale with OPAL-RT (OP4510) as the controller. With an active and reactive power demand of 1.1 kW and 210VAr, the designed PPF supplies 110 VAr, whereas the rest is supplied by the APF. The practical THD in source current is observed to be 2.081 %, which meets the standards. The results from both simulations and experiments are validated, and the efficacy of the proposed technique in mitigating the aforementioned power quality issues is proved. [Display omitted] • A passive power filter design to share the reactive power requirement in addition to mitigating the predominant harmonics of the 5th and 7th order. • A robust nonlinear adaptive filter implementation based on exponential functional link network (EFLN-NAF) algorithm to the shunt hybrid active power filter (SHAPF) control for reference current generation and fundamental component separation from harmonics. • Solution for current-associated power quality issues such as reducing the reactive power burden, achieving unity power factor operation, and mitigating the harmonics, thereby reducing the source current THD value. • Simulation of the proposed technique for the control of shunt hybrid active power filter and evaluation of the outcomes for resolving the power quality issues in both steady-state and dynamic conditions. • Development of a hardware prototype at a laboratory scale using OPAL-RT (OP4510) real-time simulator as a controller for the proposed technique for the control of SHAPF and evaluation of the outcomes. [ABSTRACT FROM AUTHOR]

An electrical motors, together with its appropriate drive system, is one of the most important elements of electromobility. In recent years, there has been a particular interest by academic researchers and engineers in permanent-magnet motors (PMSMs) in various applications, such as electric vehicles, Unmanned Aerial Vehicles (UAVs), elevator systems, etc., as the main source of drive transmission. Nowadays, the elevator industry, with the evolution of magnetic materials, has turned to gearless PMSMs over geared induction motors (IMs). One of the most important elements that is given special emphasis in these applications is proper motor design in consideration of the weight and speed of the chamber to be served during operation. This paper presents a design of a high-efficiency PMSM, in which finite elements analysis (FEA) and the study of the lift operating cycle provided useful conclusions on the magnetic field of the machine in different operating states. In addition, a simulated model was compared with experimental results of test operations. Furthermore, the drive system also required the use of appropriate electrical power and controls to drive the PMSM. Especially in elevator applications, the control of the motor speed by the variable voltage variable frequency technique (VVVF) is the most common technology used to avoid endangering the safety of the passengers. Thus, suitable speed and current controllers were used for this purpose. In our research, we focused on studying different control techniques using a suitable inverter to compare the system operation in each case studied. [ABSTRACT FROM AUTHOR]

Excessive cogging torque can cause torque fluctuations, noise, and vibration in electric power steering (EPS) motors, which is a key factor in the high-precision and high-performance optimization design of EPS motors for electric vehicles. This article takes a 12-slot 10-pole electric power steering motor for a certain car as an example. By establishing the corresponding electromagnetic field model and theoretical analysis of the motor, the influence of the pole arc coefficient and eccentricity parameters of the permanent magnet on the cogging torque of the electric power steering motor is explored. A comprehensive optimization scheme for reducing the cogging torque of the motor structure is proposed. The effectiveness of the designed scheme was verified through finite-element simulation and experimental testing of motor electromagnetism. Compared with the original design, the optimized structure of the EPS motor resulted in an 86.62% reduction in cogging torque during experimental testing. [ABSTRACT FROM AUTHOR]

Dual-Active-Bridge (DAB) DC–DC converters are becoming increasingly favored for their efficiency in transferring electrical power across varying voltage levels. They are crucial in enhancing safety and reliability in various fields, such as renewable energy systems, electric vehicles, and the power supplies of electronic devices. This paper introduces a new control strategy for bidirectional isolated DAB DC–DC converters, implementing a Double Integral Super Twisting Sliding Mode Control (DI-STSMC) to accurately regulate the output voltage and current. The approach starts with a state-space representation to mathematically model the DAB converter. In light of model uncertainties and external disturbances, a robust DI-STSMC controller has been formulated to optimize the DAB converter's output performance. This method achieves zero steady-state error without chattering and provides a quick response to fluctuations in load and reference changes. The validity of the proposed technique is demonstrated through simulation results and a control hardware-in-the-loop (CHIL) experimental setup, using Typhoon HIL 606 and Imperix B-Box RCP 3.0 on a 230 W DAB converter. Furthermore, the paper offers a comparative analysis of the DI-STSMC with other control strategies, such as the proportional-integral (PI) controller, standard sliding mode control (SMC), and integral sliding mode control (ISMC). [ABSTRACT FROM AUTHOR]

This paper presents the design of a digital twin for a 6U CubeSat electrical power system, including the solar arrays, solar array regulators, battery, power distribution unit, and load subsystems. The digital twin is validated by comparing its real-time outputs with those of the physical system. Experimental tests confirm its feasibility, showing that the digital twin's real-time outputs closely match those of the physical system. Additionally, the digital twin can be used for control-hardware-in-the-loop and power-hardware-in-the-loop tests, allowing the real-time integration of simulated subsystems with hardware. This capability facilitates testing of new subsystems and optimization during the project's development phases. Additionally, to demonstrate the advanced capabilities of this model, the digital twin is used to simulate the CubeSat electrical power system behavior in real time throughout a complete orbital cycle in low Earth orbit conditions. This simulation provides valuable insights into the CubeSat operation by capturing the transient and steady-state responses of the EPS components under real orbital conditions. The results obtained indicate that the digital twin significantly enhances the testing and optimization process of new subsystems during the development phases of the project. Moreover, the capabilities of the digital twin can be further augmented by incorporating real-time telemetry data from the CubeSat, resulting in a highly accurate replication of the satellite's in-orbit behavior. This approach is crucial for identifying and diagnosing failures or malfunctions in the electrical power system, ensuring the robust and reliable operation of the CubeSat. [ABSTRACT FROM AUTHOR]