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The uninterrupted power supply (UPS) plays a dominant role in domestic appliances and also the growth rate of solar roof top system implementation is massively increasing day by day. To minimize the cost on the converters, solar PV power is directly connected with existing UPS with separate MPPT controller. However, due to the presence of nominal frequency transformer, the size and cost of UPS becomes more. In addition, it consumes the power with poor power quality to charge the battery. Apart this, the current supplied from the battery is much higher due to the lower voltage level of battery, which makes voltage dip during peak load condition and resulting to shorten the battery life and degrades its performances. In order to overcome all these drawbacks, this particular paper proposes a transformer-less novel hybrid converter based solar PV fed UPS system. In the hybrid structure, the gain can be achieved higher with minimum components counts. The novelty of the proposed transformer-less hybrid converter is that the regeneration of switched capacitor voltage is applied to input of switched inductor network in DC–DC converter, due to this hybrid structure the gain has been extended drastically with minimum number of devices. Also the coordinated control algorithm is implemented in solar PV fed UPS to take the decision according to the situation of generation, load and battery back-up. The detailed operation of the proposed coordinated control algorithm has been addressed in this paper. Moreover, the detailed simulation study is carried out for each mode of operation and measured results are obtained and presented in this paper. [ABSTRACT FROM AUTHOR]

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Nowadays, the application of industrial robots in manufacturing is widespread to automatize tedious and repeatable precision-sensitive processes. Modern robotic cells compete with the human workforce and specialized industrial machines in general efficiency. Additionally, robotic cells can be typically reprogrammed for different tasks, thus providing flexible applications, especially compared to more traditional methods. Advanced autonomous and intelligent capabilities are widespread in modern robotic systems, supplying quantitative factors like higher availability, fault tolerance, precision, and system flexibility. Robotic systems typically work measurably more efficiently regarding resource usage, electrical power, and waste than other industrial production line systems. New intelligent and interconnected methods (e.g., cooperative robotics, big data analysis, cyber-physical systems) contribute further to the operation efficiency. Recently, sustainability has become a significant question in robotics: modern technical society faces problems such as decreasing availability of natural resources, workforce scarcity, and environmental challenges. This work focuses on industrial robotic systems as a primary pillar for sustainability efforts in numerous production sectors, such as metallurgy, assembly lines, and construction. This paper aims to review and analyze possible sustainability indicators of the industrial applications of robotics. Based on the analysis, the paper presents a manufacturing process model with industrial robots that considers sustainability indicators. This model highlights the relationship between industrial robotization and sustainability from a quantitative and qualitative perspective. The model indicates that energy efficiency and data interconnectivity play a crucial role in the sustainability of industrial processes. The aim of the model is to help identify indicators playing a role in the sustainability of industrial robot-based manufacturing lifecycle and maintenance. [ABSTRACT FROM AUTHOR]

Traditionally, reading of energy meters is done by human operators who move from house to house collecting readings. This exercise requires huge labor operator numbers and a lot of time to achieve complete reading of meters in a particular area. This paper endeavors to do away with this problem by using a telemetering system. With this system, power can be measured from a remote site. To achieve this, readings from an energy meter on site are processed by a microcontroller device that then sends the energy consumption information to a Global System Mobile (GSM) module. The GSM module then sends this information using microwaves to a particular mobile subscriber who receives it in the form of an Short Message Service (SMS). The reading is also transmitted to a web based telemetering system through a server. In the remote site, a remote computer which can access the internet is able to obtain data from the server through the internet. The microcontroller is developed in such a way that it achieves communication between the energy meter and the particular server using Transmission Control Protocol(TCP) protocol. Software programs are also developed to facilitate transfer of data to the user at remote site. With the web based telemetering system connected to the internet, electrical energy measurements can be accessed globally. The efficiency of the transmission channel is important for the success of both SMS and web based telemetering systems. [ABSTRACT FROM AUTHOR]

In recent years, Microgrids in integration with Distributed Energy Resources (DERs) are playing as one of the key models for resolving the current energy problem by offering sustainable and clean electricity. Selecting the best DER cost and corresponding energy storage size is essential for the reliable, cost-effective, and efficient operation of the electric power system. In this paper, the real-time load data of Bengaluru city (Karnataka, India) for different seasons is taken for optimization of a grid-connected DERs-based Microgrid system. This paper presents an optimal sizing of the battery, minimum operating cost and, reduction in battery charging cost to meet the overall load demand. The optimization and analysis are done using meta-heuristic, Artificial Intelligence (AI), and Ensemble Learning-based techniques such as Particle Swarm Optimization (PSO), Artificial Neural Network (ANN), and Random Forest (RF) model for different seasons i.e., winter, spring & autumn, summer and monsoon considering three different cases. The outcome shows that the ensemble learning-based Random Forest (RF) model gives maximum savings as compared to other optimization techniques. [ABSTRACT FROM AUTHOR]

During photovoltaic (PV) conversion in solar panels, a part of the solar radiation is not converted to electricity by the cells, producing heat that could increase their temperature. This increase in temperature deteriorates the performance of the PV panel. In this paper, a hybrid PV/thermal (PV/T) water system is proposed to mitigate this problem. This system combines a PV panel and a thermal collector. In this paper, we focused on the modeling and control of this hybrid system in the linear parameter varying (LPV) framework. An optimal linear quadratic regulator (LQR) is proposed to control the PV cell temperature around an optimal value that maximises electricity generation. Since the system model is nonlinear, an optimal LQR gain-scheduling state-feedback control approach based on an LPV representation of the nonlinear model is designed using the Linear Matrix Inequality (LMI) method. The goal is to obtain the maximum electrical power for each solar panel. Since a reduced number of sensors is available, an LPV Kalman filter is also proposed to estimate the system states required by the state-feedback controller. The obtained results in a laboratory setup in simulation are used to assess the proposed approach, showing promise in terms of control performance of the PV/T system. [ABSTRACT FROM AUTHOR]

A new power receiving unit (PRU) is proposed in this paper for resonant wireless power transfer (WPT), which is characterized by the capability of attracting high power from the power transmitting unit (PTU). The resonant WPT is designed for delivering the electrical power to the PRU attached on an electrical vehicle (EV) chassis 50 cm away from a PTU installed on the ground. The proposed PRU uses only the passive elements such as inductors, diodes, and capacitors, which need no initial power from the EV. It is then applicable for charging a battery to several hundred volts for even a first-time charging battery. For a resonant WPT at a switching frequency of 4 MHz, the proposed PRU behaves as a negative impedance converter (NIC) itself in the subharmonics of 4 MHz. The NIC effect plus the subharmonic oscillation causes an instability current charging the battery connected to the PRU. In this paper, we simulated the PRU and performed the experiment. The experiment demonstrated a battery charging of 150 W from 50 cm away using three D-mode GaN HEMT transistors via the instability current ramp. The power transfer efficiency (PTE) improved as the power delivered to the load (PDL) increased. The peak PTE was 65% in the present findings. The simulation analysis showed that the circuit allowed itself be used to much higher power transfer when it is implemented with more GaN HEMT transistors connected in parallel. The theoretical derivation of the PRU circuit is also used to support both the experimental and simulation results. [ABSTRACT FROM AUTHOR]

In this paper, the object of the research is 110 kV power grids of three regions of the Republic of Kazakhstan: Astana city, Turkestan region and Shymkent city, as well as West Kazakhstan region. Operators of the studied power grids have no idea about the real levels of voltage and current sinusoidality distortion coefficients, as well as about their relationship with other regime and system parameters of power grids. Similar problems may be faced by other grid companies that do not have the appropriate information and measurement infrastructure to monitor the modes of power grids in terms of voltage and current sinusoidality distortion. In the course of the present study, using portable three-phase power quantity and quality analyzers, it was possible to make daily measurements of mode parameters in 41 110 kV transmission lines with a length of 5 to 120 km. The results of measurements showed that in Astana city, the voltage quality is at a satisfactory level, but the distortion coefficient of sinusoidality of current reaches 39 % (the average level for 15 studied lines is 13.3 %) due to the high concentration of non-linear load of consumers. In the South of Kazakhstan, the voltage and current sinusoidality distortion coefficients are relatively moderate, but voltage drops are frequent (sometimes up to 10 % or more) due to the large distance between load centers and relatively high population density. In the power grids of Western Kazakhstan, voltage and current sinusoidality distortion coefficients have high levels (reach 14 % and 70 %, respectively) due to low network load with a large length of transmission lines. The analysis makes it possible to trace the relationship of voltage and current sinusoidality distortion coefficients with such regional characteristics as population density, nature of loads, power losses, voltage and current levels. [ABSTRACT FROM AUTHOR]

Most of countries around the world tends to increases the penetration of renewable energies generation in electrical power networks. This led to the emergence of many challenges in these systems, such as congestion of lines, voltage instability, etc. The most important of these problems is the spillage of renewable energies in order to maintain the stability of the power system. However, by using the traditional methods to mitigate the spillage, the stability of the power system may be deteriorated leading to a vulnerable power system against disturbances. This paper proposes a bilevel multi-objective Musical Chairs optimization algorithm for optimal allocation of multi-type flexible AC transmission system (FACTS) devices. The main target of the upper-level is to reduce the wind power spillage with minimize the investment cost of FACTS devices and load shedding, while maximize the voltage stability. Moreover, under different operating scenarios, the lower-level problem captured the market clearing with maintain the system constraints for maximize the social welfare. This leads to a robust and economical operating point where included enough levels of voltage security. The technique proposed in this paper is tested on the IEEE 24-bus modified reliability test system. The results show that the applicability of the proposed algorithm in aiding power system improvement planning for minimizing wind power spillage to integrate wind energy with maximizing the social welfare and improving the loadability and the voltage stability. [ABSTRACT FROM AUTHOR]

This paper presents the development of an Air‐Cored Axial Flux Permanent Magnet Generator (ACAF PMG) integrated for direct battery charging scheme for urban and rural micro‐wind turbine applications rated at 1 kW. The proposed generator has a Single Stator Double Rotor configuration with a relatively short axial length. In this paper, the analytical model for generator sizing is presented and the main parameters are defined. Novel analytical model is presented to determine the required number of turns for each phase in order to produce a balanced voltage in the three phases. The generator is electromagnetically analyzed using Finite Element model and simulated using Matlab/Simulink to predict its performance under several operating conditions. The effect of retainment ring type on the generator performance is also demonstrated. The machine is harnessed to a battery bank via a three‐phase fully controlled converter using six bridge thyristors to regulate the output voltage delivered from the generator to the battery. Generator model and simulation results are validated via experimental tests. The preliminary experimental results showed a good match with the simulation results. Moreover, the proposed machine is compared favourably with other counter machines of similar configuration and power ratings in terms of machine size, power‐to‐weight ratio, and voltage regulation. This paper therefore demonstrates the concrete benefits of utilizing the axial flux PMG in scavenging energy to generate electrical power from micro wind turbines. [ABSTRACT FROM AUTHOR]

As urbanization increases, streetlights have become significant consumers of electrical power, making it imperative to develop effective control methods for sustainability. This paper offers a comprehensive review on control methods of smart streetlight systems, setting itself apart by introducing a novel light scheme framework that provides a structured classification of various light control patterns, thus filling an existing gap in the literature. Unlike previous studies, this work dives into the technical specifics of individual research papers and methodologies, ranging from basic to advanced control methods like computer vision and deep learning, while also assessing the energy consumption associated with each approach. Additionally, the paper expands the discussion to explore alternative functionalities for streetlights, such as serving as communication networks, environmental monitors, and electric vehicle charging stations. This multidisciplinary research aims to be a pivotal resource for both academics and industry professionals, laying the groundwork for future innovation and sustainable solutions in urban lighting. [ABSTRACT FROM AUTHOR]

This paper presents an extensive review of the most effective and modern monitoring methods for electrical power lines, with particular attention to high-voltage (HV) and medium-voltage (MV) systems. From a general point of view, the main objective of these techniques is to prevent catastrophic failures by detecting the partial damage or deterioration of components and allowing maintenance operations to be organized. In fact, the protection devices commonly used in transmission and distribution networks guarantee the location of faults, such as short-circuits, putting the non-functioning branch of the network out of service. Nowadays, alongside these devices, it is possible to introduce new intelligent algorithms capable of avoiding the total loss of functionality, thus improving the reliability of the entire network. This is one of the main challenges in modern smart grids, which are characterized by the massive integration of renewable energy sources and a high level of complexity. Therefore, in the first part of this paper, a general overview of the most common protection devices is proposed, followed by an analysis of the most modern prevention algorithms. In the first case, the coordination of the relays plays a fundamental role in obtaining the fault location with a high level of selectivity, while in the field of preventive analysis, it is necessary to address the implementation of artificial intelligence methods. The techniques presented in this paper provide a comprehensive description of the different monitoring approaches currently used in distribution and transmission lines, highlighting the coordination of protection relays, the computational algorithms capable of preventing failures, and the influence of the distributed generation in their management. Therefore, this paper offers an overview of the main diagnostic techniques and protection devices, highlights the critical issues that can be overcome through the introduction of artificial intelligence, and describes the main prognostic methods, focusing on their invasive level and the possibility of operating directly online. This work also highlights the main guidelines for the classification and choice between the different approaches. [ABSTRACT FROM AUTHOR]

A terminal for remote control of charging stations for electric vehicles (EV) powered by renewable energy has been presented in this paper. This terminal enables remote control of EV chargers, smart batteries, smart electricity meters, fiscal cash registers (FCR), as well as remote control of renewable energy sources and other devices within the station. This terminal also makes charging stations more accessible to electric vehicles users, to electricity distribution companies, to electricity suppliers, to tax administrations, and finally to users and owners of charging stations. Therefore, communication and control with all these devices and systems is integrated in one device. Realization of hardware and software of such a terminal has also been described in this paper. The net result of development and commercialization of terminals would encourage an increase in the use of electric vehicles powered by energy from renewable sources, which would cause a decrease in the level of air pollution and all negative effects it causes in the future. Different categories of this device are considered. Moreover, although it is a device with embedded software, a very advanced method was used, that is, a model-driven development method, which enables fast and more efficient development and maintenance of the device. The results of the application of this method to the terminal for remote control of fiscal cash registers are provided. They were compared with the results of the development of the terminal for remote control of smart meters without applying this method. A simulation of the development of the terminal for remote control of the station is also provided. The presented method can be used in the future for faster and better-quality development of embedded software. [ABSTRACT FROM AUTHOR]

This paper presents a model for determining fuzzy evaluations of partial indicators of the availability of continuous systems at coal open pits using a neuro-fuzzy inference system. The system itself is a combination of fuzzy logic and artificial neural networks. The system availability is divided into partial indicators. By combining the fuzzy logic and artificial neural networks, a model is obtained that has the ability to learn and uses expert judgment for that learning. This paper deals with the ECC system (bucket wheel excavator-conveyor-crushing plant) of the open pit Drmno-Kostolac, which operates within the Electric Power Company of Serbia. The advantage of a model of this type is that it does not rely on the historical experiences of experts and usual predicted values for the fuzzy evaluation of partial indicators, which are based on the assumption that similar systems affect availability in a similar way. The fuzzy evaluation of partial indicators is based on historical data for the specific system for which the model was created. As such, it can more accurately predict continuous systems availability on the basis of expert evaluations in the appropriate time period. Another advantage of this model is that the availability is estimated on a quarterly basis, which gives a more accurate view because it uses a smaller time period with more similar characteristics and, thus, includes certain external influences which are related to the quarterly meteorological conditions. [ABSTRACT FROM AUTHOR]

Introduction: Critically ill patients require continuation of their care when receiving hyperbaric oxygen treatment. This care may be facilitated via portable electrically powered devices such as intravenous (IV) infusion pumps and syringe drivers, which may create risks in the absence of a comprehensive safety evaluation. We reviewed published safety data for IV infusion pumps and powered syringe drivers in hyperbaric environments and compared the evaluation processes to key requirements documented in safety standards and guidelines. Methods: A systematic literature review was undertaken to identify English language papers published in the last 15 years, describing the safety evaluations of IV pumps and/or syringe drivers for use in hyperbaric environments. Papers were critically assessed in relation to the requirements of international standards and safety recommendations. Results: Eight studies of IV infusion devices were identified. There were deficiencies in the published safety evaluations of IV pumps for hyperbaric use. Despite a simple, published process for evaluating new devices, and available guidelines for fire safety, only two devices had comprehensive safety assessments. Most studies focused only on whether the device functioned normally under pressure and did not consider implosion/explosion risk, fire safety, toxicity, oxygen compatibility or risk of pressure damage. Conclusions: Intravenous infusion (and other electrically powered) devices require comprehensive assessment before use under hyperbaric conditions. This would be enhanced by a publicly accessible database hosting the risk assessments. Facilities should conduct their own assessments specific to their environment and practices. [ABSTRACT FROM AUTHOR]

This paper presents a bidirectional multilevel dc–dc power converter for electric vehicle (EV) battery charging. The operating principle of the power converter was presented, analyzed, and experimentally validated under normal and fault conditions. The topology under study was integrated into a bipolar dc grid through the split dc-link of the bidirectional multilevel dc–dc power converter. Considering the failures that can occur in the bipolar dc grid, i.e., in each wire of the bipolar dc grid (positive, negative, and neutral), it was experimentally verified that the dc–dc power converter ensures that the EV battery-charging process continues, regardless of the occurrence or absence of open-circuit failures. In light of this fact, the proposed control algorithms and the presented topology were validated through a set of considerable simulation and experimental results, analyzing the distinct states of the power semiconductors, which compose the bidirectional multilevel dc–dc power converter, for distinct conditions of operation. The developed laboratory prototype of the bidirectional multilevel dc–dc power converter for EV battery charging, which was implemented to obtain the experimental results, is described in detail in this paper. The experimental validation was carried out for the main different fault conditions in the bipolar dc grid in terms of open-circuit failures and, moreover, considering the steady-state and transient-state operations of the dc–dc power converter. The experimental analysis demonstrated that even in the presence of failures in the positive, negative, or neutral wires of the bipolar dc grid, the bidirectional multilevel dc–dc power converter guarantees the correct EV battery-charging operation. [ABSTRACT FROM AUTHOR]

The energy crisis is a problem that countries all over the world pay more and more attention to, and a series of ecological problems caused by it have become increasingly prominent. It is difficult for traditional fossil fuels to maintain a healthy and coordinated sustainable development of society and economy. The establishment of a sustainable energy system has become the development trend of various countries to solve energy problems. Electric energy is a secondary energy that all primary energy can be converted into, and an irreplaceable consumable for all industrial technologies and people's lives. Electric power data has the characteristics of large rate span, numerous data sources, complicated interaction methods, and various types of data. The existence of abnormal data in the power system will greatly reduce the accuracy of the system state estimation and the state estimation convergence rate. This paper introduces the power grid industrial control system, combines the data flow of power big data, and analyzes the abnormal information detection process in detail. It takes the data stream acquired by the acquisition unit PMU of the wide area measurement system as the research object. The rapid development of the Hadoop big data platform provides important technical support for the research of power grid big data. Based on the Hadoop platform, the clustering algorithm is used to complete the anomaly detection of real-time data. The LOF algorithm has poor performance when dealing with a large amount of high-dimensional data, and has high time and space complexity. In order to make up for the shortcomings of the LOF algorithm, this paper uses the K-means clustering algorithm to propose an improved algorithm K-LOF of the density-based local abnormal factor detection algorithm LOF, and optimizes the neighborhood query process. It is verified by experiments that the K-LOF algorithm can effectively reduce the time complexity of the anomaly detection algorithm and improve the detection accuracy by 2–4.2%. [ABSTRACT FROM AUTHOR]

Solar photovoltaic energy is a vital renewable resource because it is clean, endless, and pollution‐free. Due to the fast growth of the semiconductor and power electronics sectors, photovoltaic (PV) technologies are climbing significant attention in modern electrical power applications. Operating PV energy conversion systems at the maximum power point is essential for getting the maximum power output and raising efficiency. This paper proposes a regression‐based Perturb and Observe method to quickly find a global maximum power point, avoiding being stuck in local maxima, likewise analytical and metaheuristic methods. The improved control focuses on the narrowed search areas by linear and non‐linear regression analyses using the generated PV model on a flexible Python environment. Furthermore, the method's accuracy is validated in real time under variable temperatures, irradiations, and loads. This method was proven with a hardware implementation. The proposed method is more than 98% accurate and can withstand long‐term modelling. The suggested regression‐based perturbation and observation method provided a short learning time and easy implementation. Additionally, the dynamic recorded results can be visualized for researchers to utilize efficiently. [ABSTRACT FROM AUTHOR]

This document provides an overview of the advancements in energy harvesting technologies and their integration into the Internet of Things (IoT) and wireless sensor networks. It includes 31 papers covering various energy harvesting devices, optimization techniques, and potential applications. The research aims to improve the efficiency and sustainability of wireless sensor networks while minimizing energy consumption. The articles explore different methods of energy harvesting, such as solar, thermal, vibrational, and radio frequency energy, and discuss their application in various fields, including wearable devices, solar energy harvesting, and IoT-enabled smart meters. Overall, this collection offers a comprehensive overview of the current research and advancements in energy harvesting for sensor networks. [Extracted from the article]

Ecofuels and their feedstock come in three main product classes: electrofuels (e-Fuels), biofuels, and non-biowaste-derived fuels. Ecofuels originate from non-fossil sources, derived from circular raw materials such as non-food organic waste, renewable hydrogen, and captured CO2 through a rapid process of carbon fixation. Proposed regulation drafts under discussion indicate that new fuels would need to reach a substantial degree of climate neutrality. The manufacture of all ecofuels, however, requires energy input to accomplish the conversion of the initial feedstock; their climate neutrality claims stem from the use of renewable electric energy and/or biomasses in the production process, but fossil fuels are still the main primary sources of global (and the EU's) electric power, and most biofuels consumed in the EU transport mix are still crop-based, with potential conflicts with food and land use. Furthermore, entirely neglecting GHG emissions from renewable energy generation is scientifically debatable, as the impact of the energy (and the related GHG emissions) embedded in the materials used to build renewable energy facilities is small, but not nil. The paper reports ecofuel trends according to the above-mentioned originating technologies and discusses the issues related to their development. [ABSTRACT FROM AUTHOR]

Automatic distribution master stations (ADMSs) are software platforms that can be used to monitor energy supply and consumption of power demand-side resources as well as to guarantee grid security. They play a vital role in maintaining the optimal performance and stability of electrical power systems. However, the stability of ADMSs is usually determined by the performance of the information interaction, which includes various challenges and complexities. Therefore, an efficient multiple-indicator filtering-based information interaction evaluation method for the ADMS is proposed in this paper. The proposed method first utilizes the principal component analysis (PCA) to filter the indicators of the ADMS. Then, the data envelopment method and the analytic network process (ANP) are employed to remove the invalid indicators and to determine the indicator weights. In this regard, the secondary screening of the indicators is completed, the effective indicators are obtained, and the accuracy of the evaluation system is improved. Results of the simulation show that the proposed method works well when evaluating information interaction performance, and it offers satisfactory performance evaluation of ADMSs. [ABSTRACT FROM AUTHOR]

This paper presents a methodology to forecast electrical demand for the Chilean Electrical Power System considering a national, regional, district and bus spatial disaggregation. The methodology developed was based on different kinds of econometric models and end-use models to represent the massification of low carbon emission technologies such as electromobility, electric heating, electric water heating, and distributed generation. In addition, the methodology developed allows for the projection of the electric demand considering different kinds of clients as regulated and non-regulated clients, and different economic sectors. The model was applied to forecast the long-term electricity demand in Chile for the period 2022–2042 for 207 districts and 474 buses. The results include projections under the base case and low carbon scenarios, highlighting the significant influence of new technologies on future demand. [ABSTRACT FROM AUTHOR]

This paper proposes a new technique for a single-direction solar tracker. The proposed design is based on a sun sensor system that controls the position of the solar panel. The sun sensors of the proposed design contain four photodiodes that are placed on the solar panel in specific angles and directions. The proposed system has several advantages such as the simplicity of implementing the system. This system combines the real-time tracking of sunlight and the low cost of applying a single-direction tracker. The prototyping experiment and Simulink MATLAB were applied to show the advantages of applying a single-direction tracker by following the angle of sunlight during the day. Real-time sun position and irradiation data were applied. The experimental results show that the proposed single-axis sun sensor PV tracker system generates around 20 more electric power than a fixed-structure PV system. [ABSTRACT FROM AUTHOR]

Uncertainty analysis deals with the fluctuations and unpredictability of the electrical power generated from renewable resources (RRs), such as solar PV and wind energy systems. This paper gives an insight into various techniques used for the uncertainty analysis and a probabilistic Monte Carlo Simulation is applied for modelling the uncertainties concerned with RRs and electric vehicle (EV) load in the MATLAB platform. The uncertainty associated with the price sensitivity of EV charging and the state of charge of EVs is taken as a prime factor for analysis in the present work. Despite the fluctuations and unpredictability of electricity generation and consumption, the considered system ensures that the total amount of electricity supplied by solar PV, wind and grid matches the total amount of electricity demanded by EV load. Rao‐1, Rao‐2 and Rao‐3 algorithms are applied in this work to optimize the operation cost of charging stations under uncertain conditions and without any uncertainties. The results obtained without uncertainties by Rao algorithms are compared with the existing particle swarm optimisation method. In the presence of uncertainties, Rao‐1 and Rao‐2 algorithms are compared with Rao‐3 and it is found that the Rao‐3 algorithm performed better. [ABSTRACT FROM AUTHOR]

With the continuous development of the power Internet of Things (PIoT), smart devices (SDs) have been widely used in electric power inspections. Due to the limited resources of intelligent inspection SDs and the distance of overhead transmission lines, many inspection tasks cannot be processed promptly. This paper proposes a multi-hop-based end-edge cooperative computing (MHCC) scheme to address inspection task processing in power IoT. We formulate a multi-hop task offloading problem that minimizes the energy consumption of inspection SDs with delay constraints. We develop a JDPSO algorithm to solve the multi-hop task offloading problem and evaluate the algorithm's performance based on numerous simulation experiments. The experimental results show that JDPSO reduces the system's energy consumption by 56.30%, 48.56%, 78.87%, 50.89%, 30.85%, and 68.31%, and also reduces delay by 50.69%, 42.78%, 58.67%, 44.84%, 10.22%, and 62.88% compared to GA, RSA, SSA, MFO, DOA, and ALC schemes. [ABSTRACT FROM AUTHOR]

Water desalination systems integrated with stand-alone hybrid energy sources offer a remarkable solution to the water–energy challenge. Given the complexity of these systems, selecting an appropriate energy management system is crucial. In this regard, employing artificial intelligence techniques to develop and validate an energy management system can be an effective approach for handling such intricate systems. Therefore, this paper presents an ANN-based energy management system (ANNEMS) for a pumping and desalination system connected to an isolated hybrid renewable energy source. Thus, a parametric sensitivity algorithm was developed to identify the optimal neural network architecture. The water–energy management-based supervised multi-layer perceptron neural network demonstrated effective power sharing within a short time frame, achieving accuracy criteria of RMSE, R, and R² between the actual and estimated electrical power of the three motor pumps. The ANNEMS is defined to facilitate real-time power sharing distribution among the various system motor pumps on the test bench, considering the generated power profile and water tank levels. The proposed strategy employs power field oriented control to maintain DC bus voltage stability. Experimental results from the implementation of the proposed ANNEMS are provided. Therein, the power levels of the three motor pumps demonstrated consistent adherence to their reference values. In summary, this study highlights the significance of selecting appropriate energy management for real-time experimental validation. [ABSTRACT FROM AUTHOR]

The energy consumption of Cloud–Edge systems is becoming a critical concern economically, environmentally, and societally; some studies suggest data centers and networks will collectively consume 18% of global electrical power by 2030. New methods are needed to mitigate this consumption, e.g. energy-aware workload scheduling, improved usage of renewable energy sources, etc. These schemes need to understand the interaction between energy considerations and Cloud–Edge components. Model-based approaches are an effective way to do this; however, current theoretical Cloud–Edge models are limited, and few consider energy factors. This paper analyses all relevant models proposed between 2016 and 2023, discovers key omissions, and identifies the major energy considerations that need to be addressed for Green Cloud–Edge systems (including interaction with energy providers). We investigate how these can be integrated into existing and aggregated models, and conclude with the high-level architecture of our proposed solution to integrate energy and Cloud–Edge models together. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to investigate the effects of electric current stressing on damping properties of Sn5Sb solder. Design/methodology/approach: Uniformly shaped Sn5Sb solders were prepared as samples. The length, width and thickness of the samples were 60.0, 5.0 and 0.5 mm, respectively. The damping properties of the samples were tested by dynamic mechanical analyzer with a cooling system to control the test temperature in the range of −100 to 100°C. Simultaneously, electric current was imposed to the tested samples using a direct current supply. After tests, the samples were characterized using scanning electron microscope, electron backscatter diffraction and transmission electron microscope, which was aimed to figure out the damping mechanism in terms of electric current stressing induced microstructure evolution. Findings: It is confirmed experimentally that the increase in damping properties is due to Joule heating and athermal effects of current stressing, in which Joule heating should make a higher contribution. G–L theory can be used to explain the damping properties of strain amplitude under current stressing by quantitative description of geometrically necessary dislocation density. While the critical strain amplitude and high temperature activation energy decrease with increasing electric current. Originality/value: These results provide a new method for vibration reliability evaluation of high-temperature lead-free solders in serving electronics. Notably, this method should be also inspiring for the mechanical performance evaluation and reliability assessment of conductive materials and structures serving under electric current stressing. [ABSTRACT FROM AUTHOR]

The development of wearable electronics is revolutionizing human health monitoring, intelligent robotics, and informatics. Yet the reliance on traditional batteries limits their wearability, user comfort, and continuous use. Energy harvesting technologies offer a promising power solution by converting ambient energy from the human body or surrounding environment into electrical power. Despite their potential, current studies often focus on individual modules under specific conditions, which limits practical applicability in diverse real-world environments. Here, this review highlights the recent progress, potential, and technological challenges in energy harvesting technology and accompanying technologies to construct a practical powering module, including power management and energy storage devices for wearable device developments. Also, this paper offers perspectives on designing next-generation wearable soft electronics that enhance quality of life and foster broader adoption in various aspects of daily life. [ABSTRACT FROM AUTHOR]

This paper reviews alarm processing methods in electrical power systems, focusing on evolving strategies beyond traditional fault analysis to accommodate modern grid complexities. Historically, alarm processing has predominantly aimed at fault analysis, increasingly merging with technological advances in communication and computing. However, it still needs to fully meet the challenges posed by the dynamic characteristics of modern power systems. This review points out certain inadequacies in current practices, notably their limited adaptation to new grid conditions. The authors propose a novel generation of alarm processing methodologies designed for future grids, emphasizing managing rare events and enhancing operator decision-making through advanced anomaly detection and explainable artificial intelligence. This synthesis presents a prospective direction for future research and applications in alarm processing, advocating for methodologies better suited to supporting system operators amidst technological advancements. [ABSTRACT FROM AUTHOR]

The development of energy recovery systems in vehicles is a form of synergy between energy efficiency and renewable energy to overcome the energy crisis and global warming problems. This paper addresses such challenges by introducing a novel design of a piezoelectric energy harvester (PEH) for a vehicle suspension system. The PEH is designed to capture the linear vibration of the suspension system subjected to road surface roughness and move on uniform bridges. The vibration is amplified by a pressurized liquid cylinder-piston mechanism which deforms the piezoelectric bar to produce electric power. An additional novel mechanism in the form of a piezoelectric protector is also proposed to avoid physical damage due to excessive unidirectional compressive force as a result of an unpredictable uneven road. Given the key design parameters, the electric power can be harvested up to 67.5 W for a PEH with a span of 150 m of the bridge, a velocity of 40 m/s, and a vehicle mass of 2,691.6 kg. [ABSTRACT FROM AUTHOR]

A set S ⊆ V is referred to as a k-fault-tolerant power-dominating set of a given graph G = (V , E) if the difference S ∖ F remains a power-dominating set of G for any F ⊆ S with | F | ≤ k , where k is an integer with 0 ≤ k < | V | . The lowest cardinality of a k-fault-tolerant power-dominating set is the k-fault-tolerant power-domination number of G, denoted by γ P k (G) . Generalized Petersen graphs G P (m , k) and generalized cylinders S G are two well-known graph classes. In this paper, we calculate the k-fault-tolerant power-domination number of the generalized Petersen graphs G P (m , 1) and G P (m , 2) . Also, we obtain γ P k (G) for the subclasses of cylinders S C m and S B m . [ABSTRACT FROM AUTHOR]

Ultra high voltage (UHV) transmission tower-lines systems (TTLSs) are responsible for the crucial function of transmitting and distributing electrical power over long distances, which inevitably traverse active tectonic faults when passing through seismic areas. This paper investigates the seismic behaviors of the fault-crossing UHV TTLSs, taking into account the traveling wave effects of fault-crossing ground motions. Furthermore, three scenarios (i.e. the fault located at the midspan, the side span, and the one side) according to the location of the faults relative to the TTLSs, are designated to investigate the effects of fault-crossing locations on the seismic behaviors of the fault-crossing TTLSs. The results indicate that the traveling wave effects may amplify or weaken the seismic responses and collapse of the near-fault and fault-crossing TTLSs, and the effects on the longitudinal displacement responses of the TTLS are significantly greater than those in the transverse direction, but they do not affect the distribution of the collapse weak position of the TTLSs across the fault. Besides, the effect of traveling waves on the seismic behaviors of the transmission tower further away from the fault is greater than that relatively closer to the fault. This study of the impact of the traveling wave effects and fault-crossing locations on the TTLSs serves as a valuable reference for seismic behaviors of the UHV TTLSs crossing faults. [ABSTRACT FROM AUTHOR]

The traction converter modulation generates switching-frequencies current harmonics. The trapped filters can eliminate these switching harmonics, reducing total inductance and filter size. Nonetheless, in comparison with the typical inductor-capacitor-inductor (LCL) filter, the trap inductor needs a larger magnetic core. Moreover, the trapped filter has not been analyzed in the traction systems. This paper proposes a magnetic integrated inductor-trap-inductor (LLCL) filter to decrease the filter's size and investigate its application in traction converters. In fact, the application range of this filter is quite broad, and it can be used in various electrical power systems, including industrial power systems, renewable energy systems, transportation systems, and building power systems. The LC-trap may be formed by connecting the equivalent trap inductor, introduced through the magnetic coupling between inverter-side and grid-side inductors, in series with the filter capacitor. Furthermore, for H-bridge unipolar pulse width modulation (PWM) traction converters, the prominent switching harmonics are concentrated at the double switching frequencies. Therefore, the stability zone is expanded by moving the resonance above the Nyquist frequency. The presented filter's features and design are thoroughly analyzed. The proposed method is finally validated by the MATLAB/Simulink simulation and hardware-in-the-loop (HIL) experimental results. Compared to the discrete windings, the integrated ones can save two magnetic cores. Furthermore, the proposed filter can meet IEEE criteria with 0.3% for all the harmonics and total harmonic distortion (THD) of 2.15% of the grid‐side current. [ABSTRACT FROM AUTHOR]

Summary: Autonomy is becoming a prime requirement for satellite mission control operations. Data‐driven methods like Machine Learning models are playing a key role in bringing in autonomy. Health keeping data from satellite telemetry is a key ingredient in these data‐driven methods. In real‐world satellite operations, the health‐keeping telemetry data gradually drifts due to adverse space weather effects and wear and tear of electronic and mechanical components. The key question that arises is how to detect and quantify the data drift which is generally a gradual phenomenon. This paper discusses a novel statistical method for detecting data drift occurring in satellite telemetry. For the purpose of experimental work in this paper, an actual telemetry data set of the BUS CURRENT sensor which is part of the Electrical Power System of a Low Earth Orbit Satellite was considered. Data drift detection test was carried out using this sensor data using the developed novel statistical method and with Kolmogorov Smirnov test which is a probabilistic method. Both results are analysed and compared. Thereafter novel statical method was used to check its efficacy using a synthetic data set with induced drift. [ABSTRACT FROM AUTHOR]

The Autonomous Underwater Vehicle (AUV) is capable of autonomously conducting underwater cruising tasks. When combined with docking operations, the AUV can replenish its electric power after long-distance travel, enabling it to achieve long-range autonomous monitoring. This paper proposes a positioning method for the cruising and docking stages of AUVs. Firstly, a vision guidance algorithm based on monocular vision and threshold segmentation is studied to address the issue of regional noise that commonly occurs during underwater docking. A solution for regional noise based on threshold segmentation and proportional circle selection is proposed. Secondly, in order to enhance the positioning accuracy during the cruising stage, a fusion positioning algorithm based on particle filtering is presented, incorporating the Doppler Velocity Log (DVL) and GPS carried by the AUV. In simulation, this algorithm improves positioning accuracy by over 56.0% compared to using individual sensors alone. Finally, experiments for cruising and docking were conducted in Qingjiang, Hubei, China. The effectiveness of both methods is demonstrated, with successful docking achieved in four out of five attempts. [ABSTRACT FROM AUTHOR]

High mechanical strength surge arresters (HPCAs) are essential components for protecting electrical power systems from overvoltage surges. However, HPCAs can fail under cantilever loading conditions, which is a rare but serious event that can have significant consequences for the reliability of the power system. This paper presents a failure analysis and optimization of HPCAs based on finite element analysis (FEA). A three-dimensional FEA model was developed and used to evaluate the cantilever strength of the arrester under various design configurations. The existing design configuration with 12 insulating rods of 5.8 mm diameter was found to fail to meet the cantilever strength criteria. Therefore, the deflection values of various configurations of insulating rod diameter (5.8, 8, 10, 12, 14, and 16 mm) and number of rods (12, 18, and 14) were evaluated. The depth of the insulating rods inside the aluminum end fittings (EFs) was also varied. This work further employs a ramping method in analysis to reduce processing time and applies adhesion boundary conditions to simulate the behavior of the insulating rods and aluminum EFs. These approaches have allowed us to accurately model the behavior of the HPCA under cantilever loading conditions and investigate the failure mechanisms of the system. The FEA results showed that the cantilever strength of the HPCA could be significantly improved by increasing the diameter of the insulating rods and/or increasing the number of rods. The proposed approach is used to develop a new HPCA design with improved mechanical strength, which is validated through experimental testing. [ABSTRACT FROM AUTHOR]

This paper addresses the optimal sizing of Hybrid Renewable Energy Systems (HRESs), encompassing wind, solar, and battery systems, with the aim of delivering reliable performance at a reasonable cost. The focus is on mitigating unscheduled outages on the national grid in Iraq. The proposed On–off-grid HRES method is implemented using MATLAB and relies on an iterative technique to achieve multi-objectives, balancing reliability and economic constraints. The optimal HRES configuration is determined by evaluating various scenarios related to energy flow management, electricity prices, and land cover effects. Consumer requirements regarding cost and reliability are factored into a 2D optimization process. A battery model is developed to capture the dynamic exchange of energy among different renewable sources, battery storage, and energy demands. A detailed case study across fifteen locations in Iraq, including water, desert, and urban areas, revealed that local wind speed significantly affects the feasibility and efficiency of the HRES. Locations with higher wind speeds, such as the Haditha lake region (payback period: 7.8 years), benefit more than urban areas (Haditha city: payback period: 12.4 years). This study also found that not utilizing the battery, particularly during periods of high electricity prices (e.g., 2015), significantly impacts the HRES performance. In the Haditha water area, for instance, this technique reduced the payback period from 20.1 to 7.8 years by reducing the frequency of charging and discharging cycles and subsequently mitigating the need for battery replacement. [ABSTRACT FROM AUTHOR]

An important issue concerning the inspection of the technical condition of electrical power components and systems is thermal imaging investigation. This paper presents how the thermograms obtained from these measurements should be interpreted correctly according to different standards and how operators should react when detecting a specific anomaly. It is also a review article in which all currently applicable international standards are referred to. The motivation of the article relates to the fact that these standards seem to be too general and do not cover all practical situations, even though, in many countries, thermal imaging diagnostics of overhead lines or overhead outdoor and indoor power stations have been used for years based on industry standards or good practices. The article aims are precisely to encourage and provoke the global community of metrologists, scientists, and engineers involved in thermographic measurements to discuss, strengthen efforts, and establish relevant international standards for the interpretation of thermograms containing the relevant temperature anomalies. [ABSTRACT FROM AUTHOR]

This research paper aims to investigate the application of a unified power flow controller (UPFC) for relieving power congestion on a 500/230 kV grid, Power congestion occurs when the demand for electrical power exceeds the transmission capacity of the grid resulting in potential stability issues and voltage fluctuations. The UPFC is a flexible and advanced power electronic device that can regulate power flow and voltage levels in real-time hence offering a potential solution to alleviate congestion. This study explores the principles of UPFC operation its control strategies and the impact of its installation on power system stability and reliability. The research methodology involves computer simulations and analysis of the results obtained. [ABSTRACT FROM AUTHOR]

The increase in the global temperature due to greenhouse gas emissions is a major concern to the world. To achieve the goal of zero emissions by 2050 in the USA the practical realization of all-electric vehicles, particularly all-electric aircraft (AEA), is important. For the design of electrical power systems (EPSs) in all-electric aircraft, a bipolar medium-voltage direct current (MVDC) system of ±5 kV is being investigated. However, several challenges manifest when using such voltages in a low-pressure environment. One of the main challenges is the partial discharge (PD) behavior of the insulation. It is important to study the PD behavior of the insulation by simulating the aviation environment in the lab. This work aimed to study the partial discharge behavior of air under a negative DC voltage in a needle-to-plane electrode geometry by simulating the aviation pressures in the lab. The partial discharge inception voltage (PDIV) and the breakdown voltage (BDV) show an obvious pressure-dependent variation. Regression analysis was performed to better understand the relationship between the PDIV and pressures. Plots were drawn for the average discharge current at each voltage step until breakdown. This paper's findings can provide valuable insight into the design of EPS for an AEA. To the best of our knowledge, such a study has not been carried out to date. [ABSTRACT FROM AUTHOR]

This paper analyzes the behavior of an electrical power system when N-1 contingencies occur in the transmission stage, which can be produced by incorrect operation of the protection relays, phenomena of natural origin, or increased loadability, which affect the operation and reliability of the electrical system. The operation output of a transmission line results in the variation of the nominal values of the electrical parameters involved because they disturb the stability of the generation, transmission systems, and the supply of electrical energy to the loads, such as voltages and angles of the nodes and the active and reactive power of the system. The proposed methodology was based on analyzing the different electrical parameters of the power system, quantifying the contingency index in a state of regular operation, and comparing it to operation in contingency N-1, with which the most severe contingency was determined and, therefore, achieved; identifying contingencies that can cause system collapses; improving the contingency index from 23.08555 to 22.9276624 for the L16–19 contingency and to 22.9795235 for the L21–22 contingency, which are the most severe contingencies determined with the proposed methodology. To test the proposed methodology, the IEEE 39 bus-bar test system was considered, and the elements that should be implemented to avoid the vulnerability of the power system to N-1 contingencies were determined. [ABSTRACT FROM AUTHOR]

Since the International Maritime Organization has paved the way towards zero emissions, more frequent applications of transition fuels in newly constructed ships have been observed. Fuels such as LNG or methanol are characterised by lower emissions when burned in engines. In order to diminish fuel consumption, and hence the rate of emission, support for the performance of a ship's engines with energy from renewable sources such as photovoltaic (PV) installations is increasingly common. The efficiency of PV panels decreases with an increase in temperature, and it is therefore important to cool them. However, the cooling systems for PV panels impose additional financial outlays as well as a higher demand for electric power, which is needed to run the circulating pumps. A natural cooling process can occur in some vessels via high sea waves, when the ship's decks are flooded by outboard water, although such cooling has an accidental and periodic character, as it results from weather conditions. Despite this, its potential demands a closer examination. This paper presents experimental research carried out with an experimental setup that allowed us to simulate the process of flooding of a PV panel with water waves of various frequencies, resulting from choppy periods at sea. Depending on the weather conditions and the character of flooding, our results indicate that an increase in the power of the PV module of about 18% is obtainable. Our research shows that when the intervals between flooding are longer, the periodic character of the temperature changes obtained by flooding the front surface of a PV panel with water is more distinctive. [ABSTRACT FROM AUTHOR]

The paper is devoted to the development of a device for protecting facilities with turn-to-turn insulation, namely transformers and wind generators in order to increase the reliability of operation of electrical power systems, renewable energy installations and energy storage systems. The paper presents the results of experimental studies of the parameters of a prototype frequency-dependent device, as well as an assessment of the effectiveness of suppression of high-frequency surge voltages by the proposed device. The results of four groups of measurements are shown, which were compared with each other and with the results of previously showed computer simulations. The high efficiency of the proposed device when influencing the slope and amplitude of short high-frequency transients is shown. It is indicated that the parameters proposed earlier in the simulation allow the device to be used effectively. A brief analysis of alternative methods and means of protection is provided, and the prospects for using the device as protective equipment for wind power plants are also considered. [ABSTRACT FROM AUTHOR]

This paper presents the feasibility analysis and study of integrated renewable energy (IRE) using solar photovoltaic (PV) and wind turbine (WT) system in a hypothetical study of rural health clinic in Borno State, Nigeria. Electrical power consumption and metrology data (such as solar radiation and wind speed) were used for designing and analyzing the integrated renewable energy system. The health clinic facility energy consumption is 19 kWh/day with a 3.4 kW peak demand load. The metrological data was collected from National Aeronautics and Space Administration (NASA) website and used to analyze the performance of electrical generation system using HOMER program. The simulation and optimization results show that the optimal integrated renewable energy system configuration consists of 5 kW PV array, BWC Excel‐R 7.5 kW DC wind turbine, 24 unit Surrette 6CS25P battery cycle charging, and a 19 kW AC/DC converter and that the PV power can generate electricity at 9,138 kWh/year while the wind turbine system can generate electricity at 7,490 kWh/year, giving the total electrical generation of the system as 16,628 kWh/year. This would be suitable for deployment of 100% clean energy for uninterruptable power performance in the health clinic. The economics analysis result found that the integrated renewable system has total NPC of 137,139 US Dollar. The results of this research show that, with a low energy health facility, it is possible to meet the entire annual energy demand of a health clinic solely through a stand‐alone integrated renewable PV/wind energy supply. [ABSTRACT FROM AUTHOR]

Featured Application: The research presented by the authors in this article points to the need for changes in the construction of agricultural biogas plants to optimise electricity production. Energy from biogas is widely available, inexpensive, and often contributes to waste management, making it one of the most promising renewable energy sources. The main factors influencing this process' efficiency include the substrates' chemical composition, temperature, and digester load. This paper presents the possibilities offered by a biogas plant built at a farm specialising in dairy cows. The dependence of the power generated in the micro biogas plant on its technical parameters was analysed in detail. Studies carried out by the authors in an agricultural microgas plant (with an electrical output of 40 kW) have shown that they are designed to maintain continuous energy production, despite changing process parameters such as digester mass level, biogas height, temperature or slurry flow into the digester. However, from the point of view of the amount of electricity generated, changes would have to be made to the design of the biogas plant. Firstly, a more powerful generator would have to be installed to cover the electricity requirements of the equipment installed in the biogas plant so that power close to the rated capacity of the biogas plant is still sent to the grid. Secondly, replacing the two existing agitators of the digestion mass (9 kW each) with more agitators of lower power (e.g., four agitators of 4.5 kW each) would be necessary. These should be programmed so that one of the agitators operates at any given time (the operating time of a given agitator should depend on the composition of the digestate). [ABSTRACT FROM AUTHOR]

This paper reports on the testing and evaluation of a passive autoranging (AR) method designed to dynamically extend the measurement range of a photonic current transducer (PCT) to pave the way toward a realization of a combined metering- and protection-class current sensor. The PCT utilizes a current transformer (CT), a piezoelectric transducer (PZT), and a fiber Bragg grating (FBG) to enable current measurement at multiple points in an electrical power network whereby multiple sensors are deployed and interrogated serially using a single optical fiber. The autoranging technique relies on incorporating static MOSFET switches to instantaneously short individual serially connected CT burdens in response to a measured current magnitude exceeding pre-set thresholds. The AR circuit switching events produce distinctive signal features that are used by the proposed switching algorithm to apply appropriate scaling factors to reconstruct the measured current from the optical signal. It is shown through laboratory experiments that the AR circuit correctly reacts to pre-set burden current thresholds of 130% of the nominal value and 22 times the nominal value, signifying its "metering" and "protection" range boundaries. The circuit reaction time is below 4 ms, rendering it suitable for standard power system protection purposes. Moreover, the operation of the AR circuit is demonstrated for burden currents of up to 100 A for over 1 s, satisfying a test procedure for the secondary CT circuit, as required by some power system operators. It is demonstrated that the proposed switching algorithm allows for a correct reconstruction of the burden currents from the optical signal acquired by the FBG interrogator, offering the potential to realize a dual-class optical current sensor. [ABSTRACT FROM AUTHOR]