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Paper-based microfluidic devices offer advantages such as low cost and disposability for point-of-care diagnostic applications. However, actuation of fluids on paper can be a challenge in multi-step and complex assays. In this work, a thermally programmable time-delay switch (TPTDS) is presented which operates by causing delays in the fluid path of a microfluidics paper-based analytical device (μPAD) by utilizing screen-printed wax micro-bridges. The time-delay is achieved through an electrical power feedback loop which indirectly adjusts the temperature of each individual micro-bridge, melting the wax into the paper. The melted wax manipulates the fluid flow depending on its penetration depth into the paper channel, which is a function of the applied temperature. To demonstrate functionality of the proposed method, the TPTDS is employed to automate and perform the nitrate assay which requires sequential delivery of reagents. Colorimetric detection is used to quantify the results by utilizing an electronic color sensor. [Display omitted] • Fluid actuation can be a challenge in paper-based microfluidics, limitting its applicability in multi-step assays. • Wax-based micro-bridges placed across paper channels can manipulate fluid motion when melted. • Control over the wax penetration is achieved by an electrical power feedback loop, adjusts the temperature. • Time-delay switches are thermally programmed to automate a nitrate test, requires sequential delivery of the reagents. [ABSTRACT FROM AUTHOR]

Effective quality management plays a pivotal role in ensuring the smooth operation of smart city systems, which have significant implications for safety, accessibility, affordability, and maintainability. Dependability of autonomous systems is of utmost importance, as achieving satisfactory levels of availability and reliability poses considerable challenges. Smart cities are characterized by interconnected sub-architectures, encompassing vehicle monitoring, sidewalk monitoring, and building monitoring, all of which need to function efficiently. Analytical models such as Petri nets, Markov chains, and fault trees are well-suited for evaluating complex scenarios in the context of smart cities. This paper presents analytical models that utilize fault tree and Markov chain techniques to assess the availability and reliability of smart city monitoring systems. The model is divided into shared and non-shared components, with non-shared components being specific to certain contextual applications, while shared components, such as data processing and electrical power, are essential for all smart city monitoring and management systems. The study underscores the ease with which the fault tree model can enhance availability by modifying failure requirements and resources. Case studies provide concrete examples of how availability improved from 95.3 to 99.8% by varying a configuration known as "KooN" in multiple components. This paper takes a comprehensive approach to evaluating the dependability of smart city architectures and contributes advancements, such as hierarchical modeling, sequential sensitivity analysis, and the "KooN" analytic method. These contributions expand the existing knowledge and methodologies in smart city dependability analysis. Moreover, this work aims to serve as a practical tool to assist smart city managers in optimizing their proposals. All modeling aspects and parameters are detailed thoroughly to enable effective implementation of the proposed approach by anyone using it. [ABSTRACT FROM AUTHOR]

A lot of previous studies have shown a great interest in connecting photovoltaic (PV) arrays to electric power grids. A Maximum Power Point Tracker (MPPT) controlled 100 kW PV array to boost its power that feeds the grid with the help of a three-level inverter. This paper investigated the effects of open-circuit faults of three-level inverter IGBT switches on the performance of the PV array system. This paper proposes a new diagnostic method called the Double Threshold-Trigonometric Coordinates (DT-TC) that relies on the double threshold technique and the trigonometric coordinates, respectively, for early detection and the precise location of open-circuit faults. To the best knowledge of the authors, two simultaneous open-circuit faults were not considered in the previous studies. The obtained simulation results prove the great success of the proposed diagnosis method even under noticeable changes in irradiation, temperature, and the number of PV array connected in series and in parallel. In this study, the reconfigurable fault-tolerant inverter was included to ensure the perfect continuity of the PV array system and its recovery in an extremely very short time up to 7 ms. [ABSTRACT FROM AUTHOR]

Offshore wind farms (OWFs) play a crucial role in producing renewable energy in modern electrical power systems. However, to ensure that these facilities operate smoothly, they require robust control systems. As a result, this paper employed the newly developed Walrus Optimization algorithm (WaOA) to optimize the design parameters of fractional-order proportional-integral-derivative (FOPID) controllers in the power electronic interface circuits of the studied wind energy conversion system (WECS). In contrast to conventional optimization techniques like GA and PSO, the suggested approach proves more effective. The paper validates the WaOA application in optimizing FOPID controllers within a WECS comprising two, onshore and offshore, VSC stations at the two ends of an HVDC transmission system connecting OWFs to the mainland. The study shows that the WaOA outperforms GA and PSO, improving system stability and enabling quick recovery after disturbances. The study carried out using MATLAB/Simulink highlights the significance of newly recently introduced optimization techniques to ensure efficient and reliable operation of offshore wind energy systems, thereby expediting the transition to sustainable energy sources. [ABSTRACT FROM AUTHOR]

In the development of the Power Industry Internet of Things, the security of data interaction has always been an important challenge. In the power-based blockchain Industrial Internet of Things, node data interaction involves a large amount of sensitive data. In the current anti-leakage strategy for power business data interaction, regular expressions are used to identify sensitive data for matching. This approach is only suitable for simple structured data. For the processing of unstructured data, there is a lack of practical matching strategies. Therefore, this paper proposes a deep learning-based anti-leakage method for power business data interaction, aiming to ensure the security of power business data interaction between the State Grid business platform and third-party platforms. This method combines named entity recognition technologies and comprehensively uses regular expressions and the DeBERTa (Decoding-enhanced BERT with disentangled attention)-BiLSTM (Bidirectional Long Short-Term Memory)-CRF (Conditional Random Field) model. This method is based on the DeBERTa (Decoding-enhanced BERT with disentangled attention) model for pre-training feature extraction. It extracts sequence context semantic features through the BiLSTM, and finally obtains the global optimal through the CRF layer tag sequence. Sensitive data matching is performed on interactive structured and unstructured data to identify privacy-sensitive information in the power business. The experimental results show that the F1 score of the proposed method in this paper for identifying sensitive data entities using the CLUENER 2020 dataset reaches 81.26%, which can effectively prevent the risk of power business data leakage and provide innovative solutions for the power industry to ensure data security. [ABSTRACT FROM AUTHOR]

The coupling between modern electric power physical and cyber systems is deepening. An increasing number of users are gradually participating in power operation and control, engaging in bidirectional interactions with the grid. The evolving new power system is transforming into a highly intelligent socio–cyber–physical system, featuring increasingly intricate and expansive architectures. Demands for stable system operation are becoming more specific and rigorous. The new power system confronts significant challenges in areas like planning, dispatching, and operational maintenance. Hence, this paper aims to comprehensively explore potential synergies among various power system components from multiple viewpoints. It analyzes numerous core elements and key technologies to fully unlock the efficiency of this coupling. Our objective is to establish a solid theoretical foundation and practical strategies for the precise implementation of integrated planning and operation dispatching of source–grid–load–storage systems. Based on this, the paper first delves into the theoretical concepts of source, grid, load, and storage, comprehensively exploring new developments and emerging changes in each domain within the new power system context. Secondly, it summarizes pivotal technologies such as data acquisition, collaborative planning, and security measures, while presenting reasonable prospects for their future advancement. Finally, the paper extensively discusses the immense value and potential applications of the integrated planning and operation dispatching concept in source–grid–load–storage systems. This includes its assistance in regards to large-scale engineering projects such as extreme disaster management, facilitating green energy development in desertification regions, and promoting the construction of zero-carbon parks. [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]

Full- and reduced-order observers have been used in many engineering applications, particularly for energy systems. Applications of observers to energy systems are twofold: (1) the use of observed variables of dynamic systems for the purpose of feedback control and (2) the use of observers in their own right to observe (estimate) state variables of particular energy processes and systems. In addition to the classical Luenberger-type observers, we will review some papers on functional, fractional, and disturbance observers, as well as sliding-mode observers used for energy systems. Observers have been applied to energy systems in both continuous and discrete time domains and in both deterministic and stochastic problem formulations to observe (estimate) state variables over either finite or infinite time (steady-state) intervals. This overview paper will provide a detailed overview of observers used for linear and linearized mathematical models of energy systems and review the most important and most recent papers on the use of observers for nonlinear lumped (concentrated)-parameter systems. The emphasis will be on applications of observers to renewable energy systems, such as fuel cells, batteries, solar cells, and wind turbines. In addition, we will present recent research results on the use of observers for distributed-parameter systems and comment on their actual and potential applications in energy processes and systems. Due to the large number of papers that have been published on this topic, we will concentrate our attention mostly on papers published in high-quality journals in recent years, mostly in the past decade. [ABSTRACT FROM AUTHOR]

This paper introduces a novel hybrid filter topology that combines passive and active components to enhance harmonic filtering and resonance damping in electrical power systems. The design integrates a three-phase two-level voltage-source converter with a double-tuned passive filter in parallel, significantly reducing the power rating and operational costs while maintaining good harmonic filtering performance and reactive current compensation. Double-tuned passive filters, compared to single-tuned ones, offer improved harmonic attenuation at multiple frequencies, enhancing overall system efficiency. Moreover, when used with the proposed hybrid filter topology, the double-tuned version allows for even lower dimensions of the active part, thereby further reducing system cost. A state-feedback controller is designed to enhance the performance of the hybrid filter, proving particularly effective in environments with complex impedance conditions. This paper also examines the impact of variations in passive component parameters, demonstrating the design's robustness against potential deviations expected over the operational lifespan. The results indicate that the hybrid filter effectively mitigates harmonics and maintains operational stability under various transient conditions, as confirmed by analytical and simulation studies on a real industrial network model. These findings underline the hybrid filter's potential to significantly improve power quality in modern electrical networks. [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]

The electric power sector is the primary contributor to carbon emissions in China. Considering the context of dual carbon goals, this paper examines carbon emissions within China's electricity sector. The research utilizes the LMDI approach for methodological rigor. The results show that the cumulative contribution of economies scale, power consumption factors and energy structure are 114.91%, 85.17% and 0.94%, which contribute to the increase of carbon emissions, the cumulative contribution of power generation efficiency and ratio of power dissipation to generation factor are -19.15% and -0.01%, which promotes the carbon reduction. The decomposition analysis highlights the significant influence of economic scale on carbon emissions in the electricity industry, among the seven factors investigated. Meanwhile, STIRPAT model, Logistic model and GM(1,1) model are used to predict carbon emissions, the average relative error between actual carbon emissions and the predicted values are 0.23%, 8.72% and 7.05%, which indicates that STIRPAT model is more suitable for medium- to long-term predictions. Based on these findings, the paper proposes practical suggestions to reduce carbon emissions and achieve the dual carbon goals of the power industry. [ABSTRACT FROM AUTHOR]

This paper is aimed at performing a comprehensive review of the approaches employed in nanosatellite platforms, specifically 1 U and 3 U, for electrical power systems (EPS). Moreover, it seeks to develop a robust maximum power point tracking (MPPT) controller using the sliding mode control (SMC) method. The proposed control strategy is intended to monitor the solar panel's maximum power point (MPP) and adapt to changes in temperatures and solar irradiance in low Earth orbit (LEO). The EPS model, designed with the proposed sizing method, is built in MATLAB-Simulink and integrates a solar panel, battery storage, and power converters controlled by diverse MPPT methods. Then, simulation results demonstrate the effectiveness of the proposed SMC approach compared to other conventional control methods for the designed EPS under varying LEO conditions. To achieve a robust validation of the most appropriate MPPT control method under steady-state conditions, this paper presents an experimental investigation into the proposed EPS hardware design. The proposed SMC method achieved an increase in power generation from 10% to 12% for buck and boost power converters, respectively, compared to traditional control methods. [ABSTRACT FROM AUTHOR]

In the ship's electrical power system, the largest percentage of a load powered by an induction machine (IM) can be represented through the fan load characteristics. Likewise, it is well known that, from the point of view of the current load, the "most problematic" way of starting the induction machine is the direct start. This paper deals with a novel analytical modeling of the IM direct start-up speed–time curve under fan load. The derived analytical expressions have been used for modeling the start of induction machines of different powers and voltage levels. Also, the obtained results have been compared with the corresponding results provided by using the realized MATLAB/Simulink model of the induction machine coupled with fan load. Moreover, the results obtained have been compared with the methods presented in the literature as regards the modeling of start-up characteristics. The experimental validation of the proposed analytical expressions for modeling the direct start of IM driving fan load has also been carried out on a 300 W machine in a laboratory environment. Both the simulations and experimental verification have demonstrated an exceptional accuracy of the derived analytical expressions. The paper also provides the implemented MATLAB code for determining the speed–time curve of IM during direct start under fan-type load. [ABSTRACT FROM AUTHOR]

The rapid development of electric vehicles (EVs) has created more possibilities for their flexible participation in electric power dispatching. Considering the clustering and fast mobility of EVs coinciding with real-time market requirements for responsive demands, a bidding strategy is proposed in this paper to assist EV aggregators with submitting reasonable quotations for the real-time market. Based on Bayesian updating, the strategy in this paper considers relevant factors such as aggregator cost and expected return. First, a quotation strategy in electricity spot market is proposed for EV aggregators. Second, the applicable scope of the strategy is given under different scenarios. Then, the objective function of learning is proposed, and the specific process of Bayesian updating is demonstrated. Finally, a case study of the aggregator quotation strategy based on Bayesian updating is simulated to verify the effectiveness and feasibility of the proposed strategy, which helps improve the bidding success rate of EVs and peak-to-valley balance of the grid. [ABSTRACT FROM AUTHOR]

Electrical power generation in Oman depends mainly on natural gas, while in rural areas it is based mainly on diesel fuel. Oman has committed to net-zero emissions by 2050, in line with the Paris Agreement's goal of limiting global warming to 1.5°C. The objective of this paper is to propose an optimal energy mix model for electricity generation from various energy sources, such as gas, diesel, wind, and photovoltaic, that considers more renewable sources in the energy mix. The optimization model minimizes various costs such as construction cost, operation cost, fuel cost, and carbon emissions, while satisfying the load demand. In this paper, Masirah Island is selected to perform our analysis. Several scenarios are contemplated, including grid extension to the island. The results found that gas-powered generators with 20% PV and storage are the best option in terms of the levelized cost of electricity. The grid extension is an economically feasible option if the existing load is more than doubled. [ABSTRACT FROM AUTHOR]

This paper is dedicated to optimizing the functionality of Microgrid-Integrated Charging Stations (MICCS) through the implementation of a new control strategy, specifically the fractional-order proportional-integral (FPI) controller, aided by a hybrid optimization algorithm. The primary goal is to elevate the efficiency and stability of the MICCS-integrated inverter, ensuring its seamless integration into modern energy ecosystems. The MICCS system considered here comprises a PV array as the primary electrical power source, complemented by a proton exchange membrane fuel cell as a supporting power resource. Additionally, it includes a battery system and an electric vehicle charging station. The optimization model is formulated with the objective of minimizing the integral of square errors in both the DC-link voltage and grid current while also reducing total harmonic distortion. To enhance the precision of control parameter estimation, a hybrid of the one-to-one optimizer and sine cosine algorithm (HOOBSCA) is introduced. This hybrid approach improves the exploitation and exploration characteristics of individual algorithms. Different meta-heuristic algorithms are tested against HOOBSCA in different case studies to see how well it tunes FPI settings. Findings demonstrate that the suggested method improves the integrated inverters' transient and steady-state performance, confirming its improved performance in generating high-quality solutions. The best fitness value achieved by the proposed optimizer was 3.9109, outperforming the other algorithms investigated in this paper. The HOOBSCA-based FPI successfully improved the response of the DC-link voltage, with a maximum overshooting not exceeding 8.5% compared to the other algorithms employed in this study. [ABSTRACT FROM AUTHOR]

[Display omitted] • Various carbon nanotube-based devices are developed for solar energy utilization. • The water evaporation system can generate freshwater (1.28 kg m−2h−1). • The solar-thermoelectric system can output a voltage and charge a cellphone. • The supercapacitor performs an areal specific capacitance of 19.6 mF cm−2. • The hybrid energy system can produce freshwater, generate and store electric power. Nowadays, multi-functional systems driven by solar energy have been explored to alleviate the crisis of energy and freshwater scarcity. However, it remains a great challenge to integrate multi-functions into one hybrid system with a monolithic material, which can harvest, convert and store solar energy synergistically. Here, we firstly propose a multi-functional carbon nanotube paper, which starts from a material level to solve these problems. The carbon nanotube paper is fabricated by vacuum filtration. It exhibits high efficiency of solar-thermal conversion. Secondly, three types of energy conversion/storage systems (e.g., solar-thermal evaporation system, solar-thermoelectric generation system, and supercapacitor) are constructed based on the carbon nanotube paper, which extend the research to a device level. The solar-thermal evaporation system shows an evaporation rate of 1.28 kg m-2h−1 under simulated sunlight irradiation of 1 kW m−2. The solar-thermoelectric generation system demonstrates a stable electric power generation with an output voltage of 100 mV under light irradiation of 1 kW m−2. The supercapacitors perform the energy storage function with an areal specific capacitance of 19.6 mF cm−2. These devices and systems can be used in freshwater generation (0.84 kg m-2h−1, sunlight irradiation of 1 kW m−2), water purification/desalination (inorganic ions rejection larger than 99.9%) and portable solar charging system (maximum output voltage of 5 V). Finally, a hybrid energy system is innovatively proposed from the system level to simultaneously produce freshwater, generate and store electric power. Through the synergetic coupling of solar conversion and storage technologies, the hybrid energy system can supply sustainable freshwater and electricity for remote areas in daily life, highlighting the superiority of multi-energy (thermal energy, electrical energy, and electrochemical energy) complementary. [ABSTRACT FROM AUTHOR]

Highlights: [•] Effect of [DBDS], time, air and paper-Cu proximity on Cu x S deposition was studied. [•] XPS and EDX revealed deposition of Cu x S in paper increased with time or [DBDS]. [•] O2 was observed to have a key role in Cu x S displacement from the conductor surface. [•] A bifurcated pathway for Cu x S deposition in oil-immersed equipment is proposed. [Copyright &y& Elsevier]

Focuses on the reliability and power quality at Champion International Corp. paper mill in Deferiet, New York. Numerous process interruptions experienced by Champion; Voltage sags emanating from the Niagara Mohawk Power Corp. transmission system; Causes and location of faults; Mitigation techniques.

More than 50% of the electrical power needed to treat pulp and paper industry effluents is used for aeration in biological treatment stages. A large share of the oxygen that passes through the wastewater is not consumed and will be found in the off-gas. Energy can be saved by aerating under conditions where the oxygen transfer is most efficient, for example at low concentrations of dissolved oxygen Consider the sludge as an energy source; electricity can be saved by avoiding sludge reduction through prolonged aeration. High oxygen transfer efficiency can be retained by using the oxygen consumption of biosolids. Quantified savings in the form of needed volumes of air while still achieving sufficient COD reduction are presented. The tests have been made in a bubble column with pulp mill process water and sludge from a biological treatment plant. These were supplemented with case studies at three pulp and paper mills. [ABSTRACT FROM AUTHOR]

Electric vehicles are in vogue nowadays and it has been gaining some ground in India after Tesla entered into the Indian automobile market. Electric vehicles do not require conventional fuel sources such as fuel, oil, etc., so they do not pollute the environment. BLDC motors are used as the motor of electric vehicles, as they provide a higher speed as well as higher efficiency as compared to other motors. Since the vehicles are powered electrically, it is imperative for us to charge the vehicles just like cell phones. Just like fuel cars have fuel stations for filling up fuel for the operation of vehicles, there must also be battery charging or swapping stations for charging the battery of electric vehicles. This paper would determine how we must charge the electric vehicle using solar along with the traditional grid charging architecture. These two must work in tandem to provide the necessary electrical power to assuring the sufficiently charged battery at the swapping station for uninterrupted use of electric vehicles even in emergency cases. Here, the solar PV along with the traditional grid (Renewable and Conventional both respectively) is used to charge the battery at the swapping station, so it is named a hybrid battery swapping station (HBSS). Also, the concept of charging the battery packs in batches with scheduling is used which reduces the installation cost and the area requirement for the swapping stations compared to other existing battery swapping stations (BSS) or battery charging stations (BCS). [ABSTRACT FROM AUTHOR]

In this paper, three photovoltaic (PV) cooling systems are examined. The three cooling systems are (1) a PV frontside passive air (FPA) cooling system that relies on the chimney effect of air to cool the PV module, (2) a PV frontside active water (FAW) cooling where water flows in frontside of the PV panel, and (3) a PV backside active water (BAW) cooling system where water flows in a heatsink (collector) attached to the backside of the PV module. While comparing to the standalone PV, the FPA, FAW and BAW systems have cooled the PV surface temperature by 2.1, 22.4 and 17.8 °C, respectively. The FPA and BAW systems improved the PV electric efficiency by 0.84 and 6.86%, respectively; while, the FAW system degraded the PV efficiency by 26.27 % . The spectrometer measurement showed that the plexiglass and water thickness significantly lower the transmission of ultraviolet and visible light waves to the PV module. In contrast, the FAW system produced water with higher thermal content than that of the BAW system. The results show that to maximize electrical power output, BAW system is recommended, while to maximize thermal energy collection, FAW system is recommended. [ABSTRACT FROM AUTHOR]

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]

The development of the automotive industry is associated with the rapid advancement of onboard systems. In addition, intensive development in the electronics and control systems industry has resulted in a change in the approach to the issue of assistance systems in vehicles. Classic hydraulic systems have been almost completely replaced by modern electric power steering (EPS) systems, especially in citizen vehicles. This paper focuses on fault detection algorithms for EPS, along with the available tools to aid development and verification. The article discusses in detail the current state of knowledge in this area. The principle of operation of the EPS system and the influence of the structure of the mechanical system on its operation, in particular the characteristics of the ground–tire contact, are presented. Various error identification methods are presented, including those based mainly on a combination of tests of real objects as well as those combined with modern hardware-in-the-loop (HIL) equipment and virtual vehicle environment software, enabling the development of new diagnostic methods, enhancing the security, reliability, and energy control in the vehicle. A review of the literature indicates that although many algorithms which enable fault detection at an early stage are described, their potential for use in a vehicle is highly limited. The reason lies in simplifications, including models and the operating EPS temperature range. The most frequently used simplification of the model is its linearization, which significantly reduces the calculation time; however, this significantly reduces the accuracy of the model, especially in cases with a large range of system operation. The need for methods to detect incipient faults is important for the safety and reliability of the entire car, not only during regular use but also especially during life-saving evasive maneuvers. [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]

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]

The Global Navigation Satellite Systems (GNSS) provide valuable data for computing accurate and reliable Zenith Tropospheric Delay (ZTD) products used in GNSS precise positioning, climate, and meteorological studies. However, inconsistent GNSS data streaming in the East African region, caused by poor internet connectivity, equipment failure, and electrical power outages, results in data gaps that pose an impact on the applications of the ZTD products. To ensure continuous ZTD data availability, alternative approaches are necessary to fill the gaps. This paper evaluates the accuracy and feasibility of computing ZTD over East Africa using the European Centre for Medium-Range Weather Forecasts (ECMWF) 5th Re-Analysis (ERA5) model. The ERA5 ZTD is compared with ZTD data from 13 GNSS stations for the years 2013 to 2020 from the Nevada Geodetic Laboratory (NGL) products. Seven statistical evaluation metrics, including mean bias (MnB), root mean squared error (RMSE), Pearson correlation coefficient (R), coefficient of determination (R2), refined index of agreement (IA), Nash–Sutcliffe coefficient of efficiency (NSE), and Taylor skill score (TSS) were used to determine the agreement between ERA5 and GNSS tropospheric products. The results indicate that ERA5ZTD products match well with GNSS ZTD products, with an average MnB of −0.80 mm, RMSE of 8.94 mm, R of 0.976, R2 of 0.952, IA of 0.986, TSS of 0.975, and NSE of 0.945. The high accuracy and stability of ERA5 data in computing ZTD make it an excellent alternative source of ZTD data to augment GNSS ZTD products for positioning and meteorological applications in the East African region. [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]

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]

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]

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]

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]

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]

The paper analyses the combined effect of fin number (n) and inclination (β) on the overall performance of the PV module in the finned PV-PCM system by numerical simulation. System geometries with no fin to four fins are considered with inclinations varying from 0° to 45° to obtain different configurations of the PV-PCM system. Performance parameters such as mean temperature, PV efficiency, PV power output, mean velocity, and temperature contours are simulated for all the system configurations. The system is subjected to actual dynamic conditions such as variable solar radiation and ambient temperature. The maximum temperature reduction is obtained for the three-finned system with an inclination of 45°. The inclusion of fins is relatively effective for horizontal systems compared to other inclinations, and the highest relative enhancement in efficiency of 5.56% is obtained for horizontal PV-PCM system with 4 fins. Three-finned PV-PCM system with a 45° inclination angle produces the highest instantaneous PV electrical power output of 165.87 W and the lowest peak PV temperature of 50.23 °C, which is the optimum. The peak average velocity of melted PCM is maximum for unfinned PV-PCM system with β = 45 ∘ , indicating the presence of the highest strength of convection current in melted PCM. [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]

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]

For the oil-impregnated power transformers in service, the condition of the main insulation system is very important. This article reports a non-destructive evaluation technique based on time-frequency domain dielectric characteristics. First, the polarization/depolarization current and frequency-domain spectroscopy were well measured under controlled laboratory conditions. Then, the recovery voltage curves and recovery voltage polarization spectroscopy were also obtained by using the conversion method between polarization/depolarization current and recovery voltage based on the extended Debye model. After that, the time-domain dielectric characteristics, which can represent oil-paper insulation aging, were extracted from the polarization/depolarization current curves, recovery voltage curves and recovery voltage polarization spectroscopy. In addition, the frequency-domain dielectric characteristics, which can represent the oil-paper insulation aging, were also proposed in terms of frequency domain spectroscopy. Finally, the change rules of time-frequency domain dielectric characteristics under different aging times were investigated in depth. Results show that the time-frequency domain dielectric characteristics are sensitive to the aging states of power transformers, which could be utilized to diagnose the aging state of oil-paper insulation in field power transformers. [ABSTRACT FROM PUBLISHER]

This paper is an attempt to provide a dual-source inverter, an intelligent inverter topology that links two isolated DC sources to a single three-phase output through single-stage conversion. The converter is designed to be utilized in hybrid photovoltaic fuel cell systems, among other renewable energy applications. The proposed dual-source inverter employs a single DC-AC converter, as opposed to conventional dual-source hybrid inverters which make use of several input DC-DC modules to obtain the voltage formed across the inverter's input DC-link. In the proposed topology, the semiconductor count is low, which leads to improved efficiency, cost, complexity, and reliability. The proposed topology makes use of two impedance networks connected by transformers, diodes, and capacitors. The regulation of the electrical power generated by primary sources and the independence of the converter on key factors like voltage and frequency are essential parameters in multi-input converters. This feature becomes highly prominent when the control algorithm is implemented by conventional processors. Viewed from this perspective, the control method described in this paper is worthy of consideration. The research work describes a 220-W/50 Hz prototype that employs Simple Boost-SPWM. Experimental results verify the analyses and corroborate the satisfactory performance of the suggested converter. [ABSTRACT FROM AUTHOR]

Modern electrical power systems are characterized by a high rate of transient processes, the use of digital monitoring and control systems, and the accumulation of a large amount of technological information. The active integration of renewable energy sources contributes to reducing the inertia of power systems and changing the nature of transient processes. As a result, the effectiveness of emergency control systems decreases. Traditional emergency control systems operate based on the numerical analysis of power system dynamic models. This allows for finding the optimal set of preventive commands (solutions) in the form of disconnections of generating units, consumers, transmission lines, and other primary grid equipment. Thus, the steady-state or transient stability of a power system is provided. After the active integration of renewable sources into power systems, traditional emergency control algorithms became ineffective due to the time delay in finding the optimal set of control actions. Currently, machine learning algorithms are being developed that provide high performance and adaptability. This paper contains a meta-analysis of modern emergency control algorithms for power systems based on machine learning and synchronized phasor measurement data. It describes algorithms for determining disturbances in the power system, selecting control actions to maintain transient and steady-state stability, stability in voltage level, and limiting frequency. This study examines 53 studies piled on the development of a methodology for analyzing the stability of power systems based on ML algorithms. The analysis of the research is carried out in terms of accuracy, computational latency, and data used in training and testing. The most frequently used textual mathematical models of power systems are determined, and the most suitable ML algorithms for use in the operational control circuit of power systems in real time are determined. This paper also provides an analysis of the advantages and disadvantages of existing algorithms, as well as identifies areas for further research. [ABSTRACT FROM AUTHOR]

This paper is an extension of our previous research aimed to improve the performance of radiative-based thermoelectric power generator concept through the use of vertical finned absorber instead of horizontal one (TEG-RVFA). To this end, we used the experimental setup developed in previous study and modified it according to the objective of this paper. The TEG-RVFA is composed of a heated plate (297 mm×182 mm) and four sets of vertical finned absorbers (41 mm×55 mm) with 40×40 mm thermoelectric modules to absorb the heat emitted. At the back side, a finned aluminum heat sink 119 mm wide and 200 mm length with two DC fans was used for cooling. The electrical power supplied to the heater varied between 1000 - 1400 watts and the air gap between the heated plate and the finned absorber varied between 1 to 5 cm. Data recorded included the generated voltage, current, and temperatures at various locations. Results are also compared to those published earlier with horizontal finned absorber. It was observed that the electrical current generated varied like in the case with horizontal finned absorber (TEG-RHFA); it increased with the power supplied and reducing the air gap space. However, the TEG-RVFA led to better performance. The maximum power generated and the temperature difference between the hot and cool sides of thermoelectric modules observed at 1400 Watt and 3 cm air gap space were 1.63 Watt and 73.85℃ compared to 0.78 Watt and 58.93℃ for TEG-RHFA. The maximum power generation efficiency is 7.4% with horizontal fins and 9.1% for vertical finned absorber. This improvement is due to better heat transfer due to induced air circulation between the fins reducing heat accumulation at the base of the absorber and creating higher temperature difference between the two sides of thermoelectric modules. Therefore, TEG-RVFA is recommended for use when considering application in waste heat recovery such as furnaces and chimneys. [ABSTRACT FROM AUTHOR]