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Modern aircraft are being equipped with high-voltage and direct current (HVDC) architectures to address the increase in electrical power. Unfortunately, the rise of voltage in low pressure environments brings about a problem with unexpected ionisation phenomena such as arcing. Series arcs in HVDC cannot be detected with conventional means, and finding methods to avoid the potentially catastrophic hazards of these events becomes critical to assure further development of more electric and all electric aviation. Inductive sensors are one of the most promising detectors in terms of sensitivity, cost, weight and adaptability to the circuit wiring in aircraft electric systems. In particular, the solutions based on the detection of the high-frequency (HF) pulses created by the arc have been found to be good candidates in practical applications. This paper proposes a method for designing series arc fault inductive sensors able to capture the aforementioned HF pulses. The methodology relies on modelling the parameters of the sensor based on the physics that intervenes in the HF pulses interaction with the sensor itself. To this end, a comparative analysis with different topologies is carried out. For every approach, the key parameters influencing the HF pulses detection are studied theoretically, modelled with a finite elements method and tested in the laboratory in terms of frequency response. The final validation tests were conducted using the prototypes in real cases of detection of DC series arcs. [ABSTRACT FROM AUTHOR]

This paper presents the design and the non-linearity optimization of a new vertical non-contact angle sensor based on the electromagnetic induction principle. The proposed sensor consists of a stator part (with one solenoidal excitation coil and three sinusoidal receiver coils) and a rotor part (with six rectangular metal sheets). The receiver coil was designed based on the differential principle, which eliminates the effect of the excitation coil on the induced voltage of the receiver coil, and essentially decouples the excitation field from the eddy current field. Moreover, the induced voltages in the three receiver coils are three-phase sinusoidal signals with a phase difference of 10°, which are linearized by CLARK transformation. To minimize the sensor non-linearity, the Plackett–Burman technique was used, which identified the stator radius and the rotor blade thickness as the key factors affecting the sensor linearity. Then, the particle swarm algorithm with decreasing inertia weights was utilized to optimize the sensor linearity. A sensor prototype was made and tested in the laboratory, where the experimental results showed that the sensor non-linearity was only 0.648% and 0.645% in the clockwise and counterclockwise directions, respectively. Notably, the non-linearity of the sensor was less than −0.696% at different speeds. [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]

Rapid increase in the usage of intermittent renewable energy, ongoing changes in electrical power system structure and operational needs posing growing problems while ensuring adequate service reliability and retaining the quality of power. Power system reliability is a pertinent factor to consider while planning, designing, and operating distribution systems. utilities are obligated to offer their customers uninterrupted electrical service at the least cost while maintaining a satisfactory level of service quality. The important metrics for gauging the effect of distributed renewable energy on distribution networks is reliability analysis. Reliability analysis in distribution systems involves evaluating the performance and robustness of electrical distribution networks. An artificial intelligence approach is implemented in this paper to improve reliability analysis with dispersed generations in distribution network. Deep belief neural networks (DBNNs) are a type of artificial neural network that can be used for various tasks, including analyzing complex data such as those found in power distribution systems. This paper integrated a DBNN using a particle swarm optimization (PSO) technique. The proposed model performance is assessed using mean square error, mean absolute error, root mean square error, and R squared error. The findings reveal that reliability analysis with this novel technique is more accurate. [ABSTRACT FROM AUTHOR]

The growing penetration of fast charging stations (FCSs) to electric vehicles (EVs) and distributed energy resources (DERs) in the electrical power system brings technical issue changes in the voltage profile throughout grid nodes and feeder current overload. The provision of ancillary services by DERs and FCSs arises as an appealing solution to reduce these adverse effects, enhancing the grid hosting capacity. The control of microgrids is essential for the coordinated implementation of these services. Although microgrid control is widely applied to DERs, few studies address the coordinated control of DERs and FCSs to obtain benefits for the electrical power system. This paper proposes a coordinated and simultaneous control of DERs and FCSs based on the power-based control (PBC) strategy, efficiently exploiting FCSs in a microgrid model previously unaddressed in the literature. The results show that, with the coordinated control of DERs and FCSs, the control of the power flow in a minigrid (MG) is achieved both in moments of high generation and in moments of high load, even with the maximum operation of DERs. This method allows for the maintenance of voltage levels within values considered acceptable by technical standards (above 0.93 pu). The maintenance of voltage levels is derived from reducing the overload on the point of common coupling (PCC) of the minigrid by 28%, performing the peak shaving ancillary service. Furthermore, the method allows for the control of zero power flow in the PCC of the minigrid with the upstream electric grid in periods of high generation, performing the ancillary service of valley filling. The method performs this control without compromising vehicle recharging and power dispatch by DERs. [ABSTRACT FROM AUTHOR]

This paper proposes a two-level control strategy based on a super-twisting sliding-mode algorithm (STA) to optimally allocate power imbalances in shipboard microgrids (SMGs) while achieving frequency regulation. The strategy employs an STA observer to estimate the unknown power load demand imbalances in finite time. This estimate is then passed to an online high-level optimal control framework to periodically determine the optimal sequence of power reference values for each energy storage device (ESS), minimising the operational cost of the SMG. The online optimised power reference values are interpolated and passed to the low-level STA control strategy to control the output power of each ESS. The efficacy of the proposed methods is demonstrated through numerical simulations conducted on a prototypical model of an SMG equipped with two ESSs, namely batteries and fuel cells with associated hydrogen storage. [ABSTRACT FROM AUTHOR]

As the operating speed of electric multiple units (EMUs) in high-speed railways increases, pantograph–catenary (PC) detachment arcing occurs frequently. The resulting vehicular-grounding electromagnetic transients are related to the dynamic characteristics of the arc length. During large detachment, the processes of arc extinction and arc reignition may occur, resulting in more severe train body (TB) over-voltages and adverse effects on some vehicular electronic devices. As an extension of the previous works, this paper aims to establish a suitable PC arc model to examine the TB transient voltages. To begin with, the arc length dynamic characteristics are reasonably analyzed to deduce the relationship between the detachment distance and the arc length via the chain arc model. Then, the dynamic characteristics of the arc length are introduced, and an arc modeling scheme is proposed to elaborate the vehicle-grid electric power model for EMUs encountering various arcing scenarios. Based on this, the transient over-voltages are analyzed, accounting for both the arc extinction and arc reignition, as well as the mutual influences of multiple detachments in a short time. The influential factors, including arc length characteristics, phase angle, excitation inductance, and grounding parameters, are also involved in the performed analyses. [ABSTRACT FROM AUTHOR]

The deployment of isolated microgrids has witnessed exponential growth globally, especially in the light of prevailing challenges faced by many larger power grids. However, these isolated microgrids remain separate entities, thus limiting their potential to significantly impact and improve the stability, efficiency, and reliability of the broader electrical power system. Thus, to address this gap, the concept of interconnected smart transactive microgrids (ISTMGs) has arisen, facilitating the interconnection of these isolated microgrids, each with its unique attributes aimed at enhancing the performance of the broader power grid system. Furthermore, ISTMGs are expected to create more robust and resilient energy networks that enable innovative and efficient mechanisms for energy trading and sharing between individual microgrids and the centralized power grid. This paradigm shift has sparked a surge in research aimed at developing effective ISTMG networks and mechanisms. Thus, in this paper, we present a review of the current state-of-the-art in ISTMGs with a focus on energy trading, energy management systems (EMS), and optimization techniques for effective energy management in ISTMGs. We discuss various types of trading, architectures, platforms, and stakeholders involved in ISTMGs. We proceed to elucidate the suitable applications of EMS within such ISTMG frameworks, emphasizing its utility in various domains. This includes an examination of optimization tools and methodologies for deploying EMS in ISTMGs. Subsequently, we conduct an analysis of current techniques and their constraints, and delineate prospects for future research to advance the establishment and utilization of ISTMGs. [ABSTRACT FROM AUTHOR]

Featured Application: The proposed solution of fasteners made of corrugated steel sheet and shot nails can be used as the connector for steel–concrete composite floor beams. The sheet provides stay-in-place formwork for a monolithic reinforced concrete slab. Furthermore, the sheet in the shape of the dovetail caused the connection between the steel I-beam and the concrete slab. The connectors are easy to fabricate. Any special mounting equipment that requires high-current electrical power is not necessary. Because shot nails have very wide applications, nailing devices are available in almost every construction factory and on construction sites. The shape of a such cross-section of the metal sheet improves its stability during installation compared to a flat metal sheet. An additional advantage is the ability to easily suspend the finishing elements by using dedicated hangers fixed in the fold of sheet. The paper presents an analysis of the innovative connector for manufacturing a steel–concrete composite beam. The connector consists of a corrugated metal sheet in the shape of a dovetail and shot nails. The nails are shot through the sheet fold into the flange of the steel I-section. Experimental studies of push-out tests were carried out. The conducted tests proved that the proposed solution can be applied as the fastener for steel–concrete composite beams for the construction of ceilings in utility public buildings with small beam's span. Considering the criteria presented in the Eurocode 4 standard and the results of the experiments, it was proven that all analyzed types of fasteners are ductile. The connector made of sheet with a thickness of 1.00 mm and 2 nails is characterized by a breaking load of 30.83 kN. The load-bearing capacity of the fastener can be adjusted by changing the corrugated sheet thickness and changing the number of nails shot in the single fold of the sheet. [ABSTRACT FROM AUTHOR]

It is crucial to explore new green energy sources to alleviate the earth's energy depletion and the impact of air pollution and greenhouse effects. Although wafer manufacturing is increasing worldwide, the implementation of carbon footprint policies necessitates a shift toward green electricity. To expand the scale of wafer manufacturing, it is essential to develop terrestrial green electricity, which requires additional terrestrial green energy sources. This paper presents a green energy harvesting method that generates wave hydraulic energy via a vibration-based electromagnetic generator through a buoy. An energy harvester composed of two magnets in series driven by a buoy via a connected pole is introduced. The sensitivity of induced electricity to the energy harvester's design parameters, including the magnets' geometric dimensions (diameter and height), the coil's turns, and layers, is analyzed. Additionally, the relationship between electricity and wave information (wave amplitude and wavelength) is explored. To evaluate the electrical power efficiency between a pair of single-magnet energy harvesters and the two-magnet harvester, a pair of parallel energy harvesters consisting of one magnet and paralleled in line is assessed. The impact of electricity on the horizontal span between the parallel energy harvesters is also investigated. To achieve maximal electricity, the two-magnet energy harvester is numerically optimized using a simulated annealing method. The numerical result shows that the two-magnet (in series) energy harvester can produce 0.472 W when the wavelength is 0.03, the amplitude is 0.09 m, and the wave speed is 3 m/s. [ABSTRACT FROM AUTHOR]

The supply of electric power is vital for the daily lives of people, industrial production, and business services. At present, although enough electric power can be supplied to meet the power demand, there are still some challenges, especially in terms of long-distance power transmissions and long-term power storage. Consequently, if the power production capacity exceeds the immediate consumption requirements, i.e., the produced electric power cannot be consumed in a short period, and much electric power could be wasted. Evidently, to minimize the wastage of electric power, it is necessary to properly plan power production by accurately forecasting the future power load. Therefore, a preferable power load forecasting algorithm is crucial for the planning of power production. This paper proposes a novel deep learning model for the purpose of power load forecasting, termed the SSA-CNN-LSTM-ATT model, which combines the CNN-LSTM model with SSA optimization and attention mechanisms. In this model, the CNN module extracts the features from the sequential data, and then the features are passed to the LSTM module for modeling and capturing the long-term dependencies hidden in the sequences. Subsequently, an attention layer is employed to measure the importance of different features. Finally, the output is obtained through a fully connected layer, yielding the forecasting results of the power load. Extensive experiments have been conducted on a real-world dataset, and the metric R2 can reach 0.998, indicating that our proposed model can accurately forecast the power load. [ABSTRACT FROM AUTHOR]

To investigate the harmonic characteristics of electric locomotives connected to a photovoltaic (PV) power grid based on the actual parameters of a region in Tibet, this paper establishes a simulation model of an electric power grid, including PV and electric locomotive. First, theoretical analysis is conducted to study the harmonic characteristics of electric locomotives and PV power stations. On this basis, we built the MATLAB model to analyze the influence of dynamic working conditions on the locomotive and PV sides on the harmonic characteristics of the power grid. Through the first, second, and third working conditions, a simulation analysis is performed to examine the harmonic characteristics of an electric locomotive when connected to the grid, which includes a PV power source. The results show that the grid side current, including PV and electric locomotive, has a three-phase equilibrium phenomenon, and at the same time, the grid side current harmonic characteristics, including PV and electric locomotive, are mainly reflected in the 17, 19, 21, 23, and 25 frequency odd harmonics. [ABSTRACT FROM AUTHOR]

This paper deals with the control and performance improvement of parallel-operated voltage-source inverters (VSIs) controlled as virtual synchronous generators (VSGs). In publications regarding the parallel-operated VSGs, transmission lines are considered to be mainly inductive. However, less analytical works have been done regarding the control of paralleled VSGs in low-voltage grids with dominant resistive impedances. Once VSIs are controlled as VSGs in a microgrid with more resistive transmission lines, swing equation and system representation for the power-angle synchronization will change leading to a new control structure. Therefore, this paper deals with the control of parallel-operated converter-based VSGs in low-voltage grids with dominant resistive line impedances. In this way, the VSG representation, comprising the swing equation and V-P droop characteristic, for applications in highly resistive microgrids is presented, in which the swing equation and VSG frequency are related to reactive power. Then, the V-P droop characteristic is modified and an enhanced P-V droop characteristic for proper sharing of active power between the VSGs in highly resistive microgrids is proposed. Next, the VSG control is modified so that the R/X ratio at the VSG output increases and thus the decoupled control of active/reactive powers in relatively inductive cases is realized as well. [ABSTRACT FROM AUTHOR]

Present day complex power system network especially power transmission is being operated under highly stressed condition due to continuous increase in electric power demand day by day in various sectors such as industrial, commercial and domestic etc. As long as load increases, the reactive power demand also increases abruptly. The main objective of the present research paper is to develop a strange way of analyzing the power system conditions by locating various FACTS devices such as STATCOM, SSSC and UPFC which improves voltage profile and minimize network losses. FACTS devices with suitable placement will meet the required reactive power demand of the complex and stressed power transmission system. In this paper the placement of FACTS devices using GA, PSO and HGAPSO heuristic techniques are introduced and the results are compared on IEEE 30 bus test system in a MATLAB environment. The HGAPSO heuristic technique gives effective placement than GA and PSO heuristic techniques are presented in this paper. [ABSTRACT FROM AUTHOR]

In locations where power is restricted, such as off-grid, solar, and generator-powered houses, considering the capacity of the power source is critical for the effectiveness of home automation systems. During regular power system outages, millions of houses all over the globe are reliant on a fixed current power supply to keep their lights on. In such circumstances, prioritizing and arranging the home's workload is essential. The goal of this paper is to decrease the amount of effort required by the user to manually control a gadget. To connect with the Raspberry Pi and the users, this system makes use of Google Assistant Software Development Kit (SDK), which is offered by Google. Users use voice commands to manage the devices in their homes, check the amount of current available, and chat to the Google Assistant to turn on/off the smart switch. This paper suggests using a sensor, Message Queuing Telemetry Transport (MQTT) protocol, a controller (OpenHAB open source), and an actuator in conjunction with each other (smart switch) has the capability of measuring and monitoring the entire power that is available and making choices based on that knowledge. Finally, the usage of Google Assistant as an artificial intelligence system makes end-user engagement with the smart home more pleasant. The proposed network was executed in both unlimited and limited power or electrical current modes to compare the standard unlimited smart home setup and our current control design. The system was programmed to function based on the proposed algorithm, with a 10 Ampere as a maximum available current. The water heater was considered a low priority load in this trial as a heavy load. In this system’s run, the smart controller was continuously monitoring the load, and when the total load reaches 10 Amperes or above it turns off the low priority loads. Thus, preventing the power supply overload. [ABSTRACT FROM AUTHOR]

The outdoor terminal box is the basic node of the power Internet of Things as an intermediate link between outdoor electrical equipment and indoor equipment, like measurement and control, protection, communication and other equipment. Terminal boxes and terminals need to be regularly checked on site, loop tests, transformations, and equipment replacement. Operator errors have become one of the main factors in outdoor terminal box accidents. In terms of human risk assessment of outdoor terminal boxes, few papers are involved. In order to correctly evaluate the influence of human factors on the failure of outdoor terminal boxes, the paper first analyzes the human behavior factors of outdoor terminal box operators, the common performance conditions of the CREAM (Cognitive Reliability and Error Analysis Method) model is used to analyze the human behavior mechanism and behavior reliability factors during the operation of the terminal box. Then, the SLIM (Success Likelihood Index Method) model is used to calculate the probability of human error. The proportional failure model is used to calculate the failure rate of the outdoor terminal box itself. Finally, taking a circuit breaker terminal box as an example for simulation, the probability of human error is 1.56%, the equipment failure rate is 0.84%, the risk value of the system is 10.7%, and the risk level of the system is 3. From the probabilistic perspective, it shows that human factors have a greater influence on the causes of accidents. [ABSTRACT FROM AUTHOR]

The need for economic, reliable, and effective delivery of electric power has lead to the search for fast, efficient, and effective methods for diagnosing the insulation of high-voltage (HV) equipment in the power industries. The recent dielectric techniques that have been carefully considered by major industries for transformer insulation condition assessment are the recovery voltage method (RVM) and the polarization and depolarization current (PDC) measurement. However, due to the complexity of the transformer insulation structure and various degradation mechanisms under multiple stresses, insulation condition assessment is usually performed by experts with special knowledge and experience. In this paper, an expert system (ES) is developed, which imitates the performance of a human expert, to make the complicated insulation condition assessment procedure accessible to plant maintenance engineers. The structure of the ES is described in detail including knowledge base, inference engine, and human-computer interface. Examples of the application of the ES are also presented to confirm that the system can provide accurate insulation diagnosis. [ABSTRACT FROM AUTHOR]

This paper considers a single-machine scheduling problem with sequence-dependent setup times and energy-generation and storage systems. Each job requires a sequence-dependent setup to be processed on the machine, and both setup and processing of the job require job-dependent amounts of energy. The energy consumed by the machine can be bought from an Electric Power Company (EPC) or generated by own Distributed Energy Resource (DER), such as solar photovoltaic or wind, and the energy can be stored in an Energy Storage System (ESS). The objective is to minimise the total cost, the sum of production cost depending on makespan and energy cost by considering energy usage from the EPC, DER and ESS. For the problem, a mathematical programming model is first derived by using period-based indexes. Then, a hybrid genetic algorithm, which adds appropriate idle times between jobs and determines an efficient energy schedule by storing some energy during less expensive periods into the ESS for later use in high-price periods, is developed. Finally, computational experiments show that the proposed algorithm provides effective solutions, and which component of the total cost affects the performance the most, how effective adding idle times between jobs is, and how much cost can be saved by having a DER and ESS. [ABSTRACT FROM AUTHOR]

Safety mishaps at electric power construction sites have been more frequent in recent years as a result of the growth of the electric power business, the inescapable carelessness of current safety oversight, and other causes. Traditional manual supervision and video surveillance methods demand a lot of human resources and suffer from issues like low efficiency and lack of objectivity, making it unable to provide security alerts in real-time and accurately. Therefore, solutions like intelligent monitoring based on object detection are required to address this issue. Many object detection methods now in use (such as R-CNN, Fast R-CNN, and YOLOV5) are computationally and energy intensive. They are typically installed on remote back-end servers, which makes it impossible to guarantee the real-time security alert. This paper trains a lightweight NanoDet network model to recognize the attire and actions of power construction workers in order to address the aforementioned issues. Additionally, in order to meet the real-time security warning requirements and fully utilize the limited computing resources of edge devices, the NanoDet network model is divided, with some layers being divided into CPU execution. According to experiments, power consumption can be reduced by deploying the Backbone or PAFPN blocks of the NanoDet model to CPUs and running them in 30W4Core mode. [ABSTRACT FROM AUTHOR]

The growing demand for electricity in long-duration space missions has become a pressing concern. The space nuclear closed-Brayton-cycle (CBC) power generation system offers advantages in power output, operational lifespan, and range. However, a significant speed disparity exists between its compressor and alternator. To address this challenge, this paper proposes a double-rotor CBC configuration. A corresponding dynamic model that couples the nuclear reactor and radiator is formulated, and dynamic analysis is conducted to facilitate system control. The study delves into the dynamic start-up process of the double-rotor CBC system and examines how various component parameters impact its power generation performance. The findings indicate that through the introduction of suitable reactivity to regulate reactor power and the incorporation of a PID controller to manage flow distribution between two turbines, the system can achieve start-up within 5200 s. Moreover, the innovative double-rotor structure suggested in this paper enables the separation of compressor and alternator speeds. Consequently, the compressor and alternator can operate within their optimal speed ranges independently, which is a feature that holds potential benefits for the system's practical implementation. In addition, the steady-state operation of the system showcases the recuperator's heat transfer power at around 1127.60 kW, a parameter of significant importance. Following steady-state operation, the double-rotor CBC system demonstrated an electrical power output of 175.99 kW and a thermal efficiency of 32.38%. [ABSTRACT FROM AUTHOR]

For ultra‐high‐voltage (UHV) systems together with high‐voltage facilities, more rationalized insulation coordination and equipment design are required. To this end, making large‐scale and long‐term field lightning‐strike observations, large amount of and practical experiments, and introducing new analysis techniques have enabled the development of advanced technologies capable of transforming conventional techniques. This paper reviews what has been developed in a Japanese electric power company in this regard. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Currently, there are strong and sustained growth trends observed in multi-disciplinary industrial technologies such as building-integrated photovoltaics and agrivoltaics, where renewable energy production is featured in building envelopes of varying degrees of transparency. Novel glass products can provide a combination of thermal energy savings and solar energy harvesting, enabled by either patterned-semiconductor thin-film energy converters on glass substrates, or by using luminescent concentrator-type approaches to achieve high transparency. Significant progress has been demonstrated recently in building integrated solar windows featuring visible light transmission of up to 70%, with electric power outputs of up to Pmax ~ 30–33 Wp/m2. Several slightly different designs were tested during 2021–2023 in a greenhouse installation at Murdoch University in Perth, Western Australia; their long-term energy harvesting performance differences were found to be on the scale of ~10% in wall-mounted locations. Solar greenhouse generated electricity at rates of up to 19 kWh/day, offsetting nearly 40% of energy costs. The objective of this paper is to report on the field performance of these PV windows in the context of agrivoltaics and to provide some detail of the performance differences measured in several solar window designs related to their glazing structure materials. Methods for the identification and quantification of long-term field performance differences and energy generation trends in solar windows of marginally different design types are reported. The paper also aims to outline the practical application potential of these transparent construction materials in built environments, focusing on the measured renewable energy figures and seasonal trends observed during the long-term study. [ABSTRACT FROM AUTHOR]

Subsea oil and gas (O&G) exploration demands significantly high power to supply the electrical loads for extraction and pumping of the oil and gas. The energy demand is usually met by fossil fuel combustion-based platform generation, which releases a substantial volume of greenhouse gases including carbon dioxide (CO2) and methane into the atmosphere. The severity of the resulting adverse environmental impact has increased the focus on more sustainable and environment-friendly power processing for deepwater O&G production. The most feasible way toward sustainable power processing lies in the complete electrification of subsea systems. This paper aims to dive deep into the technology trends that enable an all-electric subsea grid and the real-world challenges that hinder the proliferation of these technologies. Two main enabling technologies are the transmission of electrical power from the onshore electrical grid to the subsea petroleum installations or the integration of offshore renewable energy sources to form a microgrid to power the platform-based and subsea loads. This paper reviews the feasible power generation sources for interconnection with subsea oil installations. Next, this interconnection's possible power transmission and distribution architectures are presented, including auxiliary power processing systems like subsea electric heating. As the electrical fault is one of the major challenges for DC systems, the fault protection topologies for the subsea HVDC architectures are also reviewed. A brief discussion and comparison of the reviewed technologies are presented. Finally, the critical findings are summarized in the conclusion section. [ABSTRACT FROM AUTHOR]

Synchronization is one of the key issues in three-phase AC power systems. Its characteristics have been dramatically changed with the large-scale integration of power-electronic-based renewable energy, mainly including a permanent magnetic synchronous generator (PMSG) and a double-fed induction generator (DFIG) for wind energy and a photovoltaic (PV) generator for solar energy. In this paper, we review recent progresses on the synchronization stability and multi-timescale properties of the renewable-dominated power system (RDPS), from nodes and network perspectives. All PMSG, DFIG, and PV are studied. In the traditional synchronous generator (SG) dominated power system, its dynamics can be described by the differential–algebraic equations (DAEs), where the dynamic apparatuses are modeled by differential equations and the stationary networks are described by algebraic equations. Unlike the single electromechanical timescale and DAE description for the SG-dominated power system, the RDPS dynamics should be described by the multiscale dynamics of both nodes and networks. For three different timescales, including the AC current control, DC voltage control, and rotor electromechanical timescales, their corresponding models are well established. In addition, for the multiscale network dynamics, the dynamical network within the AC current control timescale, which should be described by differential equations, can also be simplified as algebraic equations. Thus, the RDPS dynamics can be put into a similar DAE diagram for each timescale to the traditional power system dynamics, with which most of power electrical engineers are familiar. It is also found that the phase-locked loop for synchronization plays a crucial role in the whole system dynamics. The differences in the synchronization and multiscale characteristics between the traditional power system and the RDPS are well uncovered and summarized. Therefore, the merit of this paper is to establish a basic physical picture for the stability mechanism in the RDPS, which still lacks systematic studies and is controversial in the field of electrical power engineering. [ABSTRACT FROM AUTHOR]

Hybrid renewable power generation becomes essential in most of electric power networks. Battery storage is commonly used in renewable energy systems (RESs) with distributed generation, such as solar and wind energy systems, to reduce power fluctuations caused by the intermittent behavior of renewable energy sources. A battery has been connected with the dc grid through a dc–dc bi-directional converter. The control scheme of the dc–dc bi-directional converter (BDC) is having two controlled loops. One is voltage-controlled loop, and another is the current-controlled loop. In this work, two-degree-of-freedom fractional order proportional integral derivative + proportional integral controller (2-DOF FOPID + PI) is proposed and applied in the voltage-controlled loop to stabilize the dc bus voltage and power flow effectively for both islanded mode and grid-connected mode. A novel meta-heuristic algorithm, i.e., modified sine cosine algorithm (m-SCA), is used to tune the controller parameters of the proposed controller. To test the performance of the modified SCA algorithm, various well-known uni-modal and multi-modal benchmark functions are taken in this paper. To confer the viability of the proposed controller, its performance is compared with other literature-based conventional controllers. This paper presents time-domain analysis, stability, and robustness test to illustrate the effectiveness of the proposed controller. MATLAB/Simulink has been used for computational work to analyze the system's efficiency. Finally, the proposed technique is validated by using OPAL-RT platform (Opal-RT-OP4510 model) with the power management of RES (PV and wind) and battery energy storage. Experimental work proved the effectiveness of the proposed m-SCA optimized 2-DOF FOPID + PI controller. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study of winter temperatures in Norway and northern Sweden, covering a period of 50 to 70 years. The analysis utilizes Singular Spectrum Analysis (SSA) to investigate temperature trends at six selected locations. The results demonstrate an overall long-term rise in temperatures, which can be attributed to global warming. However, when investigating variations in highest, lowest, and average temperatures for December, January, and February, 50% of the cases exhibit a significant decrease in recent years, indicating colder winters, especially in December. The study also explores the variations in Atlantic Meridional Overturning Circulation (AMOC) variations as a crucial climate factor over the last 15 years, estimating a possible 20% decrease/slowdown within the first half of the 21st century. Subsequently, the study investigates potential similarities between winter AMOC and winter temperatures in the mid to high latitudes over the chosen locations. Additionally, the study examines another important climatic index, the North Atlantic Oscillation (NAO), and explores possible similarities between the winter NAO index and winter temperatures. The findings reveal a moderate observed lagged correlation for AMOC-smoothed temperatures, particularly in December, along the coastal areas of Norway. Conversely, a stronger lagged correlation is observed between the winter NAO index and temperatures in northwest Sweden and coastal areas of Norway. Thus, NAO may influence both AMOC and winter temperatures (NAO drives both AMOC and temperatures). Furthermore, the paper investigates the impact of colder winters, whether caused by AMOC, NAO, or other factors like winds or sea ice changes, on electrical power and energy systems, highlighting potential challenges such as reduced electricity generation, increased electricity consumption, and the vulnerability of power grids to winter storms. The study concludes by emphasizing the importance of enhancing the knowledge of electrical engineering researchers regarding important climate indices, AMOC and NAO, the possible associations between them and winter temperatures, and addressing the challenges posed by the likelihood of colder winters in power systems. [ABSTRACT FROM AUTHOR]

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A Lead-Cooled Fast Reactor (LFR) is one of the six advanced fourth-generation reactors that many countries have been interested in designing, constructing, or develop them in the world. ALFRED reactor design investigated in this paper has 125 (MW) electric power and is being cooled by lead. The main purpose of the ALFRED project is to design and construct a reactor with high safety performance and reliability in all operation modes. In the present study, Monte Carlo codes MCNPX and SuperMC are used to calculate the neutronic parameters of the ALFRED reactor core including effective multiplication factor, kinetic parameters, neutron flux, and power distribution based on the latest design data. According to the results, the insertion of the control rods into the core can move the maximum flux height of about 40% to 50% to the end. Also, comparing codes' results show an appropriate consistency. [ABSTRACT FROM AUTHOR]

Disruptive failures threaten the reliability of electric supply in power branches, often indicated by the rise of leakage current in distribution insulators. This paper presents a novel, hybrid method for fault prediction based on the time series of the leakage current of contaminated insulators. In a controlled high-voltage laboratory simulation, 15 kV-class insulators from an electrical power distribution network were exposed to increasing contamination in a salt chamber. The leakage current was recorded over 28 h of effective exposure, culminating in a flashover in all considered insulators. This flashover event served as the prediction mark that this paper proposes to evaluate. The proposed method applies the Christiano–Fitzgerald random walk (CFRW) filter for trend decomposition and the group data-handling (GMDH) method for time series prediction. The CFRW filter, with its versatility, proved to be more effective than the seasonal decomposition using moving averages in reducing non-linearities. The CFRW-GMDH method, with a root-mean-squared error of 3.44 × 10 − 12 , outperformed both the standard GMDH and long short-term memory models in fault prediction. This superior performance suggested that the CFRW-GMDH method is a promising tool for predicting faults in power grid insulators based on leakage current data. This approach can provide power utilities with a reliable tool for monitoring insulator health and predicting failures, thereby enhancing the reliability of the power supply. [ABSTRACT FROM AUTHOR]

Provides instructions and guidelines to prospective authors who wish to submit manuscripts. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy, power demand has been closely linked with economic development in order to analyze and predict the future power situation in China. Based on the historical data of China's electricity consumption, this paper analyzes the data characteristics of China's electricity consumption by using Eviews software. The long-term trend of power consumption sequence is eliminated by fitting the regression curve, and then the residual sequence is analyzed and identified according to the relevant theory of time series. Using the data of China's power demand from 2004 to 2019, the ARMA time series model is used to analyze China's future power situation finally according to the test statistics of the model. Finally, the exponential regression ARMA model is selected to predict China's electricity consumption. The index regression analysis method extracts the long-term characteristic information of the sequence, which is conducive to the stability processing and empirical analysis of long-term prediction. The result predicts China's power demand in 2020 more accurately, which can provide a reference for the future productivity layout of China's power. [ABSTRACT FROM AUTHOR]

The development of more electric aircrafts (MEA) and all electric aircrafts (AEA) inevitably implies an increase in electric power and a consequent increase in distribution voltage levels. Increased operating voltages coupled with low pressure in some areas of the aircraft greatly increase the chances of premature insulation failure. Insulation failure manifests itself as surface discharges, arc tracking, arcing, and disruptive or breakdown discharges, in order of increasing severity. Unfortunately, on-board electrical protections cannot detect discharges at an early stage, so other strategies must be explored. In their early stage, insulation faults manifest as surface and corona discharges. They generate optical radiation, mainly in the near-ultraviolet (UV) and visible spectral regions. This paper focuses on a method to detect the discharges, locate the discharge sites, and determine their intensity to facilitate predictive maintenance tasks. It is shown that by using small size and low-cost image sensors, it is possible to detect, locate, and quantify the intensity of the discharges. This paper also proposes and evaluates the behavior of a discharge severity indicator, which is based on determining the intensity of digital images of the discharges, so it can be useful to apply predictive maintenance tasks. The behavior and accuracy of this indicator has been tested in the laboratory using a low-pressure chamber operating in the pressure range of 10–100 kPa, which is characteristic of aircraft applications, analyzing a needle-plane air gap geometry and using an image sensor. The proposed method can be extended to other applications where electrical discharges are an issue. [ABSTRACT FROM AUTHOR]

Smart electric grids are practising flexible, reliable and robust operations during delivery and consumption of power. However, these grids are highly vulnerable to a wide range of cyber attacks due to the deployment of an extensive communication network. In this paper, the nature of cyber attack on given power system based on proposed cyber attack models and theorems is analysed by utilizing steady state voltage stability (L index). Further, a cyber attack factor is introduced which may mislead the bus voltage stability virtually. The proposed cyber attack models and theorems are validated by executing cyber attacks on WSCC 9 bus and IEEE 14 bus test systems by using Siemens PSS/E and MATLAB softwares. Through the proposed theorems, the paper exposes and quantifies the threat of cyber attacks in the electric power grid. The simulation results reveal that the proposed cyber attack models may misrepresent the bus voltage stability, thereby misleading the energy management centre (EMC) operator into taking incorrect countermeasures. The above incorrect actions may force voltage instability which further leads to major interruptions in the electric power supply and possible cascading failure of the electric power grid. Moreover, the proposed theorems and rigorous simulations presented in the paper support the EMC operator in intelligently identifying a cyber attack, thereby enabling development of appropriate corrective actions during such cyber attacks on the smart electric grid. Thus, the concept of proposed methodology could best assist the power system operator to build detection algorithms for discrimination of cyber attacks from electrical faults towards strong electric grid resilience character. [ABSTRACT FROM AUTHOR]

Predictive control offers many advantages such as simple design and a systematic way to handle constraints. Model predictive control (MPC) belongs to predictive control, which uses a model of the system for predictions used in predictive control. A major drawback of MPC is the dependence of its performance on the model of the system. Any discrepancy between the system model and actual plant behavior will greatly affect the performance of the MPC. Recently, model-free approaches have been gaining attention because they are not dependent on the system model parameters. To obtain the advantages of both a model-free approach and predictive control, model-free predictive control (MFPC) is being explored and reported in the literature for different applications such as power electronics and electric drives. This paper presents an overview of model-free predictive control. A comprehensive review of the application of MFPC in power converters, electric drives, power systems, and microgrids is presented in this paper. Moreover, challenges, opportunities, and emerging trends in MFPC are also discussed in this paper. [ABSTRACT FROM AUTHOR]

Power system planning faces various issues related to reliability and quality evaluation. The power system network planning is by nature a complex, huge-scale, and mixed-objective optimization problem, especially when concerning its non-linear behavior and the requirements of future unknown loads. In this regard, the electric power utilities attempt to maintain a balance between the generation energy, the transmission capacity, and the needed demand. The main purpose of the current paper is to utilize modern modeling techniques and computational procedures, including the advanced deficit transmission system evaluation method and sparse-matrix network analysis algorithms, in order to evaluate, with sufficient accuracy, the deficit and reliability levels in practical real-life large-scale power systems. The new evaluation methodology is based on three quantities representing the relationship between the generation push in the grid, the maximum limitation of the transmission capacity, and the needed load. The main contribution of the paper is assessing the deficit transmission system index with novel formulas. [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 presents a power management (PMS)-based resource regulation system for combat robots equipped with batteries, supercapacitor banks, and solar cells. Hybrid energy storage source arrangements are needed to increase operational duration and increase the range of combat robots. Integration of multiple devices with different characteristics requires the implementation of a PMS. Distribution of the load of a combat robot by solving a power management problem, formulated as a finite quadratic program (CQP). Optimization of parameters is carried out, such as speed, drag coefficient and operating point of robot components, which are then regulated by the PMS controller. Data information during robot maneuvering by the PMS is measured and takes into account power management issues during the control period. In this research simulation, variations in weight factor parameters are given to determine various difficulties, namely regenerative power management. The simulation results show that the combat robot power management control system is capable of optimally generating electrical power loads for all components. In another study, a comparison of CQP performance in power management is comparable to benchmark performance after being analyzed based on nonlinear model predictive control. [ABSTRACT FROM AUTHOR]

China Power Grid is actively building a new energy-based ultra-high voltage grid system. Therefore, the researches on fire safety of power grid are of great importance. This paper firstly investigates the fire accident characteristics in the substation system. With the focuses on the transformer oil fires, the early detection and early warning, modification, fire monitoring and extinguishing systems of transformer oil are reviewed. It is found that the researches on flowing and jet fires should be reinforced while modified oil and pyrolysis gas detection can be applied for reducing the fire probability. Secondly, the fire risks and characteristics of cables are summarized for the transmission and distribution lines, and the methods of early warning, fire prevention and rescue are analyzed. For the wildfire threatening the transmission and distribution cables, the characteristics of wildfire and corresponding firefighting methods are reviewed. The water mist and liquid nitrogen are identified as the most effective ways of extinguishing cable fires and advanced fire detection and long-range drone fire extinguishing technologies should be improved for wildfires. Finally, the thermal runaway mechanism and fire characteristics of LIB in the energy storage system are summarized, and the difficulties in fire extinguishing are discussed. The application of the existing fire detection system in the field of LIB is proposed, and the early warning indicators for intelligent fire protection are introduced. In the future, the intelligent fire protection systems will improve the safety of energy storage systems, and efficient test platforms and reliable test standards will continue to be demanded to reduce the likelihood of thermal runaway and fire severity. [ABSTRACT FROM AUTHOR]

Wide Area Monitoring System (WAMS) using Phasor Measurement Unit (PMU) have been widely implemented in power systems. Due to its voltage and current measurements accuracy and precision, PMU can be adopted into power system defense plan as well as WAMS. However, there are considerations of the PMU data acquisition to be able to deliver performing analysis of the electrical power system, i.e.: the synchronization of data acquisition time, reporting rate effect, data sample acquisition, and data acquisition range. This paper addresses problems in PMU data collection and method to solve them prior to carrying out analysis to achieve reliable results. Further, the proposed method has been exercised and implemented in actual power systems accordingly the data collection issues in PMU for WAMS analysis have been solved. In contrast to other studies, this research offers insight into data collections and its solutions before they are examined. [ABSTRACT FROM AUTHOR]

The growing integration of renewable energy sources, especially offshore wind (OSW), is introducing frequency stability challenges to electric power grids. This paper presents a novel hybrid deloading control strategy that enables modular multilevel converter (MMC)-based wind energy conversion systems (WECSs) to actively contribute to grid frequency regulation. This research investigates a permanent-magnet synchronous generator (PMSG)-based direct-drive configuration, sourced from the International Energy Agency's (IEA's) 15 MW reference turbine model. Specifically, phase-locked loop (PLL)-free grid-forming (GFM) control is employed via the grid-side converter (GSC), and DC-link voltage control is realized through the machine-side converter (MSC), both of which boost the energy support for the integrated AC grid's frequency stability. This control strategy combines the benefits of over-speeding and pitch control modes, facilitating smooth transitions between different modes based on real-time wind speed measurements. In addition, the practical challenges of MMCs, such as circulating currents and capacitor voltage imbalances, are addressed. Numerical simulations under varying wind speeds and loading conditions validate the enhanced frequency regulation capability of the proposed approach. [ABSTRACT FROM AUTHOR]

The solar array drive assembly (SADA) slip ring is a critical link that provides electrical power and electric signal transmission between solar arrays and satellite power systems, which is prone to arc faults in the space environment. If these arc faults cannot be detected and eliminated quickly enough, they will seriously threaten the safety of the satellite power system and the satellite. In this paper, a fast arc detection method based on fractal dimension is proposed that adapts to different operating modes of power systems. The detection method collects the current differential signal data flowing through the SADA slip ring, and, according to the trend of the fractal dimension change in this signal, the fault identification algorithm is designed for different operating modes of the power system to achieve real-time and rapid identification of arc faults. Finally, the effectiveness of the proposed method is demonstrated using test data under several different fault conditions. [ABSTRACT FROM AUTHOR]

Deviations of power quality indices (PQI) from standard values in power supply systems of industrial consumers lead to defective products, complete shutdown of production processes, and significant damage. At the same time, the PQI requirements vary depending on the industrial consumer, which is due to different kinds, types, and composition of essential electrical loads. To ensure their reliable operation, it is crucial to introduce automatic PQI control devices, which evaluate the extent of distortion of the sinusoidal voltage waveform of a three-phase system. This allows the power dispatchers of grid companies and industrial enterprises to quickly make decisions on the measures to be taken in external and internal power supply networks to ensure that the PQI values are within the acceptable range. This paper proposes the use of an integrated indicator to assess the extent of distortion of the sinusoidal voltage waveform in a three-phase system. This indicator is based on the use of the magnitude of the ratio of complex amplitudes of the forward and reverse rotation of the space vector. In the study discussed, block diagrams of algorithms and flowcharts of automatic PQI control devices are developed, which implement parametric and nonparametric multiple-hypothesis sequential analysis using an integrated indicator. In this case, Palmer's algorithm and the nearest neighbor method are used. The calculations demonstrate that the developed algorithms have high speed and high performance in detecting deviations of the electrical power quality. [ABSTRACT FROM AUTHOR]

With the progress of modern times, automobile technology has become integral to human society. At the same time, the need for energy has also grown. In parallel, the total amount of waste energy that is liberated from different parts of the automobile has also increased. In this ever-increasing energy demand pool, future energy shortages and environmental pollution are the primary concerns. A thermoelectric generator (TEG) is a promising technology that utilizes waste heat and converts it into useful electrical power, which can reduce fuel consumption to a significant extent. This paper comprehensively reviews automobile thermoelectric generators and their technological advancements. The review begins by classifying different waste heat technologies and discussing the superiority of TEGs over the other existing technologies. Then, we demonstrate the basic concept of and advancements in new high-performance TEG materials. Following that, improvements and associated challenges with various aspects, such as the heat exchanger design, including metal foam, extended body, intermediate fluid and heat pipe, leg geometry design, segmentation, and multi-staging, are discussed extensively. Finally, the present study highlights research guidelines for TEG design, research gaps, and future directions for innovative works in automobile TEG technologies. [ABSTRACT FROM AUTHOR]

The regulation of tie-line electricity flow and frequency of electrical power systems (EPS) is crucial for ensuring their robustness to parameter changes and efficient management of disturbances. To this end, a novel cascade control design approach utilizing a serial Proportional-Integral-Derivative controller with a filter (PIDF) is proposed in this paper. The parameters of the controllers are derived analytically, and it is employed in both loops of the cascade control system to regulate the Load Frequency Control (LFC) of EPS. The implementation of PIDF controllers in both loops is utilized in the cascade control scheme for various power systems featuring different turbine topologies. This approach has been applied to single, and two-area power systems and has exhibited enhanced performance compared to other commonly referenced studies in the literature. To assess the effectiveness of the cascade control approach proposed performance metrics such as settling time, peak value (overshoot), and integral absolute error (IAE) value of frequency and tie-line power variations are utilized to gauge the system's response to a load perturbation. Additionally, the suggested cascade control technique and design process have undergone robustness testing with ±50% changes in system parameters to validate their reliability. [ABSTRACT FROM AUTHOR]

Marine electric propulsion is an important topic in the research of modern ships and underwater vehicles. The propulsion motor drives based on model predictive control (MPC) are becoming increasingly popular in marine propulsion systems as an emerging technology. However, the multi-objective optimization in conventional MPC requires cumbersome weighting factor tuning. The relatively large computational cost is also detrimental to the industrial application of MPC. Aiming at reducing the computational complexity of multi-objective optimization without weighting factors, this paper proposes an enhanced ranking-based MPC method for induction motor drives in marine electric power propulsion. The presented control set pre-optimization aims to reduce the computational complexity of enumeration and ranking. Based on the sign of torque prediction deviation, the proposed method avoids enumerating all fundamental voltage vectors. Consequently, the number of candidate elements in the initial control set are reduced to four without excessively excluding feasible solutions. By converting predicted numerical errors into ranking results, the proposed MPC seeks the optimal solution among the candidates through improved ranking evaluation. Considering the situation of simultaneous optimal ranking, the normalization error judgment is developed to further optimize the optimal solution selection process. The simulation and experimental results confirm that the proposed MPC is simple and effective. Without the involvement of tuning the weighting factors, the proposed method achieves good performance. [ABSTRACT FROM AUTHOR]