Mass Impregnated PPLP cable, which is applied to various high-voltage direct current (HVDC) projects due to its excellent dielectric and temperature properties, has a problem wherein voids are formed inside the butt-gap due to cavitation. However, there has been no previous research into technology for void defect identification and insulation diagnosis on HVDC MI-PPLP cables. In this paper, to propose an insulation diagnosis method for void defects in HVDC MI-PPLP cable, the direct current (DC) void discharge patterns were analyzed according to the specimen temperature and the magnitude of applied voltage using the pulse sequence analysis method. In addition, to confirm the pre-symptoms of dielectric breakdown in MI-PPLP cable due to DC void discharge, partial discharge patterns were analyzed continuously until dielectric breakdown occurred. From the experimental results, DC void discharge patterns of the same shape were obtained regardless of the specimen temperature and the magnitud... [more]

Solutions for the maintenance of safety in an isolated working face has not been well achieved; this is attributed to its unique overburden structure and the strong mining-induced stress during the advancement. This paper is devoted to filling this research gap and is based on the case study of LW 10304 in the Xinglongzhuang Coal Mine, in China. The overburden structure and stress distribution characteristics of this isolated working face were theoretically investigated, followed by the development of a comprehensive identification method. The research results showed the following: (1) The overburden strata of LW 10304 is in the form of a short “T” shape and the stress increment is featured with the overall “saddle” shape before the extraction of the isolated working face. During this period, the lower key strata and main key strata affect the stress level at the two ends and the central part of the working face, respectively; (2) Both the frequency and energy of micro-earthquakes in t... [more]

The key to achieving smart heating is the rational use of large amounts of data from the heating network. However, many current relevant studies based on generalized mathematical methods are unable to accurately describe the physical relationships between pipe network variables. In order to solve this problem, this paper proposes a new time-series fluctuation research method, which can be applied to the measured data of the hot water heating pipe network. This method is a new approach to identifying step data. Then, we propose the concept of time-series disturbance to quantify the degree of data anomaly. Finally, the results of a case study demonstrate the transfer process of a significant disturbance in the pipe network from the supply end to the return end. The time-series fluctuation method in this paper precisely describes two physical relationships between heating system variables and provides a feasible and convenient new research idea for self-perception and self-analysis of sma... [more]

Object detection of overhead transmission lines is a solution for promoting inspection efficiency for power companies. However, aerial images contain many complex backgrounds and small objects, and traditional algorithms are incompetent in the identification of details of power transmission lines accurately. To address this problem, this paper develops an object detection method based on optimized You Only Look Once v5-small (YOLOv5s). This method is designed to be engineering-friendly, with the objective of maximal detection accuracy and computation simplicity. Firstly, to improve the detecting accuracy of small objects, a larger scale detection layer and jump connections are added to the network. Secondly, a self-attention mechanism is adopted to merge the feature relationships between spatial and channel dimensions, which could suppress the interference of complex backgrounds and boost the salience of objects. In addition, a small object enhanced Complete Intersection over Union (CI... [more]

This article aims to provide a technique for identifying and categorizing interturn insulation problems in variable-speed motor drives by combining Salp Swarm Optimization (SSO) with Recurrent Neural Network (RNN). The goal of the proposed technique is to detect and classify Asynchronous Motor faults at their early stages, under both normal and abnormal operating conditions. The proposed technique uses a recurrent neural network in two phases to identify and label interturn insulation concerns, with the first phase being utilised to establish whether or not the motors are healthy. In the second step, it discovers and categorises potentially dangerous interturn errors. The SSO approach is used in the second phase of the recurrent neural network learning procedure, with the goal function of minimizing error in mind. The proposed CSSRN technique simplifies the system for detecting and categorizing the interturn insulation issue, resulting in increased system precision. In addition, the pr... [more]

The engine fuel control system plays a crucial role in engine performance and fuel economy. Fuel control, in traditional engine control systems, is carried out by means of sensor-based control methods, which correct the fuel flow rate through correlations or scheduled parameters in order to reduce the error between a measured parameter and its desired value. In the presence of component degradation, however, the relationship between the engine measurable parameters and performance may lead to an increase in the control error. In this research, linear models for advanced control systems and for direct fuel control in the presence of components degradation are proposed, with the main objective being to directly predict and correct fuel consumption in the presence of degradation instead of adopting measurable parameters. Two techniques were adopted for model linearization: Small Perturbation and System Identification. Results showed that both models are characterized by high accuracy in p... [more]

The study on the numerical model of communication processes implemented in RFID systems, in which textile electronic (RFIDtex) tags are used, is presented in the paper. The efficiency analysis covers the case of dynamic identification of a large amount of RFIDtex tags that are located in a spatial interrogation zone of a typical Internet of Textile Things (IoTT) application. Simulations carried out in order to verify the efficiency of the identification process are confirmed by measurements on the dedicated laboratory stand. Since the application of the experiment is located in the area of a maintenance-free store to detect and distinguish textile products, particular attention is paid to reconstruction of conditions and object arrangements that are typical for this type of space. The model and experiment are developed on the basis of RFIDtex transponders that are restricted under the patent claim PL231291. The obtained results prove that within the scope of the assumed number of RFIDt... [more]

The converter is an important component of a wind turbine, and its control system has a significant impact on the dynamic output characteristics of the wind turbine. For the double-fed induction generator (DFIG) converter, the control parameter identification method is proposed. In this paper, a detailed dynamic model of DFIG with the converter is built, and the trajectory sensitivity method is used to study the observation points that are sensitive to the change of control parameters as the observation quantity for control parameter identification; the Whale Optimization Algorithm (WOA) is used to study the converter control system parameters that dominate the output characteristics of DFIG in the dynamic full-process simulation. To validate the proposed method, four classical test functions are used to verify the effectiveness of the algorithm, and the control parameters are identified by setting a three-phase grounded short-circuit fault under maximum power point tracking (MPPT), an... [more]

The present paper deals with the external identification of a reciprocal, special passive, 2n-port network under measurement uncertainties. In the present context, the multiport model is represented by an admittance matrix and the condition that the network is ‘reciprocal special passive’ refers to the assumption that the real part of the admittance matrix is symmetric and positive-definite. The key point is to reformulate the identification problem as a matrix optimization program over the matrix manifold S+(2n)×S(2n). The optimization problem requires a least-squares criterion function designed to cope with over-determinacy due to the incoherent data pairs whose cardinality exceeds the problem’s number of degrees of freedom. The present paper also proposes a numerical solution to such an optimization problem based on the Riemannian-gradient steepest descent method. The numerical results show that the proposed method is effective as long as reasonable measurement error levels and prob... [more]

Environmental concerns and economic constraints have led to increasing installations of mixed conductor circuits comprising underground cables (UGCs) and overhead transmission lines (OHLs). Faults on the OHL sections of such circuits are usually temporary, while there is a higher probability that faults on UGC sections are permanent. To maintain power system reliability and security, auto-reclose (AR) schemes are typically implemented to minimize outage duration after temporary OHL faults while blocking AR for UGC faults to prevent equipment damage. AR of a hybrid UCG−OHL transmission line, therefore, requires effective identification of the faulty section. However, the different electrical characteristics of UGC and OHL sections present significant challenges to existing protection and fault location methods. This paper presents a selective AR scheme for mixed conductor circuits based on the evaluation of differential currents in multiple defined protection zones, using distributed cu... [more]

Thermal abuse of lithium-ion batteries (LIBs) leads to the emission of gases, solids, fires and/or explosions. Therefore, it is essential to define the temperatures at which key events occur (i.e., CID activation, venting, and thermal runaway (TR)) and to identify the related emissions for identifying the hazards to which people and especially rescue teams are exposed. For this purpose, thermal abuse tests were performed on commercial lithium nickel cobalt aluminum oxide (NCA) 18650 cells at 50% state of charge in a reactor connected to an FT-IR spectrometer by varying test conditions (feed gas of N2 or air; heating rates of 5 or 10 °C/min until 300 °C). In particular, the concentrations of the gases and the composition of the condensed-phase emissions were estimated. As regards gases, a high concentration (1695 ppmv) of hydrofluoric acid (HF) was measured, while the emissions of condensed matter consisted of organic compounds such as polyethylene oxide and paraffin oil, and inorganic... [more]

The precise control of output power by grid-connected converters relies on the correct identification and tracking of a grid voltage’s phase at the converter terminal. During severe grid faults, large disturbances cause the converter’s operating point to move away from the stable equilibrium point during normal operation. This leads to oscillations of both the active and reactive power fed into the grid. Using large-signal modelling, this study investigated the converter’s dynamic processes during and after such fault situations. The investigation considered the influence of the converter’s phase-locked loop (PLL), responsible for phase tracking, as well as that of the DC link on the converter-grid system, which has a major influence on the active power exchange with the grid. On this basis, this study also focused on the reactive current reference’s influence during and after fault clearing. Furthermore, an easily implementable strategy for reactive current injection, leading to minim... [more]

This article introduces a new method for identifying anchor damage faults in fiber composite submarine cables. The method combines the Volterra model of Variation Mode Decomposition (VMD) with singular value entropy to improve the accuracy of fault identification. First, the submarine cable vibration signal is decomposed into various Intrinsic Mode Functions (IMFs) using VMD. Then, a Volterra adaptive prediction model is established by reconstructing the phase space of each IMF, and the model parameters are used to form an initial feature vector matrix. Next, the feature vector matrix is subjected to singular value decomposition to extract the singular value entropy that reflects the fault characteristics of the submarine cable. Finally, singular value entropy is used as a feature value to input into the Support Vector Machine (SVM) for classification. Compared with Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD), the proposed method achieves a highe... [more]

Energy systems need a complete decarbonization within the next 20−30 years, calling for the introduction of CO2-free renewable energy sources (RES). All final uses must face this challenge, now finally including the transportation sector which should mostly be electrified. This option could constitute both a challenge and an opportunity for the electric grid. In fact, connection to the grid of all electric vehicles (EVs) together with their electricity storage systems (ESSs) could reduce issues due to the nonprogrammable use of RES in electricity production; to this aim, sufficiently smart bi-directional vehicle-to-grid technologies (V2G) have to be designed and widely installed. Parallelly, electric grid capabilities must become fully bidirectional in all nodes, both physically and in terms of ICT capabilities (so-called smart grid paradigm). In the meanwhile, some of those V2G technologies may already be locally implemented in individual home contexts. Following previous research act... [more]

Power capacitors suffer multiple impulse voltages during their lifetime. With the multiple impulse voltage aging, the internal insulation, oil-film dielectric may deteriorate and even fail in the early stage, which is called accumulative effect. Hence, the time-domain dielectric response of oil-film dielectric with multiple impulse voltage aging is studied in this paper. At first, the procedure of the preparation of the tested samples were introduced. Secondly, an aging platform, impulse voltage generator was built to test the accumulative effect of capacitor under multiple impulse voltage. Then, a device was used to test the time-domain dielectric response (polarization depolarization current, PDC) of oil-film dielectric in different aging states. And finally, according to the PDC data, extended Debye model and characteristic parameters were obtained by matrix pencil algorithm identification. The results indicated that with the increase of impulse voltage times, the time-domain dielec... [more]

The optimization of photovoltaic (PV) systems relies on the development of an accurate model of the parameter values for the solar/PV generating units. This work proposes a modified artificial jellyfish search optimizer (MJSO) with a novel premature convergence strategy (PCS) to define effectively the unknown parameters of PV systems. The PCS works on preserving the diversity among the members of the population while accelerating the convergence toward the best solution based on two motions: (i) moving the current solution between two particles selected randomly from the population, and (ii) searching for better solutions between the best-so-far one and a random one from the population. To confirm its efficacy, the proposed method is validated on three different PV technologies and is being compared with some of the latest competitive computational frameworks. The numerical simulations and results confirm the dominance of the proposed algorithm in terms of the accuracy of the final res... [more]

Worst-case execution time (WCET) is an important metric in real-time systems that helps in energy usage modeling and predefined execution time requirement evaluation. While basic timing analysis relies on execution path identification and its length evaluation, multi-thread code with critical section usage brings additional complications and requires analysis of resource-waiting time estimation. In this paper, we solve a problem of worst-case execution time overestimation reduction in situations when multiple threads are executing loops with the same critical section usage in each iteration. The experiment showed the worst-case execution time does not take into account the proportion between computational and critical sections; therefore, we proposed a new worst-case execution time calculation model to reduce the overestimation. The proposed model results prove to reduce the overestimation on average by half in comparison to the theoretical model. Therefore, this leads to more accurate... [more]

This paper reviews the fundamentals of the Exergy Cost Theory, an energy cost accounting methodology to evaluate the physical costs of products of energy systems and their associated waste. Besides, a mathematical and computationally approach is presented, which will allow the practitioner to carry out studies on production systems regardless of their structural complexity. The exergy cost theory was proposed in 1986 by Valero et al. in their “General theory of exergy savings”. It has been recognized as a powerful tool in the analysis of energy systems and has been applied to the evaluation of energy saving alternatives, local optimisation, thermoeconomic diagnosis, or industrial symbiosis. The waste cost formation process is presented from a thermodynamic perspective rather than the economist’s approach. It is proposed to consider waste as external irreversibilities occurring in plant processes. A new concept, called irreversibility carrier, is introduced, which will allow the identif... [more]

The article deals with issues related to the processes occurring in the wear result of steel surfaces of machine components in the presence of mineral grains. This type of destruction of cooperating surfaces usually takes place during the development of roadways or during mining of coal with use of longwall methods. Wear tests were carried out using the author’s ring-on-ring test stand, on which the conditions of real wear of machine components in the presence of rocks were simulated. An abrasive material based on clayey rocks with an admixture of carbonaceous substance was used in the tests. Based on the analyses, it was found that the obtained results related to the damages are typical for wear mechanisms: microcracking and low-cycle fatigue. On the surface of the steel samples, numerous effects of micro-cutting and chipping could be observed, which were the result of the clayey impact of wear products and grains of the mineral substance. Under friction, a part of the abrasive and th... [more]

In this paper, a brief survey of measurable factors affecting the adoption of cybersecurity enhancement methods in the smart grid is provided. From a practical point of view, it is a key point to determine to what degree the cyber resilience of power systems can be improved using cost-effective resilience enhancement methods. Numerous attempts have been made to the vital resilience of the smart grid against cyber-attacks. The recently proposed cybersecurity methods are considered in this paper, and their accuracies, computational time, and robustness against external factors in detecting and identifying False Data Injection (FDI) attacks are evaluated. There is no all-inclusive solution to fit all power systems requirements. Therefore, the recently proposed cyber-attack detection and identification methods are quantitatively compared and discussed.

The article presents the results obtained during the inspection of the load-bearing structure of a power unit that suffered from fire. The inspection, consisting in the assessment of both the structure’s technical condition and durability of welded joints, was performed on seven height levels of the power unit. The vibration spectrum of the unit’s steel structure was analyzed, and frequency characteristics were, thus, obtained for individual measurement levels. Thermal vision measurements were also performed in the unit’s all connection points to check for possible unsealing of some elements in the boiler island of the inspected power unit. The next stage consisted of performing strength calculations of the steel structure with a goal to estimate the structure’s stress state. The conclusions contain suggestions for modernization of welded joints in order to maintain the power unit’s design strength.

The authors seek to investigate the characteristics of outage-causing faults that can be observed in a short time frame after their occurrence: waveform of the voltages and currents. The aim is to identify which characteristics can be used to estimate the failure type immediately after its occurrence. This paper lays the groundwork to determine which features display a stronger relation to four failure types with the aim of using this information in a later work, not presented in this paper, aimed at designing a reliable failure type estimator from readily available data. This paper focuses on the most common failures of the underground cable MV networks in Portugal: cable insulation; cable joint; secondary substation busbar; and excavation-motivated failures. A set of 206 waveform records of real underground MV network failures was available for analysis. After investigating the waveforms, the authors identified seven waveform characteristics which can be used for failure type estimat... [more]

The degradation of lithium-ion cells with respect to increases of internal resistance (IR) has negative implications for rapid charging protocols, thermal management and power output of cells. Despite this, IR receives much less attention than capacity degradation in Li-ion cell research. Building on recent developments on ‘knee’ identification for capacity degradation curves, we propose the new concepts of ‘elbow-point’ and ‘elbow-onset’ for IR rise curves, and a robust identification algorithm for those variables. We report on the relations between capacity’s knees, IR’s elbows and end of life for the large dataset of the study. We enhance our discussion with two applications. We use neural network techniques to build independent state of health capacity and IR predictor models achieving a mean absolute percentage error (MAPE) of 0.4% and 1.6%, respectively, and an overall root mean squared error below 0.0061. A relevance vector machine, using the first 50 cycles of life data, is emp... [more]

In order to locate the short-circuit fault in power cable systems accurately and in a timely manner, a novel fault location method based on traveling waves is proposed, which has been improved by unsupervised learning algorithms. There are three main steps of the method: (1) build a matrix of the traveling waves associated with the sheath currents of the cables; (2) cluster the data in the matrix according to its density level and the stability, using Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN); (3) search for the characteristic cluster point(s) of the two branch clusters with the smallest density level to identify the arrival time of the traveling wave. The main improvement is that high-dimensional data can be directly used for the clustering, making the method more effective and accurate. A Power System Computer Aided Design (PSCAD) simulation has been carried out for typical power cable circuits. The results indicate that the hierarchical struc... [more]

With the development of new energy vehicle technology, battery management systems used to monitor the state of the battery have been widely researched. The accuracy of the battery status assessment to a great extent depends on the accuracy of the battery model parameters. This paper proposes an improved method for parameter identification and state-of-charge (SOC) estimation for lithium-ion batteries. Using a two-order equivalent circuit model, the battery model is divided into two parts based on fast dynamics and slow dynamics. The recursive least squares method is used to identify parameters of the battery, and then the SOC and the open-circuit voltage of the model is estimated with the extended Kalman filter. The two-module voltages are calculated using estimated open circuit voltage and initial parameters, and model parameters are constantly updated during iteration. The proposed method can be used to estimate the parameters and the SOC in real time, which does not need to know the... [more]