Non-Intrusive Load Monitoring (NILM) refers to the analysis of the aggregated current and voltage measurements of Home Electrical Appliances (HEAs) recorded by the house electrical panel. Such methods aim to identify each HEA for a better control of the energy consumption and for future smart grid applications. Here, we are interested in an event-based NILM pipeline, and particularly in the HEAs’ recognition step. This paper focuses on the selection of relevant and understandable features for efficiently discriminating distinct HEAs. Our contributions are manifold. First, we introduce a new publicly available annotated dataset of individual HEAs described by a large set of electrical features computed from current and voltage measurements in steady-state conditions. Second, we investigate through a comparative evaluation a large number of new methods resulting from the combination of different feature selection techniques with several classification algorithms. To this end, we also inv... [more]

This paper presents the use of multi-criteria decision-making (MCDM) for the evaluation of smart cities. During the development of the method, the importance of the decision-making approach in the linear ordering of cities was presented. The method of using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was proposed for the preparation of ranking. The method was verified by the application in the measurement of energy performance in smart cities. The authors conducted a literature review of research papers related to urban energy and MCDM published in the period from 2010 to 2020. The paper uses data from the World Council on City Data (WCCD). The research conducted allowed for the identification of the most popular MCDM techniques in the field of urban energy such as TOPSIS, AHP and DEA. The TOPSIS technique was used to organize and group the analyzed cities. Porto took the top position, whereas Buenos Aries was the last.

Renewable energy sources help in decreasing negative environmental impacts and in reducing energy-import dependency. Among all renewable energy segments, photovoltaic panel (PV) installations are one of the fastest-growing. Growing concern about climate change, as well as public policies promoting the development of PV installations, have changed consumers’ behaviors and attitudes. This study uses the theory of consumption values to identify factors influencing consumers’ choice behavior regarding photovoltaic panel installations. There is little research on consumers’ perception of value related to green energy in Poland, especially in the case of photovoltaic panels. We fill this cognitive gap by testing an extended green consumption values model that includes functional, social, emotional, conditional, epistemic, and environmental values. The research was conducted on 250 Polish consumers using a self-administered questionnaire as the research tool. The results of structural equatio... [more]

This work aims at developing a methodology for the assessment of district heating (DH) potential through the mapping of energy demand and waste heat sources. The presented method is then applied to the Metropolitan City of Milano as a case study in order to investigate the current and, especially, the future sustainability of DH with the foreseen building refurbishment and consequent heat demand reduction. The first step is the identification of the areas the most interesting from a heat density and an economic point of view through a clustering algorithm, in which lies the main novelty of the work. The potential is then assessed by investigating their synergy with the available heat sources, which are mapped and analyzed in terms of recoverable thermal energy and costs. In future scenarios with foreseen heat demand reduction, low-temperature networks and excess heat sources are considered, such as metro stations and datacenters, together with the conventional sources, such as thermoel... [more]

Smart meters are used to measure the energy consumption of households. Specifically, within the energy consumption task, a smart meter must be used for load forecasting, the reduction in consumer bills as well as the reduction in grid distortions. Smart meters can be used to disaggregate the energy consumption at the device level. In this paper, we investigated the potential of identifying the multimedia content played by a TV or monitor device using the central house’s smart meter measuring the aggregated energy consumption from all working appliances of the household. The proposed architecture was based on the elastic matching of aggregated energy signal frames with 20 reference TV channel signals. Different elastic matching algorithms, which use symmetric distance measures, were used with the best achieved video content identification accuracy of 93.6% using the MVM algorithm.

Some inter-salt shale reservoirs have high oil saturations but the soluble salts in their complex lithology pose considerable challenges to their production. Low-field nuclear magnetic resonance (NMR) has been widely used in evaluating physical properties, fluid characteristics, and fluid saturation of conventional oil and gas reservoirs as well as common shale reservoirs. However, the fluid distribution analysis and fluid saturation calculations in inter-salt shale based on NMR results have not been investigated because of existing technical difficulties. Herein, to explore the fluid distribution patterns and movable oil saturation of the inter-salt shale, a specific experimental scheme was designed which is based on the joint adaptation of multi-state saturation, multi-temperature heating, and NMR measurements. This novel approach was applied to the inter-salt shale core samples from the Qianjiang Sag of the Jianghan Basin in China. The experiments were conducted using two sets of in... [more]

Several high voltage condenser type OIP (oil impregnated paper) bushings used in the electrical industry are filled with dodecylbenzene, because of its ability to absorb hydrogen formed by corona partial discharges in the thick paper insulation of these pieces of equipment. Some of them form large quantities of ethane, raising the concern of overheating faults in their paper insulation, which may be risky for their safe operation in service. The article presents dissolved gas analysis results of oil samples taken from the bushings with high ethane formation, together with results of laboratory tests of stray gassing of dodecylbenzene performed according to CIGRE procedure. By using Duval Pentagon 2 it is possible to compare patterns in the laboratory and in bushings and evaluate the temperature range of possible defects. Stray gassing/overheating of dodecylbenzene in bushings within the stray gassing temperature range and whatever the possible other causes, is not a concern for their s... [more]

This paper presents a comparative analysis of six sampling techniques to identify an efficient and accurate sampling technique to be applied to probabilistic voltage stability assessment in large-scale power systems. In this study, six different sampling techniques are investigated and compared to each other in terms of their accuracy and efficiency, including Monte Carlo (MC), three versions of Quasi-Monte Carlo (QMC), i.e., Sobol, Halton, and Latin Hypercube, Markov Chain MC (MCMC), and importance sampling (IS) technique, to evaluate their suitability for application with probabilistic voltage stability analysis in large-scale uncertain power systems. The coefficient of determination (R2) and root mean square error (RMSE) are calculated to measure the accuracy and the efficiency of the sampling techniques compared to each other. All the six sampling techniques provide more than 99% accuracy by producing a large number of wind speed random samples (8760 samples). In terms of efficienc... [more]

This paper proposes an algorithm for detection and identification of the location of short circuit faults in islanded AC microgrids (MGs) with meshed topology. Considering the low level of fault current and dependency of the current angle on the control strategies, the legacy overcurrent protection schemes are not effective in in islanded MGs. To overcome this issue, the proposed algorithm detects faults based on the rms voltages of the distributed energy resources (DERs) by means of support vector machine classifiers. Upon detection of a fault, the DER which is electrically closest to the fault injects three interharmonic currents. The faulty zone is identified by comparing the magnitude of the interharmonic currents flowing through each zone. Then, the second DER connected to the faulty zone injects distinctive interharmonic currents and the resulting interharmonic voltages are measured at the terminal of each of these DERs. Using the interharmonic voltages as its features, a multi-c... [more]

In this paper, a two-step tuning strategy of a finite element (FE) model of a bridge with pot bearings exposed to mining-triggered tremors of various intensities is proposed. In the study, a reinforced concrete bridge 160 m long is considered. Once the modal identification of the bridge was experimentally carried out based on low-energy ambient vibrations, the FE model was tuned by replacing the free-bearing sliding with a Coulomb friction-regularized model. This model of friction split the tangential relative displacement rates between contacting surfaces into a reversible elastic part and irreversible sliding. The elastic microslip (spring-like behavior) prior to macrosliding can be explained by the deformation of asperities (roughness of contacting surfaces on the microscopic scale). The proposed model allows for accurate sliding bearing performance simulation under both low-energy and high-energy mining-induced tremors. In the first step of the FE model tuning strategy, the elastic... [more]

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]