The aim and contribution of this paper is to identify with Duval Pentagon 2 the stray gassing (SG) patterns of inhibited and uninhibited mineral oils in transformers in service and in the well-established laboratory SG tests of CIGRE and ASTM, so that SG in transformers can be easily distinguished from the other types of faults occurring in them. The SG test of IEC 60296-2020 is inadequate or much less effective for that purpose.

This paper presents an experience in the design and implementation of the condition-monitoring system for the synchronous generators whose primary purpose is to record data for the identification of the capability limits of the P−Q diagram of three generators in hydro power-plant. Paper presents details about the monitoring system, the underlying theory of the identification of the synchronous generator model with a focus on the calculation of the capability limits in the P−Q diagram. Furthermore, a computationally efficient method for the representation of capability limits suitable for the implementation within the industrial automation and control system of the power-plant is described in detail. Finally, the capability diagrams for three generators were implemented in the power-plant supervisory control and data acquisition system (SCADA) system.

The lithium-ion battery is a complicated non-linear system with multi electrochemical processes including mass and charge conservations as well as electrochemical kinetics. The calculation process of the electrochemical model depends on an in-depth understanding of the physicochemical characteristics and parameters, which can be costly and time-consuming. We investigated the electrochemical modeling, reduction, and identification methods of the lithium-ion battery from the electrode-level to the system-level. A reduced 9th order linear model was proposed using electrode-level physicochemical modeling and the cell-level mathematical reduction method. The data-driven predictor-based subspace identification algorithm was presented for the estimation of lithium-ion battery model in the system-level. The effectiveness of the proposed modeling and identification methods was validated in an experimental study based on LiFePO4 cells. The accuracy and dynamic characteristics of the identified m... [more]

State-of-the-art methods for determining thermal impedance networks for IGBT (Insulated Gate Bipolar Transistor) modules usually involves the establishment of the relationship between the measured transistor or diode voltage and temperature under homogenous temperature distribution across the IGBT module. The junction temperature is recomputed from the established voltage−temperature relationship and used in determining the thermal impedance network. This method requires accurate measurement of voltage drop across the transistors and diodes under specific designed heating and cooling profiles. Validation of the junction temperature is usually done using infrared camera or sensors placed close to the transistors or diodes (in some cases and open IGBT module) so that the measured temperature is as close to the junction as possible. In this paper, we propose an alternative method for determining the IGBT thermal impedance network using the principles of least squares. This method uses mea... [more]

The analysis of the fault propagation path of transmission lines and the method of identification of vulnerable lines during typhoon weather conditions is of great significance. In this context, this paper introduces the failure probability model of transmission lines under such conditions by considering both wind speed and the load of the lines. The Monte Carlo simulation (MCS) and the DC model based on OPA are applied to simulate the failure of transmission lines. The cascading failure state transition diagram (CFSTD) is proposed based on the failure chains and the criticality ranking of nodes in CFSTD by the average weight coefficient (AWC) for identifying vulnerable lines of the power grid under such conditions. A new weight in CFSTD is proposed to describe the vulnerability of each line and a new resilience index is used to assess the impacts of a typhoon on the system. The proposed method is demonstrated by using the modified IEEE 118-bus test system. Results show that the method... [more]

Today, hydrogen production plays an important part in the industry due to the increasing use of hydrogen in significant domains, such as chemistry, transportation, or energy. In this paper, we aim to design a numerical control solution based on the thermodynamic analysis of the pyrolysis reactions for hydrogen production and to present novel research developments that highlight industrial applications. Beginning with the evaluation of the technological aspects for the pyrolysis chemical process, the paper studies the thermodynamic evaluation of the system equilibrium for the pyrolysis reactions set, to recommend an appropriate automatic control solution for hydrogen pyrolysis installations. The numerical control architecture is organized on two levels, a control level dedicated to key technological parameters, and a supervisory decision level for optimizing the conversion performances of the pyrolysis process. The data employed for modelling, identification, control, and optimization t... [more]

Smart grid operation schemes can integrate prosumers by offering economic rewards in exchange for the desired response. In order to activate prosumers appropriately, such operation schemes require models of the dynamic uncertain price-response relationships. In this study, we combine the system identification of nonlinear dynamics with control (SINDyc) algorithm with Bayesian inference techniques based on Markov-chain Monte-Carlo sampling. We demonstrate this combination of two algorithms on an exemplary system in order to obtain parsimonious models alongside parameter uncertainty estimates. The precision of the identified models depends on the identification experiment and the parameterization of the algorithms. Such models may characterize the prosumer response and its uncertainty, thereby facilitating the integration of such entities into smart grid operation schemes.

This paper develops a model-based data driven algorithm for fault classification in proton exchange membrane fuel cells (PEMFCs). The proposed approach overcomes the drawbacks of voltage and current density assumptions in conventional model-based fault identification methods and data limitations in existing data driven approaches. This is achieved by developing a 3D model of fuel cells (FC) based on semi empirical model, analytical representation of electrochemical model, thermal model, and impedance model. The developed model is simulated for membrane drying and flooding faults in PEMFC and their effects are identified for the action of varying temperature, pressure, and relative humidity. The ohmic, concentration, activation and cell voltage losses for the simulated faults are observed and processed with wavelet transforms for feature extraction. Furthermore, the support vector machine learning algorithm is adapted to develop the proposed fault classification approach. The performanc... [more]

The number of globally deployed smart meters is rising, and so are the sampling rates at which they can meter electrical consumption data. As a consequence thereof, the technological foundation is established to track the power intake of buildings at sampling rates up to several k Hz . Processing raw signal waveforms at such rates, however, imposes a high resource demand on the metering devices and data processing algorithms alike. In fact, the ensuing resource demand often exceeds the capabilities of the embedded systems present in current-generation smart meters. Consequently, the majority of today’s energy data processing algorithms are confined to the use of RMS values of the data instead, reported once per second or even less frequently. This entirely eliminates the spectral characteristics of the signal waveform (i.e., waveform trajectories of electrical voltage, current, or power) from the data, despite the wealth of information they have been shown to contain about the o... [more]

District heating networks (DHNs) are essential municipal infrastructure in the north of China. Obtaining accurate resistance characteristics is a critical step to improve the operating regulation level of DHNs. In this paper, pipe hydraulic resistances (PHRs) are introduced to express the resistance characteristics. A hydraulic model of a DHN can be established by using observed data of pressures and discharges. The boundary nodes are taken as observed sites. After establishing a matrix equation and analyzing the rank of its coefficient matrix, the authors propose a method to determine all the PHRs uniquely, by using a small number of observed sites and operating conditions. Furthermore, when observed errors are introduced, the adverse impact can be weakened by increasing the number of operating conditions and the accuracy of observed devices. When the observed error ranges are 1% and 0.5%, the results show that the average relative errors of identified PHRs are 2.4% and 1.1% respectiv... [more]

This paper presents a comprehensive study on a novel voltage injection based offline parameter identification method for surface mounted permanent magnet synchronous motors (SPMSMs). It gives solutions to obtain stator resistance, d- and q-axes inductances, and permanent magnet (PM) flux linkage that are totally independent of current and speed controllers, and it is able to track variations in q-axis inductance caused by magnetic saturation. With the proposed voltage amplitude selection strategies, a closed-loop-like current and speed control is achieved throughout the identification process. It provides a marked difference compared with the existing methods that are based on open-loop voltage injection and renders a more simplified and industry-friendly solution compared with methods that rely on controllers. Inverter nonlinearity effect compensation is not required because its voltage error is removed by enabling the motor to function at a designed routine. The proposed method is va... [more]

This paper presents a critical review of the research conducted for modeling and controlling supercritical power plants. Thermal power plants are classified according to the boiler pressure to supercritical and subcritical. The modeling concepts and control strategies of supercritical generation units are far more complex than those of subcritical. On the other hand, supercritical generation technologies are more efficient and much cleaner than subcritical generation units. From a deep technical analysis of the literature, there is no review that is dedicated to models-based control of supercritical power plants and most previous reviews are found to be too general to modeling-based control of fossil fuelled energy sources. This review reports the advancements on modeling and control of supercritical and ultra-supercritical plants as cleaner generation technologies. The various published achievements for modeling supercritical and ultra-supercritical units have been reviewed. The contr... [more]

This paper proposes an approach to develop building dynamic thermal models that are of paramount importance for controller application. In this context, controller requires a low-order, computationally efficient, and accurate models to achieve higher performance. An efficient building model is developed by having proper structural knowledge of low-order model and identifying its parameter values. Simplified low-order systems can be developed using thermal network models using thermal resistances and capacitances. In order to determine the low-order model parameter values, a specific approach is proposed using a stochastic particle swarm optimization. This method provides a significant approximation of the parameters when compared to the reference model whilst allowing low-order model to achieve 40% to 50% computational efficiency than the reference one. Additionally, extensive simulations are carried to evaluate the proposed simplified model with solar radiation and identified model pa... [more]

Accurate dynamic models of supercapacitors (SCs) are a basis for the design, control and exploitation of the hybrid energy storage systems for electric vehicles. This paper concerns a fractional model of SC impedance, based on the Cole−Cole equation describing relaxation in electric double layer. This article provides a new method of identifying the parameters of fractional order model of SC impedance, performed without disconnecting the SC module from the energy storage system. The test drive for this purpose needs only the respect a few simple recommendations. The article presents the conditions of the mentioned test drive that will ensure the frequency spectra of the recorded signals lying in the bandwidth necessary for the correct identification of the model parameters. These parameters are determined by means of the Nelder−Mead simplex optimization method. The results of the identification described by the time method coincide with those obtained in the frequency domain. It has be... [more]

Deduplication of encrypted data is a significant function for both the privacy of stored data and efficient storage management. Several deduplication techniques have been designed to provide improved security or efficiency. In this study, we focus on the client-side deduplication technique, which has more advantages than the server-side deduplication technique, particularly in communication overhead, owing to conditional data transmissions. From a security perspective, poison, dictionary, and identification attacks are considered as threats against client-side deduplication. Unfortunately, in contrast to other attacks, identification attacks and the corresponding countermeasures have not been studied in depth. In identification attacks, an adversary tries to identify the existence of a specific file. Identification attacks should be countered because adversaries can use the attacks to break the privacy of the data owner. Therefore, in the literature, some counter-based countermeasures... [more]

The accurate measurement of on-state device voltage during power-cycling tests can deliver important information about the health of the tested power electronics components. In this article, we present the major aspects of how a power-cycling test can be set up to enable high-resolution device voltage monitoring, during both heating and cooling stages, and discuss the effect of some important parameters on the arising failure modes. The thermal transient of the component can also be captured in these setups. We show how the structure functions calculated from the captured thermal transients can be used to reveal the location of degradation in the module structure. Finally, the method for identification of bond-wire cracking and lift-off using only the measured voltage curves, is shown.

In accordance with European objectives, the Basilicata region intends to promote the use of energy systems and heat generators powered by lignocellulosic biomass, so the present study aimed to investigate the availability of logging residues and most suitable areas for the construction of bioenergy production plants. The life cycle assessment (LCA) methodology was employed to conduct an environmental impact assessment of the biomass distribution and its transport, and spatial LCA was used to evaluate the impact of regional transport. One cubic meter kilometer (m3 km−1) was used as the functional unit and a small lorry was considered for the transport. The results showed that the available harvesting residues amounted to 36,000 m3 and their loading environmental impact accounted for 349 mPt m−3. The impacts of transport (4.01 mPt m−3) ranged from 3.4 to 144,400 mPt km−1 forest parcel−1, mainly affecting human health (95%) and, second, the ecosystem quality (5%). Three possible sites for... [more]

Power restoring time in power distribution systems (PDS) can be minimized by using efficient fault localization techniques. This paper proposes a novel, robust and scalable cloud based internet of things (IoT) solution for identification and localization of faults in PDS. For this purpose, a new algorithm is developed that can detect single and multiple simultaneous faults in the presence of single and multiple device or sensor failures. The algorithm has utilized a zone based approach that divides a PDS into different zones. A current sensing device (CSD) was deployed at the boundary of a zone. The function of CSD is to provide time synchronized current measurements and communicate with a cloud server through an edge device (ED). Another contribution of this research work is the unique implementation of context aware policy (CAP) in ED. Due to CAP, only those measurements are transmitted to cloud server that differ from the previously transmitted measurements. The cloud server perform... [more]

Brazilian offshore potential exploration is still in its early stages, with no single offshore park in operation or being implemented. Unlike the already identified onshore wind potential—with over 14 GW installed in the form of onshore wind turbines—offshore wind potential research is absent and restricted to limited areas. In this context, this study aims to identify offshore wind potential throughout the Brazilian coast for electricity generation. The research method took into account the average annual wind velocity records as 100 m/s, as well as bathymetry and the distance from the coast baseline, to classify areas displaying the greatest potential, applying an analytic hierarchy process (AHP) to the geographic information system for the identification of potential offshore wind energy exploration sites. Environmental conservation units were considered exclusion areas. The installable capacity using aerogenerators was estimated at 3 TW, while an annual average power production of... [more]

Since households are one of the most energy-intensive sectors in Europe, retrofit of dwellings is promoted to increase energy efficiency. Recent research, however, shows that the energy performance after retrofit does not always meet the target values, which can be caused by amongst other things, a deviating building envelope performance. This paper compares the theoretical and measured building envelope performance for a real-life case study in post-retrofit state, in order to illustrate the limitations of calculation methods and characterization models. First, the performance is evaluated on building scale by verifying the correspondence between the default theoretical heat loss coefficient (HLC) and the measured HLC, which was determined by following the guidelines formulated within IEA EBC Annex 58 and Annex 71. In order to illustrate the limitations of the standard calculation method in real-life conditions, the theoretical variability of the HLC is evaluated, generated by variati... [more]

Energy conservation is attracting more attention to achieve a reduced lifecycle system cost level while enabling environmentally friendly characteristics. Conventional research mainly concentrates on energy-saving speed profiles, where the energy level evaluation of the timetable is usually considered separately. This paper integrates the train driving control optimization and the timetable characteristics by analyzing the achievable tractive energy conservation performance and the corresponding boundaries. A calculation method for energy efficient driving control solution is proposed based on the Bacterial Foraging Optimization (BFO) strategy, which is utilized to carry out batch processing with timetable. A boundary identification solution is proposed to detect the range of energy conservation capability by considering the relationships with average interstation speed and the passenger volume condition. A case study is presented using practical data of Beijing Metro Batong Line and t... [more]

Grid-connected systems often consist of several feedback-controlled power-electronics converters that are connected in parallel. Consequently, a number of stability issues arise due to interactions among multiple converter subsystems. Recent studies have presented impedance-based methods to assess the stability of such large systems. However, only few real-life experiences have been previously presented, and practical implementations of impedance-based analysis are rare for large-scale systems that consist of multiple parallel-connected devices. This work presents a case study in which an unstable high-frequency operation, caused by multiple paralleled grid-connected rectifiers, of a 250 kW data center in southern Finland is reported and studied. In addition, the work presents an experimental approach for characterizing and assessing the system stability by using impedance measurements and an aggregated impedance-based analysis. Recently proposed wideband-identification techniques base... [more]

An accurate estimation of the state of charge for lithium battery depends on an accurate identification of the battery model parameters. In order to identify the polarization resistance and polarization capacitance in a Thevenin equivalent circuit model of lithium battery, the discharge and shelved states of a Thevenin circuit model were analyzed in this paper, together with the basic reasons for the difference in the resistance capacitance time constant and the accurate characterization of the resistance capacitance time constant in detail. The exact mathematical expression of the working characteristics of the circuit in two states were deduced thereafter. Moreover, based on the data of various working conditions, the parameters of the Thevenin circuit model through hybrid pulse power characterization experiment was identified, the simulation model was built, and a performance analysis was carried out. The experiments showed that the accuracy of the Thevenin circuit model can become... [more]

Alcohols are attractive fuel blendstocks for spark ignition engines due to their high octane values and potentially positive influence on performance and emission. Although methanol, ethanol, and butanol have been widely studied, other biomass-derived alcohols may have similar or better properties. However, it is not feasible to experimentally investigate the fuel potential of every molecule. The goals of this study were to develop a methodology for rapid screening of a fuel property database for mono-alcohols and to identify alcohols with the potential of blending to produce advantaged motor gasolines. A database was developed with 13 fuel properties of all saturated C1−C10 mono-alcohols. A decision framework was used to evaluate alcohols suitable for blending in gasoline for spark ignition engines in two scenarios: low-range (up to 15 vol%) blends and high-range (greater than 40 vol%) blends. The low-range blend cases resulted in the identification of 48 alcohols. In the case of high... [more]

In railway electrification systems, the harmonic impedance of the traction network is of great value for avoiding harmonic resonance and electrical matching of impedance parameters between trains and traction networks. Therefore, harmonic impedance identification is beneficial to suppress harmonics and improve the power quality of the traction network. As a result of the coupling characteristics of the traction power supply system, the identification results of harmonic impedance may be inaccurate and controversial. In this context, an identification method based on a data evolution mechanism is proposed. At first, a harmonic impedance model is established and the equivalent circuit of the traction network is established. According to the harmonic impedance model, the proposed method eliminates the outliers of the measured data from trains by the Grubbs criterion and calculates the harmonic impedance by partial least squares regression. Then, the data evolution mechanism based on the s... [more]