Search Results (112)

Due to its vulnerability to a variety of cyber attacks, research on cyber security for power systems has become especially crucial. In order to maintain the safe and stable operation of power systems, it is worthwhile to gain insight into the complex characteristics and behaviors of cyber attacks from the attacker’s perspective. The consensus-based distributed state estimation problem is investigated for power systems subject to collaborative attacks. In order to describe such attack behaviors, the denial of service (DoS) attack model for hybrid remote terminal unit (RTU) and phasor measurement unit (PMU) measurements, and the false data injection (FDI) attack model for neighboring estimation information, are constructed. By integrating these two types of attack models, a different consensus-based distributed estimator is designed to accurately estimate the state of the power system under collaborative attacks. Then, through Lyapunov stability analysis theory, a sufficient condition is provided to ensure that the proposed distributed estimator is stable, and a suitable consensus gain matrix is devised. Finally, to confirm the viability and efficacy of the suggested algorithm, a simulation experiment on an IEEE benchmark 14-bus power system is carried out. Full article

This paper proposes a correction technique for bad data and high-precision analysis based on micro-phasor measurement unit (μPMU) data for a stable and reliable smart substation. First, a high-precision wide-area monitoring system (WAMS) with 35 μPMUs installed at Korea’s Yeonggwang substation, which is connected to renewable energy sources (RESs), is introduced. Time-synchronized μPMU data are collected through the phasor data concentrator (PDC). A pre-processing program is implemented and utilized to integrate the raw data of each μPMU into a single comma-separated values (CSV) snapshot file based on the Timetag. After presenting the technique for identification and correction of event, duplicate, and spike bad data of μPMU, causal relationships are confirmed through the voltage and current fluctuations for a total of five states, such as T/L fault, tap-up, tap-down, generation, and generation shutdown. Additionally, the difference in active power between the T/L and the secondary side of the M.Tr is compared, and the fault ride through (FRT) regulations, when the fault in wind power generation (WP), etc., occurred, is analyzed. Finally, a statistical analysis, such as boxplot and kernel density, based on the instantaneous voltage fluctuation rate (IVFR) is conducted. As a result of the simulation evaluation, the proposed correction technique and precise analysis can accurately identify various phenomena in substations and reliably estimate causal relationships. Full article

Phasor-domain (RMS) simulations have become increasingly vital in modern power system analysis, particularly as the complexity and scale of these systems have expanded with the integration of renewable energy sources. ePHASORSIM, an advanced phasor-based simulation tool developed by OPAL-RT, plays a crucial role in this context by enabling real-time phasor-domain simulation and hardware-in-the-loop testing. To keep pace with these evolving needs, continuous efforts are being made to further improve the accuracy, efficiency, and reliability of ePHASORSIM-based simulations. These efforts include automating model conversion processes for enhanced integration with ePHASORSIM, extending ePHASORSIM’s simulation range with custom models, developing hybrid co-simulation techniques involving ePHASORSIM and an EMT simulator, enhancing simulation scalability, and refining HIL testing to achieve more precise validation of control and protection systems. This paper provides a comprehensive review of these recent advances. Additionally, the paper discusses the conversion of models from PowerFactory—a widely used and comprehensive modeling environment—to ePHASORSIM through both automated tools and manual methods using Excel workbooks, which has been discussed little in the literature. Furthermore, as ePHASORSIM is a relatively new tool with limited cross-validation studies, the paper aims to contribute to this area by presenting a comparative validation against DIgSILENT PowerFactory, with a specific emphasis on its application in electric vehicle charging management systems. Full article

With the growing concern over climate change and energy security, the Government of India expedited enhancing the share of renewable energy (RE) derived from solar, wind and biomass sources within the energy blend. In this paper, a techno-economic and environmental analysis of a microgrid-integrated electric vehicle charging stations fueled by renewable energy is proposed for a typical area in the State of Karnataka, South India. The power transaction with the grid and the sell-back price to the national grid were investigated. Carbon emissions were also assessed, and 128,406 CO₂ kg/Yr can be saved in the grid-connected mode. Also, in this work, different scenarios such as injecting active power, reactive power, and active and reactive power, and injecting active and absorbing reactive power to the grid are comprehensively assessed. Out of four types, type 3 (inject real and reactive power) provides significant reduction in power losses by up to 80.99%. The synchrophasor-technology-based monitoring method is adopted in order to enhance the microgrid system’s overall performance. The execution times for different cases with distributed generators (DGs) and electric vehicle charging stations (EVCSs) for conventional systems and micro-phasor measurement units (µPMU) were observed to be 19.07 s and 5.64 s, respectively, which is well accepted in the case of online monitoring. Full article

Gait phase recognition systems based on surface electromyographic signals (EMGs) are crucial for developing advanced myoelectric control schemes that enhance the interaction between humans and lower limb assistive devices. However, machine learning models used in this context, such as Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM), typically experience performance degradation when modeling the gait cycle with more than just stance and swing phases. This study introduces a generalized phasor-based feature extraction approach (PHASOR) that captures spatial myoelectric features to improve the performance of LDA and SVM in gait phase recognition. A publicly available dataset of 40 subjects was used to evaluate PHASOR against state-of-the-art feature sets in a five-phase gait recognition problem. Additionally, fully data-driven deep learning architectures, such as Rocket and Mini-Rocket, were included for comparison. The separability index (SI) and mean semi-principal axis (MSA) analyses showed mean SI and MSA metrics of 7.7 and 0.5, respectively, indicating the proposed approach’s ability to effectively decode gait phases through EMG activity. The SVM classifier demonstrated the highest accuracy of 82% using a five-fold leave-one-trial-out testing approach, outperforming Rocket and Mini-Rocket. This study confirms that in gait phase recognition based on EMG signals, novel and efficient muscle synergy information feature extraction schemes, such as PHASOR, can compete with deep learning approaches that require greater processing time for feature extraction and classification. Full article

The increase in renewable energy sources (RESs) in power systems is causing significant changes in their dynamic behavior. To ensure the safe operation of these systems, it is necessary to develop new methods for preserving transient stability that follow the new system dynamics. Fast-response devices such as flexible AC transmission systems (FACTSs) can improve the dynamic response of power systems. One of the most frequently used FACTS devices is the Static Var Compensator (SVC), which can improve a system’s transient stability with a proper control strategy. This paper presents a reactive power control strategy for an SVC using synchronized voltage phasor measurements and particle swarm optimization (PSO) to improve the transient stability of a multimachine power system. The PSO algorithm is based on the sensitivity analysis of bus voltage amplitudes and angles to the reactive power of the SVC. It determines the SVC reactive power required for damping active power oscillations of synchronous generators in fault conditions. The sensitivity coefficients can be determined in advance for the characteristic switching conditions of the influential part of the transmission network, and with the application of the PSO algorithm, enable quick and efficient finding of a satisfactory solution. This relatively simple and fast algorithm can be applied in real time. The proposed control strategy is tested on the IEEE 14-bus system using DIgSILENT PowerFactory. The simulation results show that an SVC with the proposed control strategy effectively minimizes the rotor angle oscillations of generators after large disturbances. Full article

An induction motor is an electric machine widely used in various industrial and commercial applications due to its efficiency and simple design. In this regard, a methodology based on the electric phasor analysis of line currents and the variations in the phase angles among these line currents is proposed. The values in degrees of the angles between every pair of line currents were introduced to a fuzzy logic algorithm based on the Mamdani model, developed using the Matlab toolbox for detection and isolation of the inter-turn short-circuit faults on the windings of an induction motor. To carry out the analysis, the induction motor was modified in its stator windings to artificially induce short-circuit faults of different magnitudes. The current signals are acquired in real time using a digital platform developed in the Delphi 7 high-level language communicating with a float point unit Digital Signal Processor (DSP) TMS320F28335 by Texas Instruments. The proposed method not only detects the short circuit faults but also isolates the faulty winding. Full article

Power systems are complex and often subject to faults, requiring accurate mathematical models for a thorough analysis. Traditional time-domain models are employed to evaluate the dynamic response of power system elements during transmission system faults. However, only the positive sequence components are considered for unbalanced faults, so the small-signal stability analysis is no longer accurate when assuming balanced conditions for asymmetrical faults. The dynamic phasor approach extends traditional models by representing synchronous machines with harmonic sequence components, making it suitable for an unbalanced condition analysis and revealing dynamic couplings not evident in conventional methods. By modeling electrical and mechanical equations with harmonic sequence components, the study implements an eigenvalue sensitivity analysis and participation factor analysis to identify the variable with significant participation in the critical modes and consequently in the dynamic response of synchronous machines during asymmetric faults, thereby control strategies can be proposed to improve system stability. The article validates the dynamic phasor model through simulations of a single-phase short circuit, demonstrating its accuracy and effectiveness in representing the transient and dynamic behavior of synchronous machines, and correctly identifies the harmonic sequence component with significant participation in the critical modes identified by the eigenvalue sensitivity to the rotor angular velocity and rotor angle. Full article

The development of digital techniques in control engineering leads to the creation of innovative algorithms for measuring specific parameters. In the field of electric power engineering these parameters may be amplitude, phase and frequency of voltage or current occurring in the analyzed electric grid. Thus, the algorithms mentioned, applied in relation to the quoted parameters, may provide precise and reliable measurement results in the electric grid as well as ensure better grid monitoring and security. Signal analysis regarding its identification due to the type of interference is very difficult because the multitude of information obtained is very large. In order to indicate the best method for determining errors in measuring synchronous parameters of the measured current or voltage waveforms, the authors propose in this paper a new form of one error for all testing functions, which is called an equivalent error. This error is determined for each error’s value defined in the applicable standards for each of selected 15 methods. The use of the equivalent error algorithm is very helpful in identifying a group of methods whose operation is satisfactory in terms of measurement accuracy for various types of disturbances (both in the steady state and in the dynamic state) that may occur in the power grid. The results are analyzed for phasor measurement unit (PMU) devices of class P (protection) and M (measurement). Full article

Reduced-order dynamic models of wireless power transfer (WPT) systems are desired to simplify the analysis and design of power control, phase synchronization, and maximum efficiency tracking. The reduced-order dynamic phasor model is a good choice because of its straightforward physical meaning and concise mathematical formula. However, the model relies on the assumption of loose coupling and loses accuracy when the coupling becomes stronger. In this paper, a model reduction method with split frequency matching is proposed to improve model accuracy under relatively strong coupling conditions, which is suitable for most short-distance WPT applications, such as wireless electrical vehicle charging. Split frequency matching is achieved through a pair of conjugate equivalent mutual inductances, which are derived from the asymmetry characteristics of the full-order dynamic phasor model in the positive and negative frequency domains. The proposed model retains the advantages of the existing model while significantly improving the accuracy under strong coupling conditions. Its characteristics are verified by comparing the experimental results and model predictions under both large step changes and small-signal perturbations. Full article

Fluorescence lifetime imaging microscopy (FLIM) has proven to be a useful method for analyzing various aspects of material science and biology, like the supramolecular organization of (slightly) fluorescent compounds or the metabolic activity in non-labeled cells; in particular, FLIM phasor analysis (phasor-FLIM) has the potential for an intuitive representation of complex fluorescence decays and therefore of the analyzed properties. Here we present and make available tools to fully exploit this potential, in particular by coding via hue, saturation, and intensity the phasor positions and their weights both in the phasor plot and in the microscope image. We apply these tools to analyze FLIM data acquired via two-photon microscopy to visualize: (i) different phases of the drug pioglitazone (PGZ) in solutions and/or crystals, (ii) the position in the phasor plot of non-labelled poly(lactic-co-glycolic acid) (PLGA) nanoparticles (NPs), and (iii) the effect of PGZ or PGZ-containing NPs on the metabolism of insulinoma (INS-1 E) model cells. PGZ is recognized for its efficacy in addressing insulin resistance and hyperglycemia in type 2 diabetes mellitus, and polymeric nanoparticles offer versatile platforms for drug delivery due to their biocompatibility and controlled release kinetics. This study lays the foundation for a better understanding via phasor-FLIM of the organization and effects of drugs, in particular, PGZ, within NPs, aiming at better control of encapsulation and pharmacokinetics, and potentially at novel anti-diabetics theragnostic nanotools. Full article

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

The decrease in overall inertia in power systems due to the shift from synchronous generator production to renewable energy sources (RESs) presents a significant challenge. This transition affects the system’s stable frequency response, making it highly sensitive to imbalances between production and consumption, particularly during large disturbances. To address this issue, this paper introduces a novel approach using Multivariate Empirical Mode Decomposition (MEMD) for the accurate estimation of power system inertia. This approach involves applying MEMD, a complex signal processing technique, to power system frequency signals. The study utilizes PMU (Phasor Measurement Unit) data and simulated disturbances in the IEEE 39 bus test system to conduct this analysis. MEMD offers substantial advantages in analyzing multivariate data and frequency signals during disturbances, providing accurate estimations of system inertia. This approach enhances the understanding of power system dynamics in the context of renewable energy integration. However, the complexity of this methodology and the requirement for precise data collection are challenges that need to be addressed. The results from this approach show high accuracy in estimating the rate of change of frequency (RoCoF) and system inertia, with minimal deviation from actual values. The findings highlight the significant impact of renewable energy integration on system inertia and emphasize the necessity of accurate inertia estimation in modern power systems. Full article

In this paper, a customizable low-cost voltage waveform generator based on a real-time desktop PC and embedded data acquisition card synchronized with Coordinated Universal Time (UTC) is presented. A software approach to phase-locked loop synchronization with an external Global Positioning System (GPS) pulse signal is utilized to achieve a time uncertainty of ±1μs. This avoids expensive hardware modules for synchronization and timing purposes, which are commonly presented in literature. Besides the application for controlling the test platform, our own phasor data concentrator (PDC) application is running concurrently on the host PC. The latter is used for collecting and comparing the syncrophasor data from the test platform against the syncrophasor data measured by phasor measurement units (PMUs) under the test. The paper describes all procedures for generating reference test signals. Numerous case studies were performed, and experimental results for steady-state compliance as well as frequency ramp and phase modulation tests for dynamic compliance are presented in detail. All tests confirm that customizable test platform meets the requirements of IEEE/IEC standards. Compared to other calibrators, the cost as well as the specifications and point-by-point concept of data processing makes the described test platform suitable for performance analysis of PMU algorithms implemented on various development boards. Full article

This paper addresses the pressing need for advanced simulation tools in electric phasor modeling and Smart Grid-Power to X systems. The motivation for this study stems from the critical importance of enhancing the balance between performance and the detailed dynamic representation of the system behavior in the simulations. The identified problem lies in the absence of a comprehensive framework that seamlessly integrates electric phasor DQ0 components into a multi-purpose object-oriented environment. The primary objective of this research is to develop and introduce two simulation libraries, centered around the core component, Electric_DQ0. These libraries aim to establish a robust phasor-based framework, incorporating essential electric components such as sources, loads, branches, power converters, and electric machines. The main goal is to enable dynamic frequency and voltage simulations, particularly focusing on transients in alternators and facilitating Voltage and Frequency Rate of Change analysis during power production-demand imbalances. The libraries were developed within a versatile object-oriented environment, employing the Electric_DQ0 components as the foundation. Through ports, these components transmit turning frequencies, supporting the simulation of dynamic frequency and voltage. The libraries are designed to comprehensively support monophasic and triphasic systems, encompassing delta and wye connections, with a flexible neutral configuration under both balanced and unbalanced conditions. A validation case is presented to demonstrate the tool’s ability to accurately reproduce predictions when compared to one of the most widely used electrical modeling tools in the market. A study case is also presented to evaluate the toolkit’s capabilities. The study sets a specific power demand to fulfill, utilizing diverse energy sources. The obtained results showcase the libraries’ effectiveness in addressing the identified problem, providing valuable insights into their performance and applicability in real-world scenarios. The results demonstrate the efficacy of the proposed framework, delivering accurate outcomes within a reduced execution time. Full article