Wide Area Measurement Research Articles

AN OVERVIEW OF THE NEW ROMANIAN WIDE AREA MANAGEMENT SYSTEM

In this paper, the authors will present the hardware and IT&C structure of the synchrophasor technology and the phasor data concentrator (PDC) of the Transport and System Operator (TSO) Transelectrica’s new Wide Area Measurement System (WAMS). Also, they will write a brief overview of these applications and the development possibilities within the platform from an engineering point of view. Moreover, it will be introduced the possibility of a new enhanced hybrid state estimator, and the link between European Awareness System (EAS) and WAMS.

Optimising Damping Control in Renewable Energy Systems through Reinforcement Learning within Wide-Area Measurement Frameworks

Optimising Damping Control in Renewable Energy Systems through Reinforcement Learning within Wide-Area Measurement Frameworks

An online dynamic security assessment integrated scheme for power systems based on sparse multinomial naive bayes and canonical correlation forest

With the expansion of power systems and renewable energies, the security of power systems is confronted with severe situations. In this research, an online integrated DSA scheme based on sparse multinomial naive Bayes (SMNB) and canonical correlation forest (CCF) is proposed. The SMNB-based feature selection process selects the key features according to the correlations between the system operating variables and the DSA classification labels. Then, the DSA model is obtained by training CCFs with the key features. Finally, the results of DSA can be provided by the model on the basis of the real-time data of phasor measurement units (PMUs) in the wide area measurement system (WAMS). The online DSA integrated scheme is tested on the IEEE 39-bus system and a practical 1648-bus system provided by PSS/E software. The test results show that the proposed scheme is suitable for online application with providing satisfactory assessment accuracy. Furthermore, topology change, data noise and missing data are also taken into account for the robustness tests of the integrated scheme.

Synchronous and non synchronous delay-dependent robust wide-area controllers for power system

Wide-area control is highly efficacious for maintaining sufficient damping of the low-frequency oscillations in the power system. The Wide-Area Measurement System (WAMS) provides wide-area signals to the control site through a communication channel. Even though the wide-area signal improved the dynamic behavior of the power system, a time delay usually exists during the transmission, which is unavoidable. The damping performance of the power system is degraded due to the time delay. In this paper, synchronized and non-synchronized feedback configurations are considered, and the time delay margin is calculated. The Lyapunov theory is adopted for investigating the synchronous and non-synchronous delay-dependent stability criteria for the power system. A lead–lag and a robust H∞ wide-area damping controller (WADC) are proposed to measure the delay margin for synchronized and non-synchronized delay feedback. The relationship between the damping performance and the delay margin is established. It is observed that a non-synchronous feedback-based controller can endure a larger time delay variation than a synchronous feedback-based controller. The nonlinear simulation is carried out to verify the effectiveness of the proposed controllers in Kundur’s two-area system and the IEEE-39 bus test system.

Design of Adaptive Damping Controller With Wide-Area Measurements Considering Unknown Power System Dynamics

Design of Adaptive Damping Controller With Wide-Area Measurements Considering Unknown Power System Dynamics

Coordination of Controllers to Development of Wide-Area Control System for Damping Low-Frequency Oscillations Incorporating Large Renewable and Communication Delay

The modern power systems incorporate high penetration of renewable is a large, composite, interconnected network with dynamic behavior. The small disturbances occurring in the system may induce low-frequency oscillations (LFOs) in the system. If the (LFOs) are not suppressed within a stipulated time, it may cause system islanding or even blackouts. Hence, it is essential to investigate the behavior of the system under various levels of disturbances and control action must be taken to damp these oscillations. The established approach to damping the LFOs is by installing power system stabilizers (PSS). PSS uses the local signals from generators to control the oscillations. The dominant source of inter-area oscillations in power systems is due to overloaded weak interconnected lines, converter-interfaced generation, and the action of the high gain exciter present in the system. Consequently, wide area control is needed to control the inter-area oscillations existent in the system. This paper developed a coordinated design of conventional PSS, static compensator, renewable converters, and wide area controller for damping the local and inter-area oscillations in renewable incorporated power systems. The performance of the developed controller is evaluated through the time domain analysis and eigenvalue analysis. A comparison of the introduced controller has been done with other standard conventional methods. The choice of input signals for the wide area controller from the wide-area measurement system is done based on the controllability index. Additionally, the location of the controller must be identified to dampen the inter-area oscillations in the system. In this paper, the controllability index is calculated to find out the highly affected wide area signals for considering it as the feedback signal to a developed controller. The location of the controller is recognized by computing the participation factor. The developed controller has experimented on renewable incorporated large study power systems when time delay and noise are present in wide area signals.

Dynamic state estimation of power system using hybrid whale-tunicate optimized unscented Kalman filter based on wide area measurement systems

The Energy Management Systems (EMS) utilizes Dynamic State Estimation to monitor the operating condition of the power grid. For a synchronous generator, the speed and angle of a rotor are the most important dynamic states. These states are responsible for producing uncertainty in the power system models. Extended Kalman Filter (EKF) and Unscented Kalman Filters (UKF) are utilized to estimate the dynamic states of the power system when it perceives significant disturbances or noise. The conventional Unscented Kalman Filter (UKF) has limitations in terms of slow convergence speed and its lack of positive semi-definiteness. This prohibits its ability to accurately track the transients of the system. The scaling parameters of UKF (alpha and beta) are optimally tuned to overcome these issues. In this paper, a novel Hybrid Whale-Tunicate-based UKF (HW-TO-UKF) is proposed for tuning the scaling parameters of UKF for reducing the mean difference between the real state and the measured state. During the validation of the proposed method, better robustness and statistical efficiency are achieved by defining the objective function as the minimization of the error difference between the actual and measured states. The simulation is carried out on the WSCC-3 and NPCC-48 machine systems to demonstrate the performance of the proposed HW-TO-UKF over the existing models.

A Complex Network-based Approach for Designing of Wide Area Measurement Systems in Smart Grids using Adam-Eve Like Genetic Algorithm

A Complex Network-based Approach for Designing of Wide Area Measurement Systems in Smart Grids using Adam-Eve Like Genetic Algorithm

Mitigating Propagation of Cyber-Attacks in Wide-Area Measurement Systems

Mitigating Propagation of Cyber-Attacks in Wide-Area Measurement Systems

Synchrophasor-Based Out-of-Step Prediction in Large Grids

Out-of-step (OOS) condition is a potential problem in the power system and uncontrolled islanding is one of the severe consequences of out-of-step condition which leads to cascaded tripping of the system. To avoid this undesired cascaded tripping, early prediction of out-of-step condition is essential before losing the synchronization of generators and between the system areas. Controlled islanding is the last emergency action that can be taken by splitting the system intentionally into coherent islands. Conventionally, OOS condition has been detected with impedance-based measurement techniques which have their own limitations. With the implementation of a wide-area measurement system with synchrophasor measurement units (PMUs) in the power system, it is now possible to measure the bus voltage angle at a much faster rate than with SCADA. In this paper, synchrophasor-based bus voltage angle measurement has been used for early prediction of OOS condition in power systems. A new algorithm has been formulated for both generator and tie lines based on the trajectory of first and second derivatives of the bus voltage phase angle for early detection of OOS condition. The prediction speed of proposed method is found to be between 5% and 70% of time to OOS, after disturbance clearance. The proposed algorithm has been mathematically formulated and evaluated with three benchmark systems in real-time simulation environment with an OPAL-RT real-time simulator and a HYPERSIM platform.

A multi-frame deformation velocity splicing method for wide-area InSAR measurement based on uncontrolled block adjustment: A case study of long-term deformation monitoring in Guangdong, China

Wide-area deformation measurements require multi-frame InSAR datasets for joint monitoring due to the limited swath width of SAR images. However, variations in the stability of reference points, error signal magnitude and distribution, and spatio-temporal filtering parameters result in different deformation rates between adjacent frames, leading to centimeter-level errors in the results. To obtain spatially consistent wide-area results, here we propose a multi-frame deformation velocity splicing method that combines InSAR datasets and block adjustment. We convert the line-of-sight deformation of each frame to vertical using an improved vertical deformation solution method. We construct an uncontrolled block adjustment model and use the results in the automatically identified overlapping areas as redundant observations to solve the deviation of each frame in a wide area. Finally, the multi-frame seamless results are sampled into a uniform spatial resolution cell network, to generate a wide-area deformation product with consistent reference. We validate the proposed method in Guangdong Province, China, covering an area of 1.96 × 105 km2. By correcting and fusing a total of 78 ALOS-1/PALSAR frames (2007–2010) and 11 Sentinel-1 frames (2015–2021) separately, we obtain the wide-area deformation products for Guangdong during the two periods. Compared with the original results, the inner precision of the ALOS-1/PALSAR and Sentinel-1 data is improved by 82.4% and 73.7%, respectively. Compared with GNSS, the accuracy of the corrected Sentinel-1 results is improved by more than 19%. The proposed method contributes to standardizing InSAR deformation production and facilitating the engineering application of wide-area InSAR measurements.

A Scalable PDC Placement Technique for Fast and Resilient Monitoring of Large Power Grids

The Wide Area Measurement System (WAMS) is a key enabler of real-time monitoring of power grids. The essential goals of WAMS design are fast and resilient data transfer from phasor measurement units (PMU) to phasor data concentrators (PDC). We propose a scalable two-stage PDC placement technique for minimizing the end-to-end delay while maintaining resiliency. In the prescreening stage, the plausible candidates of PDC configurations are identified based on a graph theory-based multi-median function (MMF). A computationally efficient meta-heuristic algorithm is used to address scalability. In the candidate selection stage, two different algorithms, namely Suurballe's and Dijkstra's, are employed to identify the best of those plausible PDC configurations as the final design. This technique not only minimizes the hop paths between PMUs and PDCs, but also ensures network resiliency against single PMU, PDC, or communication link failure by incorporating the roles of PMUs in power grid observability into routing policy. Simulation results on the IEEE 57-bus test power system and the 2000-bus test power system demonstrate the effectiveness and scalability of the proposed technique.

Robust design and best control channel selection of FACTs-based WADC for improving power system stability using Grey Wolf Optimizer

With recent advances in wide-area measurement systems (WAMS), wide-area damping controllers (WADCs) based on remote signals can effectively damp inter-area oscillations. However, these signals are inherently subjected to communication time-delay which may adversely affect the damping of inter area oscillations. The purpose of this paper is to present a optimization-based method for designing a WADC for a static synchronous series compensator (SSSC) to improve the damping of inter-area oscillations by considering the time delays of remote control signals. For this aim, the control gain value of the WADC, shifting of the critical modes to a desirable area, and the maximum time delay margins are simultaneously considered as an objective function. Moreover, to design a WADC as minimum-phase structure, the suitable constraints have been determined and added to the objective function as penalty factors. A grey wolf optimization (GWO) algorithm is utilized to solve the optimization problem. Robustness of the designed SSSC-based WADC in amplitude and phase control channels against the time delay has been compared and then the best control channels to damp inter-area oscillations has been selected. Based on simulations and statistical results conducted on 4 and 50 machine multi-machine power systems, it is evident that the proposed method based on the GWO outperforms other techniques in achieving the optimal design of a SSSC-based WADC for damping inter-area oscillations.

Review on measurement-based frequency dynamics monitoring and analyzing in renewable energy dominated power systems

The massive integration of clean energy and renewable energy source (RES) is one of the most important trends in the low carbon energy transition toward carbon neutrality. Such an important goal significantly alters the power system dynamic behavior. Consequently, monitoring and analyzing the complex frequency dynamic of RES-dominated power systems play an essential role in ensuring power system security and stability. The measurements, especially those supported by wide area measurement systems (WAMSs), can enable full state awareness and deep informatization of the power system and therefore provide effective solutions for monitoring and analyzing system frequency dynamic behaviors with complex features. This paper focus on the application of measurements in monitoring and modeling analysis technologies for the features of frequency dynamics of RES-dominated power systems. We summarize related research on online monitoring of frequency dynamic behavior features based on the information from measurements. Further, for system frequency security assessment, measurements can improve the traditional methods and promote new data-driven methods for more accuracy and effective frequency dynamics analysis. Finally, future directions and possible solutions for measurement-based frequency dynamics monitoring and analyzing are prospected.

Multipoint surface electromyography measurement using bull’s-eye electrodes for wide-area topographic analysis

BackgroundSurface electromyography (sEMG) is primarily used to analyze individual and neighboring muscle activity. However, using a broader approach can enable simultaneous measurement of multiple muscles, which is essential for understanding muscular coordination. Using the “bull’s-eye electrode,” which allows bipolar derivation without directional dependence, enables wide-area multipoint sEMG measurements. This study aims to establish a multipoint measurement system and demonstrate its effectiveness and evaluates forearm fatigue and created topographic maps during a grasping task.MethodsNine healthy adults with no recent arm injuries or illnesses participated in this study. They performed grasping tasks using their dominant hand, while bull’s-eye electrodes recorded their muscle activity. To validate the effectiveness of the system, we calculated the root mean squares of muscle activity and entropy, an indicator of muscle activity distribution, and compared them over time.ResultsThe entropy analysis demonstrated a significant time-course effect with increased entropy over time, suggesting increased forearm muscle uniformity, which is possibly indicative of fatigue. Topographic maps visually displayed muscle activity, revealing notable intersubject variations.DiscussionBull’s-eye electrodes facilitated the capture of nine homogeneous muscle activity points, enabling the creation of topographic images. The entropy increased progressively, suggesting an adaptive muscle coordination response to fatigue. Despite some limitations, such as inadequate measurement of the forearm muscles’ belly, the system is an unconventional measurement method.ConclusionThis study established a robust system for wide-area multipoint sEMG measurements using a bull’s-eye electrode setup. This system effectively evaluates muscle fatigue and provides a comprehensive topographic view of muscle activity. These results mark a significant step towards developing a future multichannel sEMG system with enhanced measurement points and improved wearability.Trial registrationThis study was approved by the Ethics Committee of Chiba University Graduate School of Engineering (acceptance number: R4-12, Acceptance date: November 04, 2022).

A subsystem‐based fault location method in distribution grids by sparse measurement

AbstractWith the development of smart meters and other intelligent electronic devices, more and more data‐driven fault location methods based on wide area measurement are emerging. However, these diagnostic methods for dealing with the whole tested system often appear complex. This paper presents an innovative subsystems‐based fault location strategy in distribution grid by the sparsity promoted Bayesian learning algorithm. To avoid taking measurement for the whole distribution system, the fault‐included subsystem is selected according to the distribution characteristics of negative sequence voltage. Then the data for fault location is measured by allocating meters in subsystem, which can reduce the number of required meters. For accurately estimating the fault location, a sparse prior is proposed for the Bayesian learning, which could improve the accuracy of the fault location algorithm by about 4%. The performance is tested on a 12.66‐kV, 69‐bus distribution system in response to various fault scenarios. The results show that the accuracy of the proposed method for the fault section location can reach 90%. It also verifies the robustness and accuracy for fault line location, faced different fault types, fault resistance, noise, etc.

A Blockchain-Enabled Approach for Enhancing Synchrophasor Measurement in Smart Grid 3.0

Smart Grid 3.0 is the latest evolution of the smart grid and incorporates advanced computing and communication technologies. The synchrophasor communication system plays a critical role in wide-area measurement systems (WAMS) for real-time protection and control of power systems, supporting the objectives of Smart Grid 3.0. This system relies on synchrophasor communication technologies, where Phasor Measurement Units (PMUs) transmit synchrophasor data to Phasor Data Concentrators (PDCs) over the synchrophasor communication network. The communication infrastructure of this network is based on the TCP/IP protocol stack, which, unfortunately, is susceptible to cyberattacks, posing security threats such as data tampering and false data injection. These vulnerabilities undermine the intended benefits of synchrophasor applications in terms of situational awareness, observability, grid reliability, resiliency, and synchronized monitoring and control in the smart grid. To address these challenges, it is crucial to enhance the security, integrity, and confidentiality of synchrophasor data within the communication system. This paper proposes a blockchain-based synchrophasor communication system that preserves the security and integrity of synchrophasor data. In this paper, an architecture is proposed for a synchrophasor communication system based on blockchain technology. The proposed architecture aims to enhance the security and integrity of synchrophasor measurements. Furthermore, the architecture is developed as a peer-to-peer distributed blockchain network, leveraging the robustness of a distributed, decentralized, hierarchical PDC architecture. To evaluate the efficacy of the proposed architecture, two case studies, one using the IEEE 9 bus and the other using IEEE 14 bus systems are considered. Moreover, various challenges with potential solutions are also recommended. The proposed work is envisioned to contribute to the advancement of Smart Grid 3.0 by adopting blockchain technology for synchrophasor applications.

A unified power flow controller-based robust damping controller considering time delay in electrical power systems

Nowadays, different power systems are connected to each other due to technical and economic reasons and form a complex developed network. Such networks measure and send system data to decision-making centers for control and protection. This information transmission is accompanied by a delay and causes the performance of the system’s damping controllers to be affected. To improve power system dynamic stability, the supplementary controller in flexible alternating current transmission system (FACTS) devices is designed to account for information transmission delays. In these methods, to increase the controllability and observability of the inter-area mode, the remote signals extracted from the wide area measurement system (WAMS) are used as the input of the modulator. WAMS systems’ time delay reduces power system stability and even causes instability, so it’s crucial to find the maximum delay margin that ensures stability. Therefore, it is necessary to carefully study the role of FACTS tools in stabilizing the power system and damping interregional fluctuations, considering the delay. This research shows that supplementary controller design can dampen frequency and load angle fluctuations in multi-zone power systems despite information transmission delays. The method works in power system analysis toolbox (PSAT) simulation and MATLAB programming.

Wide-Area Composite Load Parameter Identification Based on Multi-Residual Deep Neural Network.

Accurate and practical load modeling plays a critical role in the power system studies including stability, control, and protection. Recently, wide-area measurement systems (WAMSs) are utilized to model the static and dynamic behavior of the load consumption pattern in real-time, simultaneously. In this article, a WAMS-based load modeling method is established based on a multi-residual deep learning structure. To do so, a comprehensive and efficient load model founded on combination of impedance-current-power and induction motor (IM) is constructed at the first step. Then, a deep learning-based framework is developed to understand the time-varying and complex behavior of the composite load model (CLM). To do so, a residual convolutional neural network (ResCNN) is developed to capture the spatial features of the load at different location of the large-scale power system. Then, gated recurrent unit (GRU) is used to fully understand the temporal features from highly variant time-domain signals. It is essential to provide a balance between fast and slow variant parameters. Thus, the designed structure is implemented in a parallel manner to fulfill the balance and moreover, weighted fusion method is used to estimate the parameters, as well. Consequently, an error-based loss function is reformulated to improve the training process as well as robustness in the noisy conditions. The numerical experiments on IEEE 68-bus and Iranian 95-bus systems verify the effectiveness and robustness of the proposed load modeling approach. Furthermore, a comparative study with some relevant methods demonstrates the superiority of the proposed structure. The obtained results in the worst-case scenario show error lower than 0.055% considering noisy condition and at least 50% improvement comparing the several state-of-art methods.

A Pure Data-Driven Method for Online Inertia Estimation in Power Systems Using Local Rational Model Approach

This paper presents an online data-driven method to estimate the inertia constant of synchronous generators (SGs) and the virtual inertia of converter-based resources (CBRs), which enables time-dependent inertia tracking in the normal operation of a power system. The proposed method is based on continuous monitoring of frequency response functions (FRFs) of SGs and CBRs, which are identified by ambient wide-area measurements of phasor measurement units (PMUs). To identify FRFs, a novel non-parametric approach, namely the local rational model (LRM), is used which does not require correct model order selection. LRM approach has a low computational burden and requires a short window of data, both of which are essential for estimating time-dependent inertia using ambient data. The applicability of the proposed method is evaluated in the IEEE 39-bus system and an actual system. The results demonstrate the accuracy, robustness to noise, and effectiveness of the proposed method in estimating the time-dependent inertia of power systems.