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A dynamic phasor estimation technique based on the tensor product is presented to enhance the accuracy and robustness of phasor measurement units (PMUs) in the smart electric grid. The performance of the proposed tensor product-based dynamic phasor estimation algorithm (TDPE) is demonstrated with various test signals, i.e., DC decaying, noise, harmonics, power swings, frequency ramps, abrupt change, off-nominal frequency events as per Standard IEEE C37.118. 1a-2014 to represent peculiar dynamic scenarios of the modern power system. The simulation results reveal that the performance factor, i.e., total vector error (%TVE) of the proposed TDPE approach, is below 3 % during various simulated dynamic environments. Thus, the proposed tensor-based dynamic phasor estimation methodology can be effective to extract the phasors of voltage/current signals during peculiar dynamics in the smart electric grids and enhance the several applications based on phasor measurement units (PMUs) information for the stable and secure power system. [ABSTRACT FROM AUTHOR]

The increased integrations of intermittent renewable energy sources into power systems cause more power grid congestions and therefore system operators need more advanced control to relieve this pressure. The dynamic thermal rating (DTR) system is able to increase the thermal constraint and subsequently maximum loading of existing lines. This dynamic rating is achieved through real-time considerations of weather data and it is usually much higher than the traditional static thermal rating system. The operational tripping scheme (OTS), a variant of the wider system integrity protection scheme, also relieves line congestions but it does this by tripping pre-selected generators and this have the unwanted consequence of reducing power adequacy. This paper proposes the novel integration of DTR and OTS, while considering the inherent uncertainties of their sensors based on fuzzy numbers, to avoid unnecessary generation tripping due to conservative line ratings. This novel Fuzzy-DTR-OTS delays the tripping of generations, enhances the adequacy of power supply, improves system security and avoids high risk cascading black out inducing events.

PMU can directly measure positive sequence voltage, phase and system frequency. In this paper, the design and implementation for optimum placement of PMU in power system network (PSN) has been performed using 5 different intelligent approaches at an emulation platform. Different case studies based on IEEE 7, 14 and 30 bus system have been performed and analyzed. In the studies, PMU device is used for the measurement of voltage and current magnitude as well as its phase and its performance has been compared with measured real signals of PSN. PMU measurement gives the accurate results and reliability to PSN. But PMUs are not economical, so PSN operator needs to install a minimum number of PMU in PSN so that system should be fully observable in a real-time scenario. In this paper for optimal placement of PMU, five different intelligent methods have been analyzed for three different bus systems and obtained results are compared. For the further validation of selected PMUs for the PSN, a state estimation using WLS algorithm has been performed using conventional data and PMU data on IEEE14 and IEEE30 bus systems. The obtained results for voltage estimation error and phase estimation error with and without PMU data are compared. [ABSTRACT FROM AUTHOR]

The likelihood of an unintentional power system islanding is increased in systems with significant penetration of distributed generation. To mitigate the adverse effects of islanding, a quick and reliable islanding detection method is needed. This paper first analyzes covariance matrices of a linearized power system model, and relates them to the principal component analysis of experimentally obtained covariance matrices. Additionally, a new model-independent islanding detection method is proposed that uses measurements of voltage angle differences between multiple locations in the system. The angle differences are first preprocessed to remove the effects of nonstationarity. Thereafter, a probabilistic model of principal component analysis is trained using the acquired measurements. The principal and residual spaces extracted from the measurements are used to discriminate between islanding and other events in the system. The applicability of the proposed method is demonstrated by using real measurements gathered from several locations in a transmission grid. [ABSTRACT FROM AUTHOR]

Nowadays, series capacitors are frequently used to increase the transfer capacity and reduce losses on long transmission lines. They also play an important role in improving the voltage stability of the grid. In addition to the positive contributions, it is known that series capacitors affect the operation of distance relays negatively in series-compensated lines and adjacent lines. In this study, a protection algorithm based on wide-area monitoring is proposed using the K-NN classification method to protect series compensated transmission lines in steady-state. The algorithm is tested offline in the radial grid created in the Digsilent Power Factory program. In short circuit scenarios, 2-phase, 3-phase, 2-phase to ground and single-phase to ground faults are analyzed under different fault impedances. According to the results, in case of short circuit faults at certain locations of the lines, the proposed algorithm has determined the faulted line accurately. After the faulted line has been determined, a protection scheme is also proposed for the network. [ABSTRACT FROM AUTHOR]

Power system frequency disturbances are caused by various generation and transmission events including generator trips, load disconnections, line trips, etc. Accurate detections of the events are crucial to bulk power system situation awareness and event investigation. This paper utilizes the recent advances of deep learning to build a convolutional neural network model to detect events in an accurate yet straightforward manner. In this paper, the rate of change of frequency and the relative angle shift are converted to images as the inputs of the proposed model. Finally, this paper uses two convolutional neural networks and classifier fusion to achieve the detection result. Compared with the conventional event detection algorithm and the frequency only deep learning model, the proposed model improves the detection accuracy by over 48%. As a promising tool for bulk power system situation awareness, the proposed model requires a short decision time, which is suitable for practical scenarios. [ABSTRACT FROM AUTHOR]

The System Integrity Protection Scheme (SIPS) is a specialized protection scheme which differs to a great extent from the common protection, especially in its main intention. It is designed for integrity protection, failure prevention and mitigation of disturbance consequences in the whole power system (PS) or modern distribution system (MDS) with a significant power of distributed generation (DG). The input parameters for establishing SIPS in PS are synchronized phasor measurements obtained from the Phasor Measurement Units (PMUs), as a globally acknowledged Smart Grid technology. The realization requires that SIPS is added to the existing Wide Area Monitoring, Protection and Control (WAMPAC), based on synchronized measurements. This paper proposes an algorithm that anticipates optimal PMU placement and then uses angular stability protection based on traditional IEDs supported by synchronized measurements. By using such approach, the system avoids possible blackouts due to the combined operation of the traditional protection and WAMPAC. The proposed SIPS system is tested on specific area in the Croatian transmission system integrating hydro power and wind energy converting power plants. Due to the increased power of renewable energy sources (RES), the proposed algorithm is applicable to modern distribution systems. [ABSTRACT FROM AUTHOR]

A principal component pursuit (PCP)-based interface is proposed between raw synchrophasor data and the algorithms used for wide-area monitoring application to provide resilience against malicious data corruption. The PCP method-based preprocessor recovers a low rank matrix from the data matrix despite gross sparse errors originating from cyber-attacks by solving a convex program. The low-rank matrix consists of the basis vectors obtained from the system response and the sparse matrix represents corruption in each position of the data matrix. An augmented Lagrangian multiplier-based algorithm is applied to solve the PCP problem. The low rank matrix obtained after solving PCP represents the reconstructed data and can be used for estimation of poorly damped modes. A recursive oscillation monitoring algorithm is tested to validate the effectiveness of the proposed approach under both ambient and transient conditions. [ABSTRACT FROM AUTHOR]

Wide area monitoring (WAM) offers many opportunities to improve the performance of power system protection. This paper presents some of these opportunities and the motivation for their development. This methods include monitoring the suitability of relay characteristics, supervisory control of backup protection, more adaptive and intelligent system protection and the creation of novel system integrity protection scheme. The speed of response required for primary protection means that the role WAM in enhancing protection is limited to backup and system protection. The opportunities offered by WAM for enhancing protection are attractive because of the emerging challenges faced by the modern power system protection. The increasingly variable operating conditions of power systems are making it ever more difficult to select relay characteristics that will be a suitable compromise for all loading conditions and contingencies. The maloperation of relays has contributed to the inception and evolution of 70% of blackouts, thus the supervision of the backup protection may prove a valuable tool for preventing or limiting the scale of blackouts. The increasing interconnection and complexity of modern power systems has made them more vulnerable to wide area disturbances and this has contributed to several recent blackouts. The proper management of these wide area disturbances is beyond the scope of most of the existing protection and new, adaptive system integrity protection schemes are needed to protect power system security.

The creation of a suitable wide area monitoring system (WAMS) is widely recognized as an essential aspect of delivering a power system that will be secure, efficient and sustainable for the foreseeable future. In Great Britain (GB), the deployment of the first WAMS to monitor the entire power system in real time was the responsibility of the visualization of real time system dynamics using enhanced monitoring (VISOR) project. The core scope of the VISOR project is to deploy this WAMS and demonstrate how WAMS applications can in the near term provide system operators and planners with clear, actionable information. This paper presents the wider scope of the VISOR project and the GB wide WAMS that has been deployed. Furthermore, the paper describes some of the WAMS applications that have been deployed and provides examples of the measurement device performance issues that have been encountered during the project.

This study presents a method of estimating the effective inertia of a power system from ambient frequency and active power signals measured by phasor measurement units. Most importantly, we demonstrate that inertia can be estimated from ambient measurement data, not only from disturbances. This leads to the possibility of monitoring inertia in a close to continuous manner in the time scale of minutes or tens of minutes. The method allows the system to be divided into a number of areas and the effective inertia of each area to be estimated as a separate quantity. In principle, inertia is estimated by observing the dynamics between changes in active power and resulting frequency deviations during normal operation of the system. The method is based on applying system identification on these measurements and extracting inertia values from identified models. Efficacy of the method is demonstrated on results of real measurements from the Icelandic power system. [ABSTRACT FROM AUTHOR]

In order to systematically shift existing control and management paradigms in distribution systems to new interoperable communication supported schemes in smart grids, we need to map newly developed use cases to standard reference models like Smart Grid Architecture Model (SGAM). From the other side, any new use cases should be tested and validated ex-ante before being deployed in the real-world system. Considering various types of actors in smart grids, use cases are usually tested using co-simulation platforms. Currently, there is no efficient co-simulation platform which supports interoperability analysis based on SGAM. In this paper, we present our developed test platform which offers a support to design new use cases based on SGAM. We used this platform to develop a new scheme for wide area monitoring of existing distribution systems under growing penetration of Photovoltaic production. Off-the-shelf solutions of state estimation for wide area monitoring are either used for passive distribution grids or applied to the active networks with wide measurement of distributed generators. Our proposed distribution state estimation algorithm does not require wide area measurements and relies on the data provided by a PV simulator we developed. This practical scheme is tested experimentally on a realistic urban distribution grid. The monitoring results shows a very low error rate of about 1 % by using our PV simulator under high penetration of PV with about 30 % error of load forecast. Using our SGAM-based platform, we could propose and examine an Internet-of-Things-based infrastructure to deploy the use case.

In the last years, dynamic thermal rating assessment of overhead lines has gained a critical importance in power system operation, since it allows transmission system operators to reliably increase the exploitation of existing infrastructures, avoiding the construction of new transmission assets, and increasing the hosting capacity of renewable power generators. Amongst the possible approaches that can be adopted to solve the thermal estimation problem, the one based on synchrophasor data processing is considered as one of the most promising enabling technologies, since it does not require the need for deploying dedicated sensing technologies distributed along the line route, but only the availability of synchronized measurements already available in the control centers for supporting wide area power system applications. Anyway, the deployment of this technology in real operation conditions is still at its infancy, and several open problems need to be addressed, such as the accuracy drop in low loading conditions, and the need for properly representing and managing the data uncertainties in the thermal estimation process. In trying to address these issues, this paper presents a comprehensive analysis of the most promising solution methods proposed in the literature, evaluating their performances on a real case-study based on a thermally constrained power transmission line located in the north of Italy. [ABSTRACT FROM AUTHOR]

Micro‐grid (MG) monitoring and information sharing between them through a central monitoring unit is required in the present day operational environment. The proposed research focuses on developing wide‐area monitoring platform for multiple MGs running in parallel. This is achieved by using C37.118.1 complied phasor measurements units (PMUs) which provides accurate and reliable information monitoring at remote ends of the MGs and are further connected to the Phasor Data Concentrator which acts as the central monitoring unit. This process not only retrieves information at different nodes of the MGs equipped with PMUs, but the information can be exchanged between MGs for further action if required during contingencies. The PMUs are used to monitor phasors (amplitude and phases) and frequency of fundamentals which are further used to compute wide‐area functions at different operating nodes of the MGs at grid connected and islanded modes of operation including different operating conditions. The proposed PMU and MG models are developed on MATLAB/SIMULINK platform. Extensive test results indicate that the proposed monitoring process is highly essential to retrieve the operational status of the multiple MGs observed at the central monitoring unit. [ABSTRACT FROM AUTHOR]

When power grids are heavily stressed with a bulk power transfer, it is useful to have a fast indication of the increased stress when multiple line outages occur. Reducing the bulk power transfer when the outages are severe could forestall further cascading of the outages. We show that synchrophasor measurements of voltage angles at all the area tie lines can be used to indicate the severity of multiple outages. These synchrophasor measurements are readily combined into an “area angle” that can quickly track the severity of multiple outages after they occur. We present a procedure to define thresholds for the area angle that relate to the maximum power that can be transferred through the area until a line limit is reached. Then in real time we would monitor the area angle and compare it to the thresholds when line outages occur to determine the urgency (or not) of actions to reduce the bulk transfer of power through the area. The procedure also identifies exceptional cases in which separate actions to resolve local power distribution problems are needed. We illustrate the thresholds and monitoring with the area angle across several states of Northwestern USA. [ABSTRACT FROM AUTHOR]

This paper presents a new method to dynamically determine coherent generators and electrical areas of an interconnected power system. The proposed method is based on dynamic frequency deviations of both generator and non-generator buses, with respect to the system nominal frequency. The proposed method 1) largely overcomes the limitations of the existing model-based and measurement-based coherency identification methods, 2) enables dynamic tracking of the coherency time-evolution, and 3) provides noise immunity which is imperative in practical implementation. The method also promises the potential for real-time coherency calculation. The proposed method is applied to the 16-machine/68-bus NPCC system based on time-domain simulation studies in the PSS/E platform and the results are compared with those of the classical slow-coherency (model-based) method and a measurement-based method. [ABSTRACT FROM AUTHOR]

In this paper, a novel variational method is introduced for multi-object tracking in a network of cameras. In a camera network, objects are tracked by each camera using any of conventional algorithms and their tracks are extracted. Each extracted track is called a tracklet. The extracted tracklets are the inputs to our proposed method. Our objective in this paper is to associate the corresponding tracklets of an object and present the persistent trace of all objects. The association is formulated and solved using a variational energy function, which is based on appearance and motion model of objects. The optimization is realized by, first converting the variational energy function into an Ordinary Differential Equation (ODE) employing the Euler-Lagrange equation; then, the ODE is solved by numerical methods. The proposed method is evaluated on three well known real datasets and one synthetic dataset. The performance of our method is compared with the state of the art methods, employing the conventional metrics and under less restrictive assumption, and superiority of our method is demonstrated. [ABSTRACT FROM AUTHOR]

Phasor measurement units (PMUs) play an important role in the wide‐area monitoring and protection of modern power systems. Historically, their deployment was limited by the prohibitive cost of the device itself. Therefore, the objective of the conventional optimal PMU placement problem was to find minimum number of devices, which when carefully placed throughout the network, maximised observability subject to different constraints. Due to improvements in relay technology, digital relays can now serve as both relays and PMUs. Under such circumstances, the substation installations consume the largest portion of the deployment cost, and not the devices themselves. Thus, for minimising cost of synchrophasor deployment, number of substation installations must be minimised. This study uses binary particle swarm optimisation to minimise number of substations in which installations must be performed for making all voltage levels observable, while being subject to various practical constraints. Standard IEEE systems have been used to explain the technique. Finally, a large‐scale network of Dominion Virginia Power is used as the test bed for implementation. [ABSTRACT FROM AUTHOR]

Deployment of Phasor Measurement Units (PMU) in the United States transmission grid has brought a new data stream to be processed and an opportunity to improve situational awareness on the grid. This new data stream offers opportunity for a faster detection and response algorithm to minimize wide spread outages. High rate of data collection of PMU systems has also brought a challenge on how to extract information from fast moving PMU data stream in real time to improve situational awareness inside a control room. Despite the fact that mathematical and probabilistic methods are the most accurate methods of stability analysis, online decision making algorithms cannot afford the latency brought by those methods. Traditional batch processing Artificial Intelligence (AI) techniques have been extensively studied as potential replacements for these approaches, however conventional AI techniques do not deal with continuous streams of fast moving phasor data. This paper presented a novel application of the stream mining algorithms for synchrophasor data to meet quick decision making requirement of future situational awareness applications in power systems. To prove that the proposed methods are efficient and capable of handling huge amounts of data with reasonable accuracy and within limited resources of memory and computational power, four different experiments with different conditions (changing/unchanging the load conditions of Real Power and Reactive Power, fixing the size of memory, and comparing the performance of non-adaptive Hoeffding tree with traditional decision tree algorithms) were conducted. The algorithms discussed in this paper support decisions inside the control rooms helping stakeholders make informed decisions to improve reliability of the future smart grid. [ABSTRACT FROM AUTHOR]

In this paper, a Two-Step Hybrid State Estimator based on classical SCADA and new phasor measurement unit inputs is presented. The first step is a linear state estimator that utilizes only synchrophasors. The second step is an iterative state estimator that combines conventional measurements with pseudo-measurements obtained from the first step. The developed hybrid model takes advantage of the high sampling frequency of the synchrophasors by running the first step state estimator several times between two consecutive runs of the second step state estimator. The methodology was tested on the IEEE 14 and 57 buses test systems and the real full Croatian transmission power system model. It was also compared with other hybrid models. The proposed formulation of the hybrid state estimator is comparable with other hybrid models in view of accuracy and convergence, and it offers enhanced filtering of measurement errors. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper discusses, through two selected case studies based on real data, how the availability of the new generation of Synthetic Aperture Radar (SAR) sensors, characterized by reduced revisiting time and improved spatial resolution or coverage, is impacting the exploitation of Differential SAR Interferometry (DInSAR) techniques for the detection and monitoring of deformation phenomena. The presented analysis is carried out using X-band data of the COSMO-SkyMed constellation satellites, as well as C-band data acquired by the Sentinel-1A sensor; furthermore, we compare the achieved results to those based on first-generation ERS-1/2 and ENVISAT satellite data. The first case study shows how the COSMO-SkyMed X-band SAR systems open new opportunities for the detection and monitoring of deformation phenomena at the scale of a single building, even when they are characterized by a rather fast dynamic. The second experiment is based on the Sentinel-1A DInSAR measurements and permits us to envisage new scenarios for deformation analysis of very wide areas. The final discussion is devoted to summarise the lessons learned through the presented case studies and to identify the main future actions needed for a full exploitation of the surface deformation measurement capability provided by the new generation of SAR sensor. [ABSTRACT FROM AUTHOR]

Employment of multi-agent system (MAS) principle in power systems can provide a discipline for interrelations between the host computers in different substations in order to enhance the effectiveness and efficiency of remedial actions and consequently power system operation against disturbance occurrence. In this paper, two types of these disciplines, each of which constructs an organization for agents, are explained and their performances in voltage control of a power system (in the context of steady state regime) are examined and compared on Nordic32 as test power system. These MASs may be implemented as the main structure of a wide area monitoring, protection and control (WAMPAC) system. [ABSTRACT FROM AUTHOR]

This paper presents a fully adaptive fault location algorithm for series-compensated lines (SCLs) based on synchronized phasor measurements obtained by phasor measurement units (PMUs). The proposed algorithm does not require any knowledge on the exact model of the series-compensation device and, therefore, can be applied to transmission lines with any type of series compensation. In addition, the proposed algorithm utilizes only PMU synchronized measurements and does not require any data to be provided by the electric utility. The SCL parameters and Thevenin's equivalent (TE) of the system at SCL terminals are determined online, utilizing three independent sets of pre-fault PMU measurements, to ensure considering the actual operating conditions of the system. Fault-location accuracy evaluation of the proposed algorithm is performed with respect to various factors such as fault position, fault type, fault resistance, fault inception angle, pre-fault loading and line compensation degree. The proposed algorithm is simulated using both PSCAD/EMTDC and MATLAB and tested on a 400-kV system. Simulation results revealed that the developed algorithm is capable of producing reliable and highly accurate solutions. [ABSTRACT FROM PUBLISHER]

Post-mortem studies carried out after recent power system blackouts have shown that time-stamped measurements from Phasor Measurement Units (PMUs) would have helped to avert these blackouts if they were available. Consequently, there is the need to optimally locate these PMUs to provide information about the system's state. This paper proposes a novel method incorporating modal participation factors computed from the eigenvalues and eigenvectors of the reduced Jacobian matrix obtained from the system's power flow with Binary Integer Programming (BIP), in solving the Optimal PMU Placement (OPP) problem while considering the system's voltage stability. The proposed method identifies the critical buses prone to voltage instability, determines the minimum number of PMUs required for complete topological observability, and the best locations to site the PMUs. The proposed method was tested on benchmark IEEE 14-bus, 30-bus, and 57-bus test networks. Analyses of the results show that the proposed method provides a better procedure for the strategic placement of PMUs in practical networks for voltage stability monitoring especially for the cases of phased (multi-stage) PMU placement limited by the availability of funds and communication channels. Thereby making it necessary to give priority to critical/voltage weak buses during the phased installation process. Copyright © 2014 Praise Worthy Prize S.r.l. - All rights reserved. [ABSTRACT FROM AUTHOR]

The analysis of electromechanical oscillatory modes offers essential information on the stability of power systems. This paper investigates the use of the natural excitation technique (NExT) in conjunction with the eigensystem realization algorithm (ERA) for the modal analysis of power systems. The NExT-ERA is a multivariate method utilizing data that are measured from several locations in the power grid. The method is capable of utilizing synchronously measured data from a wide area monitoring system (WAMS) as well as unsynchronized measurements, such as measurements of individual relays' recorders. The performance of the NExT-ERA method is analyzed by applying it to data generated with test systems. The method is also applied to actual measurements received from the Nordic power system. The results indicate that the frequencies and damping ratios of electromechanical oscillatory modes can be analyzed by using the NExT-ERA method. Thus, the method is a promising identification technique for wide-area monitoring of electromechanical oscillations. [ABSTRACT FROM PUBLISHER]

Highlights: [•] An adaptive fault location algorithm based on PMUs. [•] Online calculation of Thevenin's equivalents. [•] Online calculation of transmission line parameters. [•] Fault-type selection is not required. [•] The algorithm is robust and not sensitive to measurement errors. [ABSTRACT FROM AUTHOR]

The Indian power industry is one of the fastest growing sectors and needs a paradigm shift through next-generation automation to handle the operational challenges. Presently, the Indian power sector possesses a number of issues, such as minimizing transmission and distribution losses, power theft, inadequate grid infrastructure, low metering efficiency, and lack of awareness etc. This gap can only be bridged by bringing smart grid initiatives into the Indian power industry. [ABSTRACT FROM PUBLISHER]

The paper presents the hybrid state estimator that incorporates the conventional measurements from the Supervisory Control And Data Acquisition (SCADA) system and the synchronized phasor measurements available from Phasor Measurement Units (PMUs). The voltage and current phasors are utilized to obtain pseudo-measurements of power flows and injections. The derived pseudo-measurements are combined together with the voltage phasors and the conventional measurements as inputs for the iterative state estimator based on the Weighted Least Squares method with the addition of equality constraints for zero-injections. The proposed formulation was tested on the IEEE test systems with 14, 30, 57 and 118 buses. The Croatian transmission power system model with the deployed PMUs was used as an example of the real power system. The simulation results were compared with another hybrid state estimator and with the classical solution that does not take advantage of the synchronized phasor measurements. The developed hybrid state estimator provides higher accuracy of the estimated system state along with improved filtering of measurement errors. [ABSTRACT FROM AUTHOR]

Abstract: This paper proposes the use of the discrete wavelet transform (DWT) to analyze and locate the low frequency oscillations of power systems, which can result in a loss of stability or in a black-out. The proposed DWT applied to active power signal is tested and compared with more conventional approaches of Prony and Eigenvalue analyses. The DWT also enables estimation of the total active power imbalance of a system. Estimation performances of different wavelet families are tested. Based on the proposed DWT of electromechanical transient oscillations, the DWT is also applied to identify the network nodes in the neighbourhood of the original disturbance. The performance of the proposed DWT is evaluated on the New England (NE) 39-bus test system. [Copyright &y& Elsevier]