Application Of Phasor Measurement Units Research Articles

Introducing a New Method for DPMU in Detecting the Type and Location of the Fault

Introduction: Nowadays, due to the increasing development of distribution networks, their safety and high-reliability performance are of particular importance. One of the most important problems that endanger the security and reliability of these networks is the creation of some faults in them. In case of a fault in the network, identifying its location and type can be of great help in repairing faulty equipment. Also, by detecting the disconnection of one of the equipment or lines, it is possible to prevent accidents in the network. Methods: Phasor Measurement Unit (PMU) has been widely and successfully used as Transmission- Phasor Measurement Unit (T-PMU). The reporting time of PMUs is much shorter than the old Supervisory Control and Data Acquisition (SCADA) systems. They can provide synchronized phasor measurements that can generate voltage phasors of different network nodes. This study aimed to investigate the various applications of phasor measurement units in distribution networks and present a new method for detecting and analyzing the location and type of fault and topology fault of the distribution network using the Internet of Things (IOT) analysis method. Results: To implement this method, it is necessary to measure different parameters of the distribution network before and after the occurrence of a fault, which is used by the DPMU for measurement. The simulation results indicate that for both single-topology and multi-topology faults, the proposed method has higher accuracy and better detection than the remaining common methods and effectively detects single-topology and multi-topology faults in the distribution network. Conclusion: This method can provide a more accurate network topology to estimate the state of the distribution network, which improves the accuracy of the state estimation and is suitable for implementing various advanced functions of the distribution management system.

A Graph-Theoretic Approach for Optimal Phasor Measurement Units Placement Using Binary Firefly Algorithm

The pursuit of achieving total power network observability in smart grids using Phasor Measurement Units (PMUs) carries a significant promise of real-time Wide-Area Monitoring, Protection, and Control (WAMPAC). PMU applications eliminate periodical measurements, thereby increasing accuracy through a high sampling rate of the measured power systems quantities. The high costs of installation of PMUs for total power system observability presents a challenge in the implementation of PMUs. This is due to the expensive costs of PMU devices. This has led to a prominent optimal PMU placement (OPP) problem that researchers tirelessly aim to solve by ensuring a complete power network observability while using the least installed PMU devices possible. In this paper, a novel Binary Firefly Algorithm (BFA) based on the node degree centrality scores of each bus is proposed to minimize PMU installations. The BFA solves the OPP problem in consideration of the effect of Zero Injection Buses (ZIBs) under normal operation and single PMU outage (SPO). The robustness and efficiency of the proposed algorithm is tested on IEEE-approved test systems and visualized with a force-directed technique on an undirected power network graph. The proposed BFA yields the same but better optimal PMU numbers, obtained by existing meta-heuristic optimization techniques found in the literature for each of the IEEE test cases, as well as highlighting the cost–benefit of having a robust system against single PMU loss while considering the ZIB effect for an improved system measurement availability.

Directions of Application of Phasor Measurement Units for Control and Monitoring of Modern Power Systems: A State-of-the-Art Review

The development of modern power systems is directly related to changes in the traditional principles of management, planning, and monitoring of electrical modes. The mass introduction of renewable energy sources and control devices based on power electronics components contributes to changing the nature of the flow of transient and quasi-established electrical modes. In this area, the problem arises of conducting a more accurate and rapid assessment of the parameters of the electrical regime using synchronized vector measurement devices. The paper presents an extensive meta-analysis of the modern applications of phasor measurement units (PMUs) for monitoring, emergency management and protection of power systems. As a result, promising research directions, the advantages and disadvantages of the existing approaches to emergency management, condition assessment, and relay protection based on PMUs are identified.

A Survey on the Application of Phasor Measurement Units to the Protection of Transmission and Smart Distribution Systems

Renewable energy resources have increasingly been integrated into electric power grids. Moreover, new challenges constantly arise, showing the need for modernization in monitoring, control, and protection. Transmission and distribution systems have explored the use of phasor measurement units (PMUs) in an attempt to meet these requirements. The decreasing cost of hardware components of PMUs, similar to what occurred with digital relays, is an important factor in terms of their worldwide use in different applications. Low-cost variations of PMUs focused on distribution systems, such as micro- and D-PMUs, are growing in number. Thus, this survey article presents significant and recent research conducted in the field of power systems using PMUs. Firstly, it briefly describes the characteristics of PMUs concerning hardware and phasor estimation algorithms. Afterward, recent studies related to transmission and distribution system protection based on PMUs are presented, such as fault detection and location, stability, and wide-area protection. Finally, the article also provided important guidelines, which certainly can be useful for future research in the years to come.

Real-Time Grid Monitoring and Protection: A Comprehensive Survey on the Advantages of Phasor Measurement Units

The emerging smart-grid and microgrid concept implementation into the conventional power system brings complexity due to the incorporation of various renewable energy sources and non-linear inverter-based devices. The occurrence of frequent power outages may have a significant negative impact on a nation’s economic, societal, and fiscal standing. As a result, it is essential to employ sophisticated monitoring and measuring technology. Implementing phasor measurement units (PMUs) in modern power systems brings about substantial improvement and beneficial solutions, mainly to protection issues and challenges. PMU-assisted state estimation, phase angle monitoring, power oscillation monitoring, voltage stability monitoring, fault detection, and cyberattack identification are a few prominent applications. Although substantial research has been carried out on the aspects of PMU applications to power system protection, it can be evolved from its current infancy stage and become an open domain of research to achieve further improvements and novel approaches. The three principal objectives are emphasized in this review. The first objective is to present all the methods on the synchro-phasor-based PMU application to estimate the power system states and dynamic phenomena in frequent time intervals to observe centrally, which helps to make appropriate decisions for better protection. The second is to discuss and analyze the post-disturbance scenarios adopted through better protection schemes based on accurate and synchronized measurements through GPS synchronization. Thirdly, this review summarizes current research on PMU applications for power system protection, showcasing innovative breakthroughs, addressing existing challenges, and highlighting areas for future research to enhance system resilience against catastrophic events.

Исследование практических аспектов ОМП на ЛЭП сверхвысокого напряжения по векторным измерениям на базе RTDS

Application of Phasor Measurement Unit (PMU) is a modern technology in electric power systems with quite a few possible applications. Remote identification of fault location (FL) at extra-high voltage transmission lines is one of the possible applications of PMU. The number of research works dedicated to this issue is rather limited. Also, there is no in-depth analysis of the PMU digital filter performance in case of short circuit; some factors that affect the FL accuracy are not covered; and the number of methods to identify FL remotely is insufficient. The current research goal is to study all the above-mentioned issues. The research has been conducted using the methods of mathematical modeling of fault-initiated transients represented with a real-time digital simulator RTDS (including the RSCAD software). A total of 16 FL expressions both in Russian and foreign scientific papers have been analyzed. Monte-Carlo method has been used to assess the impact of various factors on the FL accuracy. The PMU functionality presented in the RTDS simulator has been used to obtain required synchrophasors. A typical timespan of faults at extra-high voltage transmission lines has been deduced (it turns out to be at least three cycles of the fundamental frequency component). Dynamic characteristics of both M and P class PMUs have been thoroughly examined. The authors have made a conclusion that PMU-based FL is as accurate as that provided by conventional FL units. The influence of some major factors on the FL results has been investigated as well. PMU-based FL is considered to be a promising application. At the same time, P filter class PMUs are primarily used. One is to avoid getting synchrophasor data of different class PMUs at the line terminals. The obtained results are meant to be introduced to improve the PMU-based FL accuracy, especially in the context of processing real PMU data.

Design of fault-tolerant control system for distributed energy resources based power network using Phasor Measurement Units

Distributed Energy Resources (DERs) play a significant role in reducing carbon emissions and improving the power system, nonetheless, maintaining the stability of the system parameters under faulty conditions is a major challenge. To minimize fault duration and maximize the system’s fault tolerance capability while maintaining affordability and being environment friendly, DERs supported by storage units are used in parallel with the main grid which offers promising results. This paper proposes the utilization of DERs as the primary source while the main grid shares the peak load. The paper also discusses the application of Phasor Measurement Units (PMUs) to record current and voltage values. PMUs are used to detect the fault in its early stage and communicate to the central controller to shift the load on storage units and isolate fault locations. The operation is controlled at two levels, that is at the load end and the junction point of the grid and DER. Any anomaly detected by PMUs is tested for the fault location, where faults are then controlled and minimized using the proposed method while keeping economic factors under consideration. The system is tested in light of results from mathematical modeling and design simulation which show very low latency time against demand response and quick isolation of fault location. A comparison with existing and previous works also shows the promising performance of the proposed fault-tolerant power system using PMUs.

Controlled Islanding under Complete and Partial False Data Injection Attack Uncertainties against Phasor Measurement Units

The widespread application of phasor measurement units has improved grid operational reliability. However, this has increased the risk of cyber threats such as false data injection attack that mislead time-critical measurements, which may lead to incorrect operator actions. While a single incorrect operator action might not result in a cascading failure, a series of actions impacting critical lines and transformers, combined with pre-existing faults or scheduled maintenance, might lead to widespread outages. To prevent cascading failures, controlled islanding strategies are traditionally implemented. However, islanding is effective only when the received data are trustworthy. This paper investigates two multi-objective controlled islanding strategies to accommodate data uncertainties under scenarios of lack of or partial knowledge of false data injection attacks. When attack information is not available, the optimization problem maximizes island observability using a minimum number of phasor measurement units for a more accurate state estimation. When partial attack information is available, vulnerable phasor measurement units are isolated to a smaller island to minimize the impacts of attacks. Additional objectives ensure steady-state and transient-state stability of the islands. Simulations are performed on 200-bus, 500-bus, and 2000-bus systems.

Comparative Analysis of Phasor Estimation Techniques for PMU Applications

Phasor Measurement Units (PMU) are valuable sources of data which increase the visibility into several fields of application such as power production, transmission and distribution. With the initial goal of obtaining phasor values at fixed points in the network and syncing it to a standard time frame, the technology has morphed into an all-encompassing unit, which has its uses in the field of protection, control and automation. With the application of these units becoming a standard benchmark, the improvement in the current available units is a huge requirement. This study presents a comprehensive analysis of various techniques that is used for the estimation of phasors.

A Data-Driven Scheme Based on Sparse Projection Oblique Randomer Forests for Real-Time Dynamic Security Assessment

With the wide interconnection of power systems and extensive application of phasor measurement units (PMUs), the secure operation of power systems is facing considerable challenges. To satisfy the demand of online dynamic security assessment (DSA) for modern power systems, a data-driven scheme based on sparse projection oblique randomer forests (SPORF) is proposed, which includes offline training, periodic update and online assessment. In the first stage, an improved adaptive synthetic sampling (ADASYN) method is developed to mitigate the class imbalance problem for the data-driven DSA approach. Then, the SPORF-based DSA model is trained using crucial features with low redundancy selected by a feature selection procedure based on the minimal-redundancy-maximal-relevance (MRMR) criterion. In the second stage, the periodic update of the DSA model for unseen system topologies is executed to enhance the robustness of the model. In the third stage, the trained model can provide the DSA result immediately when the real-time operation information of a system is received. The satisfactory performance of the proposed scheme is demonstrated through a series of tests and the comparisons on a 23-bus system and a practical 1648-bus system.

A Value-at-Risk Based Approach for PMU Placement in Distribution Systems

With the application of phasor measurement units (PMU) in the distribution system, it is expected that the performance of the distribution system state estimation can be improved obviously with the PMU measurements into consideration. How to appropriately place the PMUs in the distribution is therefore become an important issue due to the economical consideration. According to the concept of efficient frontier, a value-at-risk based approach is proposed to make optimal placement of PMU taking account of the uncertainty of measure errors, statistical characteristics of the pseudo measurements, and reliability of the measurement instrument. The reasonability and feasibility of the proposed model is illustrated with 12-node system and IEEE-33 node system. Simulation results indicated that uncertainties of measurement error and instrument fault result in more PMU to be installed, and measurement uncertainty is the main affect factor unless the fault rate of PMU is quite high.

An integrated scheme for dynamic security assessment considering misclassification constraint based on umbrella Neyman-Pearson classifiers

Power system is one of the most complex dynamic industrial systems with the continuous expansion of the system scale and extensive application of phasor measurement units (PMUs). Dynamic security assessment (DSA) misclassification of the system will bring unpredictable consequences. Therefore, an integrated scheme for DSA that considers misclassification constraint is proposed in this paper to satisfy practical applications. The scheme includes a feature selection process and a DSA model, which are based on the bagging nearest-neighbor prediction independence test (BNNPT) and umbrella Neyman-Pearson (NP) classifiers, respectively. The BNNPT can explore the relationships between variables and the dynamic security index (DSI) to screen out the crucial features highly related to the DSI. By controlling the Type I error threshold and the cyclic split training mode, umbrella NP classifiers can effectively constrain Type I error, reduce the effect of misclassification, and improve DSA for the secure operation of the system. The performance of this integrated scheme is demonstrated through tests on the IEEE 39-bus system and a practical 500-bus system.

A data-driven approach for online dynamic security assessment with spatial-temporal dynamic visualization using random bits forest

With the continuous expansion of the power system scale and extensive application of phasor measurement units (PMUs), the secure operation of power systems has been increasingly concerned. To construct an efficient dynamic security assessment (DSA) model and make it convenient for practical applications, an integrated framework for online DSA with spatial-temporal dynamic visualization is proposed in this paper. The proposed framework consists of DSA model based on random bits forest (RBF) and spatial-temporal dynamic visualization. By using a feature selection process based on the bagging nearest-neighbor prediction independence test (BNNPT) and Pearson correlation coefficient (PCC), the key features are selected for model training. Once the real-time PMU data from the wide area measurement system (WAMS) are received, the trained DSA model can rapidly provide the corresponding transient stability margin (TSM). Particularly, the spatial-temporal dynamic visualization is presented to describe the quickly captured dynamic security information. The encouraging performance of the framework is demonstrated by tests on a 23-bus test system and a practical 1648-bus system. Especially, some impact factors that influence the practical operation of power systems are considered in the robustness examination, including variations of the topology, power distribution among generators/loads, peak/minimum load and load characteristics.

Application of PMU on Fault Detection and Hybrid State Estimations

It is feasible to record and monitor the power systems’ dynamic behavior with the extensive deployment of phasor measurement units (PMU). PMU provides high-precision data in which has shown applications in many fields. This study gives a comprehensive prospective of the application of PMU in fault detection. Basically, this paper evaluates the application of this data for fault detection. In which, it is crucial to detect the faults at their early stage so remedial reaction can be taken to reduce the potential damage. Second, the incorporation of the PMU data into state estimation algorithms to achieve more stable and accurate estimation algorithm. It is demonstrated, incorporating the PMU data will increase the observability of the system, however more comprehensive algorithm to monitor the system and detect the faults is needed.

An Integrated Scheme for Online Dynamic Security Assessment Based on Partial Mutual Information and Iterated Random Forest

With the continuous expansion of the power system scale and extensive application of phasor measurement units (PMUs), the secure operation of power systems has been increasingly concerned. In this paper, an integrated scheme for online dynamic security assessment (DSA) based on feature selection and regression prediction is proposed. First, partial mutual information (PMI) and the Pearson correlation coefficient (PCC) are used to select the key variables in the feature selection process. Second, an iterated random forest (IRF) is applied to predict the transient stability margin (TSM) based on the selected variables. Combining the feature selection process and regression prediction, a DSA model is constructed. Finally, a spatial-temporal dynamic visualization approach is proposed, which can intuitively provide real-time dynamic security information of power systems. The integrated scheme, which is tested on the IEEE 39-bus system and a practical 1648-bus system provided by the software PSS/E, exhibits desirable assessment accuracy and is suitable for online application. In the robustness test, some impact factors for power system operation are considered, such as topology change, variation of generator/load power distribution and variation of load characteristics. Moreover, the impacts of missing data and measurement noise are studied.

Application of PMUs to monitor large-scale PV penetration infeed on frequency of 60 Hz Japan power system: A case study from Kyushu Island

Recently, the large-scale photovoltaic (PV) penetration brings serious issues for system operators in monitoring and maintaining grid stability. The intermittent power output and loss of inertia property from high PV penetration critically affect the balance between generation and demand. These issues lead to larger frequency oscillations, generation tripping, and cascading failures. To overcome these challenges, this paper proposes an advanced application of phasor measurement units (PMUs) for monitoring dynamics of the system in the presence of high PV penetration. During such penetration, the data-driven analysis of the rate of change of frequency (ROCOF) is of great importance, reflecting the system stability. This approach is first demonstrated on Kyushu Island, and PMUs are installed at the domestic supply side. The contrastive scenarios of high-resolution PMUs recorded in each region are analyzed against different levels of PV penetration. The results reveal that monitoring system frequency and ROCOF variations not only indicate the oscillatory behavior of the grid, but also provide useful information for the wide-area dynamic stability. This paper also offers a recent overview of large-scale PV penetration infeed on frequency of the 60 Hz Japan power system, and it can be useful for improving a range of diagnostic/monitoring and control functionalities.

A Comprehensive Survey on Phasor Measurement Unit Applications in Distribution Systems

Synchrophasor technology opens a new window for power system observability. Phasor measurement units (PMUs) are able to provide synchronized and accurate data such as frequency, voltage and current phasors, vibration, and temperature for power systems. Thus, the utilization of PMUs has become quite important in the fast monitoring, protection, and even the control of new and complicated distribution systems. However, data quality and communication are the main concerns for synchrophasor applications. This study presents a comprehensive survey on wide-area monitoring systems (WAMSs), PMUs, data quality, and communication requirements for the main applications of PMUs in a modern and smart distribution system with a variety of energy resources and loads. In addition, the main challenges for PMU applications as well as opportunities for the future use of this intelligent device in distribution systems will be presented in this paper.

Novel voltage-to-power sensitivity estimation for phasor measurement unit-unobservable distribution networks based on network equivalent

The access and application of phasor measurement units (PMUs) in distribution networks highly improve the system observability and further enhance the performance of operation control and energy management. A novel PMU-based estimation method of voltage-to-power sensitivity via network equivalent is proposed for distribution systems. An equivalent model is introduced to simplify the PMU-unobservable parts of the distribution network. The equivalent parameters are estimated with the PMU measurements on both sides. The original PMU-unobservable distribution network is simplified into a completely observable network with an arbitrary configuration of PMUs. The maximum correntropy Kalman filter (MCKF) is exploited in parameter estimation to handle the noise and bad data within the PMU measurements. The voltage-to-power sensitivity of the simplified system is then calculated according to the estimation of the equivalent network parameters. Case studies on the IEEE 33-node and the PG&E 69-node test feeders verify the correctness and effectiveness of the proposed method.

Voltage Control Method of Distribution Networks Using PMU Based Sensitivity Estimation

Application of phasor measurement unit (PMU) at distribution networks provide new options for voltage-to-power sensitivity estimation and voltage regulation. A novel voltage control method for distribution networks using PMU based sensitivity estimation is proposed in this paper. The voltage control records are extracted from the historical synchronized phasor measurements. The voltage-to-power sensitivities to reflect the relation of voltage change and power fluctuation are estimated with the obtained voltage control records. In addition to linear parameter, parameters to match the nonlinear relation between voltage and power variation and to track the operation conditions are introduced in the fitting model for sensitivity estimation to improve the accuracy of the voltage control strategy. A voltage control scheme is proposed based on the sensitivities estimated in which the measurements of partial nodes at the distribution network are the only needed data. Case studies on IEEE 33-node test feeder verify the correctness and effectiveness of the proposed method.

Impact of Causality on Performance of Phasor Measurement Unit Algorithms

Most existing phasor measurement units (PMUs) are noncausal PMUs and they compensate for the group delay in PMU applications by shifting time stamps, which may result in high latency that will impair performance of PMU applications. This paper presents causal PMUs to reduce the group delay caused latency without shifting time stamps, and studies the impact of causality on performance of PMU algorithms. The paper first analyzes how causal and noncausal PMUs compensate for the group delay caused by digital filters and it is found that causal PMUs normally reduce latency by the group delay, whereas noncausal PMU will not. Then, the impact of causality on performance of PMU algorithms is investigated and analyzed by using the Hydro Quebec Research Institute (IREQ) PMU model and the IEEE PMU model. Finally, the simulation results carried out on two test systems highlight the difference between the causal method and the noncausal method under fault conditions in realistic multimachine setups.