Academic literature on the topic 'PMU-Phasor Measurement System'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'PMU-Phasor Measurement System.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "PMU-Phasor Measurement System"
1
Liu, Min. "Distribution System State Estimation with Phasor Measurement Units." Applied Mechanics and Materials 668-669 (October 2014): 687–90. http://dx.doi.org/10.4028/www.scientific.net/amm.668-669.687.
Full textAbstract:
With phasor measurement units (PMU) become available in the distribution system; the estimation accuracy of the distribution system state estimation (DSSE) is expected to be improved. Based on the weighted least square (WLS) approach, this paper proposed a new state estimator which takes into account the PMU measurements including voltage magnitude and phasor angle, and load current magnitude and phasor angle. Simulation results indicate that the estimation accuracy is obvious improve by adding PMU measurements to the DSSE. Furthermore, the estimation accuracy changes with the installation site of PMU, and can be maximized by choosing the installation site appropriately.
2
Reis, Amanda Wohlfahrt, and Fernando Guilherme Kaehler Guarda. "Simulação de uma Unidade de Medição Fasorial em Tempo Real utilizando Typhoon Virtual HIL." Ciência e Natura 42 (February 7, 2020): 21. http://dx.doi.org/10.5902/2179460x40589.
Full textAbstract:
This paper aims to present a project to implement a phasor measurement unit (PMU), which is the main component in the synchronized phasor measurement system. This measurement technology aims to bring significant gains to the operation of electrical systems, since it allows to simultaneously measure magnitudes and phase angles of voltage and current at geographically distant points from the electrical system. So, the paper reports the use of filters in obtaining PMU measurements. In this way, it is intended to implement the PMU in the Typhoon Virtual HIL software.
3
Ponnala, Ravi, Muktevi Chakravarthy, and Suraparaju Venkata Naga Lakshmi Lalitha. "Effective monitoring of power system with phasor measurement unit and effective data storage system." Bulletin of Electrical Engineering and Informatics 11, no. 5 (2022): 2471–78. http://dx.doi.org/10.11591/eei.v11i5.4085.
Full textAbstract:
In the recent years the monitoring and operation of the power system became complex, due to the more demand from the different linear and non-linear loads and generation from the different sources. For the effective monitoring and operation of the power system, existing power system monitoring methods need to improve or new technologies are required. For the effective monitoring and operation of the power system phasor measurement unit (PMU) based monitoring is suitable, because it provide the dynamic state monitoring system. In this paper PMU based monitoring is proposed with effective data storage system and protection. With this method phasor values of voltage and current signals are calculated at the location of PMU and with the help of software based program effective data storage also possible. With this proposed model the phasor values in the power system at different locations monitoring also possible and required phasor data only stored and total data is only monitored. The phasor values of signals are calculated with direct phasor measurement technique in LabVIEW and by adding time stamping to the each phasor value accurate measurement of power flow is possible.
4
Pandey, Rachana, Dr H. K. Verma, Dr Arun Parakh, and Dr Cheshta Jain Khare. "Artificial Intelligence Based Optimal Placement of PMU." International Journal of Emerging Science and Engineering 10, no. 11 (2022): 1–6. http://dx.doi.org/10.35940/ijese.i2541.10101122.
Full textAbstract:
The investigation of power system disturbances is critical for ensuring the supply’s dependability and security. Phasor Measurement Unit (PMU) is an important device of our power network, installed on system to enable the power system monitoring and control. By giving synchronised measurements at high sample rates, Phasor Measurement Units have the potential to record quick transients with high precision. PMUs are gradually being integrated into power systems because they give important phasor information for power system protection and control in both normal and abnormal situations. Placement of PMU on every bus of the network is not easy to implement, either because of expense or because communication facilities in some portions of the system are limited. Different ways for placing PMUs have been researched to improve the robustness of state estimate. The paper proposes unique phasor measurement unit optimal placement methodologies. With full network observability, the suggested methods will assure optimal PMU placement. The proposed algorithm will be thoroughly tested using IEEE 7, 9, 14, and 24 standard test systems, with the results compared to existing approaches.
5
Rachana, Pandey, H.K. Verma Dr., Arun Parakh Dr., and Cheshta Jain Khare Dr. "Artificial Intelligence Based Optimal Placement of PMU." International Journal of Emerging Science and Engineering (IJESE) 10, no. 11 (2022): 1–5. https://doi.org/10.35940/ijese.I2541.10101122.
Full textAbstract:
<strong>Abstract:</strong> The investigation of power system disturbances is critical for ensuring the supply’s dependability and security. Phasor Measurement Unit (PMU) is an important device of our power network, installed on system to enable the power system monitoring and control. By givingsynchronised measurements at high sample rates, Phasor Measurement Units have the potential to record quick transients with high precision. PMUs are gradually being integrated into power systems because they give important phasor information for power system protection and control in both normal and abnormal situations. Placement of PMU on every bus of the network is not easy to implement, either because of expense or because communication facilities in some portions of the system are limited. Different ways for placing PMUs have been researched to improve the robustness of state estimate. The paper proposes unique phasor measurement unit optimal placement methodologies. With full network observability, the suggested methods will assure optimal PMU placement. The proposed algorithm will be thoroughly tested using IEEE 7, 9, 14, and 24 standard test systems, with the results compared to existing approaches.
6
Pandey, Rachana, Dr H. K. Verma, Dr Arun Parakh, and Dr Cheshta Jain Khare. "Optimization of Phasor Measurement Unit (PMU) Placement: A Review." International Journal of Emerging Science and Engineering 7, no. 4 (2021): 9–13. http://dx.doi.org/10.35940/ijese.e2518.117421.
Full textAbstract:
In today’s world, a Phasor Measurement Unit (PMU) is a crucial component of our power network for managing, controlling, and monitoring. PMU can provide synchronized voltage current, and frequency measurements in real time. We can't put a PMU in every bus in the electrical grid because it's not viable from a productivity and economic standpoint, and it's also not practical for handling huge data. As a result, it's critical to reduce the amount of PMU in the power network while also increasing the power network's observability. The optimal PMU placement problem is solved using a variety of methodologies. The paper's main goal is to provide a brief overview of synchrophasor technology, phasor measurement units (PMU), and optimal PMU placement in order to reduce the number of PMUs in the system while maintaining complete observability and application in today's power systems.
7
Rachana, Pandey, Verma H.K., Parakh Arun, and Jain Khare Cheshta. "Optimization of Phasor Measurement Unit (PMU) Placement: A Review." International Journal of Emerging Science and Engineering (IJESE) 7, no. 4 (2021): 9–13. https://doi.org/10.35940/ijese.E2518.117421.
Full textAbstract:
In today’s world, a Phasor Measurement Unit (PMU) is a crucial component of our power network for managing, controlling, and monitoring. PMU can provide synchronized voltage current, and frequency measurements in real time. We can't put a PMU in every bus in the electrical grid because it's not viable from a productivity and economic standpoint, and it's also not practical for handling huge data. As a result, it's critical to reduce the amount of PMU in the power network while also increasing the power network's observability. The optimal PMU placement problem is solved using a variety of methodologies. The paper's main goal is to provide a brief overview of synchrophasor technology, phasor measurement units (PMU), and optimal PMU placement in order to reduce the number of PMUs in the system while maintaining complete observability and application in today's power systems.
8
Zakri, Azriyenni Azhari, Rangga Eka Saputra, Makmur Saini, and Hidayat Hidayat. "Distributed Generation installed by the Phasor Measurement Unit to improve voltage." SINERGI 26, no. 1 (2022): 37. http://dx.doi.org/10.22441/sinergi.2022.1.006.
Full textAbstract:
This study is intended to design a system connected to the Distributed Generation (DG) sourced from solar cells, using Matlab/Simulink. A Phasor Measurement Unit (PMU) is installed in the DG system to monitor the phasor voltage and current. Furthermore, the system comprises four buses with two 20 kV load voltages, two amplifying transformers, and four transmission lines. The DG's role is to keep the power supply to the load stable and improve power efficiency by reducing power losses on the network. However, in this network, the DG increases the current on each bus. Thus, affecting voltage increase on each bus, consequently increasing the stress experienced by both loads. The DG-connected system simulation on PMU-3 & PMU-4 has a minute error value of 0.02% and is slightly higher than the unconnected simulation. This comparison also shows the positive sequence values of the phasor currents as well as phasor voltages before and after the DG connection. The DG system connected to the PMU has monitored voltage and current for PLN and DG systems based on the simulation results. Therefore, installing the DG can increase the line voltage, especially on the load.
9
Ravi, Ponnala, Chakravarthy Muktevi, and Venkata Naga Lakshmi Lalitha Suraparaju. "Performance and comparison of different phasor calculation techniques for the power system monitoring." Bulletin of Electrical Engineering and Informatics 11, no. 3 (2022): 1246~1253. https://doi.org/10.11591/eei.v11i3.3833.
Full textAbstract:
Day to day to electrical power demand increases very rapidly with linear and non-linear load demands. Especially the nonlinear loads are creating the harmonics in the current and voltage signals. The current and voltage signal values are measured with the phasor measurement unit (PMU) for the proper magnitude and phase angle calculation even in the presence of harmonic components in the signals. The performance of the PMU is depending upon the phasor calculation technique. Different technique/methods are available for the phasor calculation, from the method to method there is difference in the accuracy, phasor computation time and complexity. In this paper various techniques for phasor calculation are presented. For better performance of PMU, more accurate and less computation time for phasor calculation technique is required. But in real time, accuracy and speed both may not satisfied with single technique. Need to find a satisfactory technique, which satisfies the speed of phasor computation and accuracy. In this paper it is proposed that direct phasor estimation technique, which gives the better results in terms of accuracy and time and this method, satisfies the requirements for the dynamic monitoring of power system according to the IEEE std. C37.118.1-2011.
10
Bartolomey, Petr, and Sergey Semenenko. "Phasor Measurements Application in Power Systems for Accelerated Power Flow Calculations in Emergency Control." Applied Mechanics and Materials 792 (September 2015): 286–92. http://dx.doi.org/10.4028/www.scientific.net/amm.792.286.
Full textAbstract:
Power system’s voltage phasor (phase and amplitude) measurements provided by phasor measurement unit (PMU) gives opportunity to build the algorithm of PMU assessment generating triangular admittance matrix. It allows reducing of the power system power flow calculation to the sequential solving of single equations with one variable at a time, instead of conventional linear equations system solving. The effect of super accelerated calculation is important for on-line operative calculations and for emergency control systems with pre-selected settings. This paper considers the general features of the algorithm. The paper presents test results obtained from the IEEE power system models and big power systems for more than 3000 buses. The PMU and SCADA concurrent use was concerned.
Dissertations / Theses on the topic "PMU-Phasor Measurement System"
1
Wu, Zhongyu. "Synchronized Phasor Measurement Units Applications in Three-phase Power System." Diss., Virginia Tech, 2013. http://hdl.handle.net/10919/51660.
Full textAbstract:
Phasor Measurement Units (PMUs) are widely acknowledged as one of the most significant developments in the field of real-time monitoring of power system. By aligning time stamps of voltage and current phasor measurements, which are consistent with Coordinated Universal Time (UTC), a coherent picture of the power system state can be achieved through either direct measurements or simple linear calculations. With the growing number of PMUs installed or planned to be installed in the near future, both utilities and research institutions are looking for novel applications of synchrophasor measurements from these widely installed PMUs. In this dissertation, the author proposes two new PMUs measurements applications: three-phase instrument transformer calibration, and three-phase line parameter calculation with instrument transformers.
First application is to calibrate instrument transformers. Instrument transformers are the main sensors used in power systems. They provide isolation between high voltage level of primary side and metering level of the secondary side. All the monitoring and measuring systems obtain input signals from the secondary side of instrument transformers. That means when instrument transformers are not accurate, all the measurements used in power system are inaccurate. The most important job of this dissertation is to explore a method to automatically calibrate all the instrument transformers in the power system based on real-time synchrophasor measurements.
The regular instrument transformer calibration method requires the instrument transformer to be out of service (offline) and calibrated by technicians manually. However, the error of instrument transformer changes when environment changes, and connected burden. Therefore, utilities are supposed to periodically calibrate instrument transformers at least once a year. The high labor and economic costs make traditional instrument transformer calibration method become one of the urgent problems in power industry. In this dissertation we introduce a novel, low cost and easy method to calibrate three-phase instrument transformers. This method only requires one three-phase voltage transformer at one bus calibrated in advance. All other instrument transformers can be calibrated by this method as often as twice a day, based on the synchrophasor measurements under different load scenarios.
Second application is to calculate line parameters during calibrating instrument transformers. The line parameters, line impedance and line shunt admittance, as needed by utilities are generated by the computer method. The computer method is based on parameters, such as the diameter, length, material characteristics, the distance among transmission line, the distance to ground and so on. The formulas to calculate line parameters have been improved and re-modeled from time to time in order to increase the accuracy. However, in this case, the line parameters are still inaccurate due to various reasons. The line parameters errors do affect the instrument transformers calibration results (with 5% to 10% error). To solve this problem, we present a new method to calculate line parameters and instrument transformers in the same processing step.
This method to calibrate line parameter and instrument transformers at the same time only needs one pre-calibrated voltage transformer and one pre-calibrated current transformer in power system. With the pre-calibrated instrument transformers, the line parameter as well as the ratio correction factors of all the other instrument transformers can be solved automatically. Simulation results showed the errors between calculated line parameters and the real line parameter, the errors between calibrated ratio correction factors and the real ratio correction factors are of the order of 10e-10 per unit. Therefore, high accuracy line parameters as well as perfectly calibrated instrument transformers can be obtained by this new method. This method can run automatically every day. High accuracy and dynamic line parameters will significantly improve power system models. It will also increase the reliability and speed of the relay system, enhance the accuracy of power system analysis, and benefit all other researches using line parameters. New methods of calculating line parameter and the instrument transformer calibrations will influence the whole power industry significantly.<br>Ph. D.
2
Zhong, Zhian. "Power Systems Frequency Dynamic Monitoring System Design and Applications." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/28707.
Full textAbstract:
Recent large-scale blackouts revealed that power systems around the world are far from the stability and reliability requirement as they suppose to be. The post-event analysis clarifies that one major reason of the interconnection blackout is lack of wide area information. Frequency dynamics is one of the most important parameters of an electrical power system. In order to understand power system dynamics effectively, accurately measured wide-area frequency is needed. The idea of building an Internet based real-time GPS synchronized wide area Frequency Monitoring Network (FNET) was proposed to provide the imperative dynamic information for the large-scale power grids and the implementation of FNET has made the synchronized observations of the entire US power network possible for the first time. The FNET system consists of Frequency Disturbance Recorders (FDR), which work as the sensor devices to measure the real-time frequency at 110V single-phase power outlets, and an Information Management System (IMS) to work as a central server to process the frequency data. The device comparison between FDR and commercial PMU (Phasor Measurement Unit) demonstrate the advantage of FNET. The web visualization tools make the frequency data available for the authorized users to browse through Internet.
The research work addresses some preliminary observations and analyses with the field-measured frequency information from FNET. The original algorithms based on the frequency response characteristic are designed to process event detection, localization and unbalanced power estimation during frequency disturbances. The analysis of historical cases illustrate that these algorithms can be employed in real-time level to provide early alarm of abnormal frequency change to the system operator. The further application is to develop an adaptive under frequency load shedding scheme with the processed information feed in to prevent further frequency decline in power systems after disturbances causing dangerous imbalance between the load and generation.<br>Ph. D.
3
Sanchez, Ayala Gerardo. "Centralized Control of Power System Stabilizers." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/51754.
Full textAbstract:
This study takes advantage of wide area measurements to propose a centralized nonlinear controller that acts on power system stabilizers, to cooperatively increase the damping of problematic small signal oscillations all over the system. The structure based on decision trees results in a simple, efficient, and dependable methodology that imposes much less computational burden than other nonlinear design approaches, making it a promising candidate for actual implementation by utilities and system operators.
Details are given to utilize existing stabilizers while causing minimum changes to the equipment, and warranting improvement or at least no detriment of current system behavior. This enables power system stabilizers to overcome their inherent limitation to act only on the basis of local measurements to damp a single target frequency. This study demonstrates the implications of this new input on mathematical models, and the control functionality that is made available by its incorporation to conventional stabilizers.
In preparation of the case of study, a heuristic dynamic reduction methodology is introduced that preserves a physical equivalent model, and that can be interpreted by any commercial software package. The steps of this method are general, versatile, and of easy adaptation to any particular power system model, with the aggregated value of producing a physical model as final result, that makes the approach appealing for industry. The accuracy of the resulting reduced network has been demonstrated with the model of the Central American System.<br>Ph. D.
4
Zhou, Ming. "Advanced System Monitoring with Phasor Measurements." Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/27813.
Full textAbstract:
Phasor Measurement Units (PMUs) are widely acknowledged as one of the most promising developments in the field of real-time monitoring of power systems. By aligning the time stamps of voltage and current phasor measurements that are consistent with Coordinated Universal Time (UTC), a coherent picture of the power system state can be achieved through either direct measurements or simple linear calculations. With the growing number of PMUs planned for installation in the near future, both utilities and research institutions are looking for the best solutions to the placement of units as well as to the applications that make the most of phasor measurements.
This dissertation explores a method for optimal PMU placement as well as two applications of synchronized phasor measurements in state estimation. The pre-processing PMU placement method prepares the system data for placement optimization and reduces the size of the optimization problem. It is adaptive to most of the optimal placement methods and can save a large amount of computational effort. Depth of un-observability is one of the criteria to allow the most benefit out of a staged placement of the units. PMUs installed in the system provide synchronized phasor measurements that are highly beneficial to power system state estimations. Two related applications are proposed in the dissertation. First, a post-processing inclusion of phasor measurements in state estimators is introduced. This method avoids the revision of the existing estimators and is able to realize similar results as mixing phasor data with traditional SCADA with a linear afterwards step. The second application is a method to calibrate instrument transformers remotely using phasor measurements. Several scans of phasor measurements are used to accomplish estimating system states in conjunction with complex instrument transformer correction factors. Numerical simulation results are provided for evaluation of the calibration performance with respect to the number of scans and load conditions.
Conducting theoretical and numerical analysis, the methods and algorithms developed in this dissertation are aimed to strategically place PMUs and to incorporate phasor measurements into state estimators effectively and extensively for better system state monitoring. Simulation results show that the proposed placement method facilitates approaching the exact optimal placement while keep the computational effort low. Simulation also shows that the use of phasor measurement with the proposed instrument transformer correction factors and proposed state estimation enhancement largely improves the quality of state estimations.<br>Ph. D.
5
Tuku, Woldu. "Distributed state estimation using phasor measurement units (PMUs)for a system snapshot." Kansas State University, 2012. http://hdl.handle.net/2097/14129.
Full textAbstract:
Master of Science<br>Department of Electrical and Computer Engineering<br>Noel N. Schulz<br>As the size of electric power systems are increasing, the techniques to protect, monitor and control them are becoming more sophisticated. Government, utilities and various organizations are striving to have a more reliable power grid. Various research projects are working to minimize risks on the grid. One of the goals of this research is to discuss a robust and accurate state estimation (SE) of the power grid. Utilities are encouraging teams to change the conventional way of state estimation to real time state estimation. Currently most of the utilities use traditional centralized SE algorithms for transmission systems.
Although the traditional methods have been enhanced with advancement in technologies, including PMUs, most of these advances have remained localized with individual utility state estimation. There is an opportunity to establish a coordinated SE approach integration using PMU data across a system, including multiple utilities and this is using Distributed State Estimation (DSE). This coordination will minimize cascading effects on the power system. DSE could be one of the best options to minimize the required communication time and to provide accurate data to the operators. This project will introduce DSE techniques with the help of PMU data for a system snapshot. The proposed DSE algorithm will split the traditional central state estimation into multiple local state estimations and show how to reduce calculation time compared with centralized state estimation. Additionally these techniques can be implemented in micro-grid or islanded system.
6
Ghassempour, Aghamolki Hossein. "Phasor Measurement Unit Data-based States and Parameters Estimation in Power System." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6505.
Full textAbstract:
The dissertation research investigates estimating of power system static and dynamic states (e.g. rotor angle, rotor speed, mechanical power, voltage magnitude, voltage phase angle, mechanical reference point) as well as identification of synchronous generator parameters. The research has two focuses:
i. Synchronous generator dynamic model states and parameters estimation using real-time PMU data.
ii.Integrate PMU data and conventional measurements to carry out static state estimation.
The first part of the work focuses on Phasor Measurement Unit (PMU) data-based synchronous generator states and parameters estimation. In completed work, PMU data-based synchronous generator model identification is carried out using Unscented Kalman Filter (UKF). The identification not only gives the states and parameters related to a synchronous generator swing dynamics but also gives the states and parameters related to turbine-governor and primary and secondary frequency control. PMU measurements of active power and voltage magnitude, are treated as the inputs to the system while voltage phasor angle, reactive power, and frequency measurements are treated as the outputs. UKF-based estimation can be carried out at real-time. Validation is achieved through event play back to compare the outputs of the simplified simulation model and the PMU measurements, given the same input data. Case studies are conducted not only for measurements collected from a simulation model, but also for a set of real-world PMU data. The research results have been disseminated in one published article.
In the second part of the research, new state estimation algorithm is designed for static state estimation. The algorithm contains a new solving strategy together with simultaneous bad data detection. The primary challenge in state estimation solvers relates to the inherent non-linearity and non-convexity of measurement functions which requires using of Interior Point algorithm with no guarantee for a global optimum solution and higher computational time. Such inherent non-linearity and non-convexity of measurement functions come from the nature of power flow equations in power systems.
The second major challenge in static state estimation relates to the bad data detection algorithm. In traditional algorithms, Largest Normalized Residue Test (LNRT) has been used to identify bad data in static state estimation. Traditional bad data detection algorithm only can be applied to state estimation. Therefore, in a case of finding any bad datum, the SE algorithm have to rerun again with eliminating found bad data. Therefore, new simultaneous and robust algorithm is designed for static state estimation and bad data identification.
In the second part of the research, Second Order Cone Programming (SOCP) is used to improve solving technique for power system state estimator. However, the non-convex feasible constraints in SOCP based estimator forces the use of local solver such as IPM (interior point method) with no guarantee for quality answers. Therefore, cycle based SOCP relaxation is applied to the state estimator and a least square estimation (LSE) based method is implemented to generate positive semi-definite programming (SDP) cuts. With this approach, we are able to strengthen the state estimator (SE) with SOCP relaxation. Since SDP relaxation leads the power flow problem to the solution of higher quality, adding SDP cuts to the SOCP relaxation makes Problem’s feasible region close to the SDP feasible region while saving us from computational difficulty associated with SDP solvers. The improved solver is effective to reduce the feasible region and get rid of unwanted solutions violate cycle constraints. Different Case studies are carried out to demonstrate the effectiveness and robustness of the method.
After introducing the new solving technique, a novel co-optimization algorithm for simultaneous nonlinear state estimation and bad data detection is introduced in this dissertation. ${\ell}_1$-Norm optimization of the sparse residuals is used as a constraint for the state estimation problem to make the co-optimization algorithm possible. Numerical case studies demonstrate more accurate results in SOCP relaxed state estimation, successful implementation of the algorithm for the simultaneous state estimation and bad data detection, and better state estimation recovery against single and multiple Gaussian bad data compare to the traditional LNRT algorithm.
7
Mazloomzadeh, Ali. "Development of Hardware in the Loop Real-Time Control Techniques for Hybrid Power Systems Involving Distributed Demands and Sustainable Energy Sources." FIU Digital Commons, 2014. http://digitalcommons.fiu.edu/etd/1666.
Full textAbstract:
The future power grid will effectively utilize renewable energy resources and distributed generation to respond to energy demand while incorporating information technology and communication infrastructure for their optimum operation. This dissertation contributes to the development of real-time techniques, for wide-area monitoring and secure real-time control and operation of hybrid power systems.
To handle the increased level of real-time data exchange, this dissertation develops a supervisory control and data acquisition (SCADA) system that is equipped with a state estimation scheme from the real-time data. This system is verified on a specially developed laboratory-based test bed facility, as a hardware and software platform, to emulate the actual scenarios of a real hybrid power system with the highest level of similarities and capabilities to practical utility systems. It includes phasor measurements at hundreds of measurement points on the system. These measurements were obtained from especially developed laboratory based Phasor Measurement Unit (PMU) that is utilized in addition to existing commercially based PMU’s. The developed PMU was used in conjunction with the interconnected system along with the commercial PMU’s. The tested studies included a new technique for detecting the partially islanded micro grids in addition to several real-time techniques for synchronization and parameter identifications of hybrid systems.
Moreover, due to numerous integration of renewable energy resources through DC microgrids, this dissertation performs several practical cases for improvement of interoperability of such systems. Moreover, increased number of small and dispersed generating stations and their need to connect fast and properly into the AC grids, urged this work to explore the challenges that arise in synchronization of generators to the grid and through introduction of a Dynamic Brake system to improve the process of connecting distributed generators to the power grid.
Real time operation and control requires data communication security. A research effort in this dissertation was developed based on Trusted Sensing Base (TSB) process for data communication security. The innovative TSB approach improves the security aspect of the power grid as a cyber-physical system. It is based on available GPS synchronization technology and provides protection against confidentiality attacks in critical power system infrastructures.
8
Jones, Kevin David. "Three-Phase Linear State Estimation with Phasor Measurements." Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/32119.
Full textAbstract:
Given the ability of the Phasor Measurement Unit (PMU) to directly measure the system state and the increasing implementation of PMUs across the electric power industry, a natural expansion of state estimation techniques would be one that employed the exclusive use of PMU data. Dominion Virginia Power and the Department of Energy (DOE) are sponsoring a research project which aims to implement a three phase linear tracking state estimator on Dominionâ s 500kV network that would use only PMU measurements to compute the system state. This thesis represents a portion of the work completed during the initial phase of the research project. This includes the initial development and testing of two applications: the three phase linear state estimator and the topology processor. Also presented is a brief history of state estimation and PMUs, traditional state estimation techniques and techniques with mixed phasor data, a development of the linear state estimation algorithms and a discussion of the future work associate with this research project.<br>Master of Science
9
Guo, Tingyan. "On-line identification of power system dynamic signature using PMU measurements and data mining." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/online-identification-of-power-system-dynamic-signature-using-pmu-measurements-and-data-mining(989938d4-c236-48a7-a653-17326937f5b4).html.
Full textAbstract:
This thesis develops a robust methodology for on-line identification of power system dynamic signature based on incoming system responses from Phasor Measurement Units (PMUs) in Wide Area Measurement Systems (WAMS). Data mining techniques are used in the methodology to convert real-time monitoring data into transient stability information and the pattern of system dynamic behaviour in the event of instability. The future power system may operate closer to its stability limit in order to improve its efficiency and economic value. The changing types and patterns of load and generation are resulting in highly variable operating conditions. Corrective control and stabilisation is becoming a potentially viable option to enable safer system operation. In the meantime, the number of WAMS projects and PMUs is rising, which will significantly improve the system situational awareness. The combination of all these factors means that it is of vital importance to exploit a new and efficient Transient Stability Assessment (TSA) tool in order to use real-time PMU data to support decisions for corrective control actions. Data mining has been studied as the innovative solution and considered as promising. This work contributes to a number of areas of power systems stability research, specifically around the data driven approach for real-time emergency mode TSA. A review of past research on on-line TSA using PMU measurements and data mining is completed, from which the Decision Tree (DT) method is found to be the most suitable. This method is implemented on the test network. A DT model is trained and the sensitivity of its prediction accuracy is assessed according to a list of network uncertainties. Results showed that DT is a useful tool for on-line TSA for corrective control approach. Following the implementation, a generic probabilistic framework for the assessment of the prediction accuracy of data mining models is developed. This framework is independent of the data mining technique. It performs an exhaustive search of possible contingencies in the testing process and weighs the accuracies according to the realistic probability distribution of uncertain system factors, and provides the system operators with the confidence level of the decisions made under emergency conditions. After that, since the TSA for corrective control usually focuses on transient stability status without dealing with the generator grouping in the event of instability, a two-stage methodology is proposed to address this gap and to identify power system dynamic signature. In this methodology, traditional binary classification is used to identify transient stability in the first stage; Hierarchical Clustering is used to pre-define patterns of unstable dynamic behaviour; and different multiclass classification techniques are investigated to identify the patterns in the second stage. Finally, the effects of practical issues related to WAMS on the data mining methodologies are investigated. Five categories of issues are discussed, including measurement error, communication noise, wide area signal delays, missing measurements, and a limited number of PMUs.
10
Retty, Hema. "Load Modeling using Synchrophasor Data for Improved Contingency Analysis." Diss., Virginia Tech, 2016. http://hdl.handle.net/10919/78328.
Full textAbstract:
For decades, researchers have sought to make the North American power system as
reliable as possible with many security measures in place to include redundancy. Yet the
increasing number of blackouts and failures have highlighted the areas that require
improvement. Meeting the increasing demand for energy and the growing complexity of the
loads are two of the main challenges faced by the power grid. In order to prepare for
contingencies and maintain a secure state, power engineers must perform simulations using
steady state and dynamic models of the system. The results from the contingency studies are
only as accurate as the models of the grid components. The load components are generally the most difficult to model since they are controlled by the consumer. This study focuses on
developing static and dynamic load models using advanced mathematical approximation
algorithms and wide area measurement devices, which will improve the accuracy of the system
analysis and hopefully decrease the frequency of blackouts.
The increasing integration of phasor measurement units (PMUs) into the power system
allows us to take advantage of synchronized measurements at a high data rate. These devices
are capable of changing the way we manage online security within the Energy Management
System (EMS) and can enhance our offline tools. This type of data helps us redevelop the
measurement-based approach to load modeling.
The static ZIP load model composition is estimated using a variation of the method of
least squares, called bounded-variable least squares. The bound on the ZIP load parameters
allows the measurement matrix to be slightly correlated. The ZIP model can be determined
within a small range of error that won't affect the contingency studies. Machine learning is used
to design the dynamic load model. Neural network training is applied to fault data obtained
near the load bus and the derived network model can estimate the load parameters. The neural network is trained using simulated data and then applied to real PMU measurements. A PMU algorithm was developed to transform the simulated measurements into a realistic
representation of phasor data. These new algorithms will allow us to estimate the load models
that are used in contingency studies.<br>Ph. D.
Book chapters on the topic "PMU-Phasor Measurement System"
1
Recioui, Abdelmadjid. "Application of Teaching Learning-Based Optimization to the Optimal Placement of Phasor Measurement Units." In Handbook of Research on Emergent Applications of Optimization Algorithms. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-2990-3.ch018.
Full textAbstract:
In recent years, the placement of phasor measurement units (PMUs) in electric transmission systems has gained much attention. This chapter presents a binary teaching learning based optimization (BTLBO) algorithm for the optimal placement of phasor measurement units (PMUs). The optimal PMU placement problem is formulated to minimize the number of PMUs installation subject to full network observability at the power system buses. The efficiency of the proposed method is verified by the simulation results of IEEE14-bus, 30-bus, 57-bus-118 bus systems, respectively. The results show that the whole system can be observable with installing PMUs on less than 25% of system buses. For verification of our proposed method, the results are compared with some newly reported methods which show the method as a novel effective solution to obtain system measurements with the least number of phasor measurement units.
2
Bentarzi, Hamid, and Abderrahmane Ouadi. "PMU Phasor Estimation Using Different Techniques." In Advances in Computer and Electrical Engineering. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-4027-5.ch004.
Full textAbstract:
Many models of phasor measurement units (PMU) have been implemented; however, few dynamic models have been developed when the power system parameters change. It is necessary to use a method that can somehow estimate the frequency and correct the phasors. The conventional way to determine frequency is to detect zero crossings per unit time. However, this method has many drawbacks such as high cost and low accuracy. Also, after the frequency determination, the phasor should be corrected by suitably modifying the algorithm without omitting any data. This chapter presents different estimation techniques such as discrete Fourier transform (DFT), smart discrete Fourier transform (SDFT) that may be used to estimate the phasors. These estimated values would be incorrect if the input signals are at an off-nominal frequency and the phase angles would drift away from the true values. To correct this issue, first of all, the off-nominal frequency has been estimated using different techniques such as least error squares and phasor measurement angle changing, and then it is used to correct the phasors.
3
Dixit, Ashutosh, Arindam Chowdhury, and Parvesh Saini. "A review on optimal placement of phasor measurement unit (PMU)." In System Assurances. Elsevier, 2022. http://dx.doi.org/10.1016/b978-0-323-90240-3.00028-x.
Full text
4
Alhelou, H. H. "An Overview of Wide Area Measurement System and Its Application in Modern Power Systems." In Handbook of Research on Smart Power System Operation and Control. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8030-0.ch012.
Full textAbstract:
In this chapter, wide area measurement systems (WAMS), which are one of the cornerstones in modern power systems, are overviewed. The WAMS has great applications in power system monitoring, operation, control, and protection systems. In the modern power systems, WAMS is adopted as a base for the modern monitoring and control techniques. Therefore, an introduction of WAMS is firstly provided. Then, phasor measurement unit (PMU), which is the base of WAMS, is described. Afterward, the most recent developments in power system estimation, stability, and security techniques, which are based on WAMS, are introduced. Later, general system setup for WAMS-based under-frequency load shedding (UFLS) is provided. Finally, the required communications infrastructures are comprehensively discussed.
5
Bentarzi, Hamid. "PMU Placement Optimization for Fault Observation Using Different Techniques." In Advances in Computer and Electrical Engineering. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-4027-5.ch009.
Full textAbstract:
This chapter presents different techniques for obtaining the optimal number of the phasor measurement units (PMUs) that may be installed in a smart power grid to achieve full network observability under fault conditions. These optimization techniques such as binary teaching learning based optimization (BTLBO) technique, particle swarm optimization, the grey wolf optimizer (GWO), the moth-flame optimization (MFO), the cuckoo search (CS), and the wind-driven optimization (WDO) have been developed for the objective function and constraints alike. The IEEE 14-bus benchmark power system has been used for testing these optimization techniques by simulation. A comparative study of the obtained results of previous works in the literature has been conducted taking into count the simplicity of the model and the accuracy of characteristics.
6
Ah King, Robert T. F., and Samiah Mohangee. "A Reliability-Based Two Stage Phasor Measurement Unit (PMU) Placement Optimisation Model Using Mathematical- and Nature-Based Evolutionary Algorithms." In Artificial Intelligence, Engineering Systems and Sustainable Development. Emerald Publishing Limited, 2024. http://dx.doi.org/10.1108/978-1-83753-540-820241010.
Full textConference papers on the topic "PMU-Phasor Measurement System"
1
Bečejac, Vladimir. "OPTIMIZATION OF PMU PLACEMENT FOR IMPROVED NETWORK OBSERVABILITY USING MATLAB." In 21.Simpozijum CIGRE Srbija 2024. Srpski nacionalni komitet Međunarodnog saveta za velike električne mreže CIGRE Srbija, 2024. https://doi.org/10.46793/cigre21s.112b.
Full textAbstract:
This paper presents the development and implementation of a MATLAB application for the optimal placement of PMU (Phasor Measurement Units) devices in the power system. The aim of the application is to maximize the reliability and efficiency of system monitoring, ensuring full topological observability of the network. By utilizing linear and advanced optimization methods (Particle Swarm Optimization), the application identifies the best locations for PMU devices, taking into account classical analyses, N-1 analyses, and existing PMU devices. The described activities were carried out through the European Horizon 2020 project Reliability, Resilience, and Defense Technology for the Grid-R2D2.
2
Lee, Jonathan. "Automatic Fault Location on Distribution Networks Using Synchronized Voltage Phasor Measurement Units." In ASME 2014 Power Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/power2014-32231.
Full textAbstract:
Automatic fault location on the distribution system is a necessity for a resilient grid with fast service restoration after an outage. Motivated by the development of low cost synchronized voltage phasor measurement units (PMUs) for the distribution system, this paper describes how PMU data during a fault event can be used to accurately locate faults on the primary distribution system. Rather than requiring many specialized line sensors to enable fault location, the proposed approach leverages a PMU data stream that can be used for a variety of applications, making it easier to justify the investment in fault location. The accuracy of existing automatic fault location techniques are dependent either on dense deployments of line sensors or unrealistically accurate models of system loads. This paper demonstrates how synchronized voltage measurements enable sufficiently accurate fault location with relatively few instrumentation devices and relatively low fidelity system models. The IEEE 123 bus distribution feeder is examined as a test case, and the proposed algorithm is demonstrated to be robust to variations in total load and uncertainty in the response of loads to voltage sags during a sample set of varied fault conditions.
3
Bazerque, Juan Andres, Monzon, Pablo, and Giusto, Alvaro. "Online prediction of power system trajectories from phasor measurement unit (PMU) data." In XXII Congresso Brasileiro de Automática. SBA Sociedade Brasileira de Automática, 2018. http://dx.doi.org/10.20906/cps/cba2018-0324.
Full text
4
Kumar, Jitender, J. N. Rai, and Naimul Hasan. "Use of Phasor Measurement Unit (PMU) for large scale power system state estimation." In 2012 IEEE 5th India International Conference on Power Electronics (IICPE). IEEE, 2012. http://dx.doi.org/10.1109/iicpe.2012.6450371.
Full text
5
Noureen, Subrina Sultana, Vishwajit Roy, and Stephen B. Bayne. "Phasor measurement unit integration: A review on optimal PMU placement methods in power system." In 2017 IEEE Region 10 Humanitarian Technology Conference (R10-HTC). IEEE, 2017. http://dx.doi.org/10.1109/r10-htc.2017.8288967.
Full text
6
Gholami, Mohammad, Ali Abbaspour Tehrani Fard, and Moein Moeini-Aghtaie. "Linear Voltage Based State Estimator for Active Distribution System Including Phasor Measurement Unit (PMU)." In 2018 23rd Electrical Power Distribution Conference (EPDC). IEEE, 2018. http://dx.doi.org/10.1109/epdc.2018.8536296.
Full text
7
Narendra, Krish, Zhiying Zhang, John Lane, Bill Lackey, and Ed Khan. "Calibration and testing of TESLA Phasor Measurement Unit (PMU) using doble F6150 test instrument." In 2007 iREP Symposium - Bulk Power System Dynamics and Control - VII. Revitalizing Operational Reliability. IEEE, 2007. http://dx.doi.org/10.1109/irep.2007.4410561.
Full text
8
Bundalo, Igor, Goran Jakupović, Marija Popović, Srđan Subotić, and Dušan Prešić. "Implementation of ENTSO-E emergency and restoration procedure in a real-time environment." In International Conference IcETRAN. ETRAN Society, Academic Mind, Belgrade, 2024. https://doi.org/10.69994/11ic24010.
Full textAbstract:
This paper describes one implementation of the ENTSO-E emergency and restoration procedure in a real-time environment. The initial system, featuring this procedure, was developed as part of the Horizon 2020 Trinity project. The system was implemented in a study environment and tested on a network model that simulates the behavior of the power system model of Serbia and the zone observability of neighboring Transmission System Operators (TSOs). Within the framework of the R2D2 project, improvements to this system are underway. While in the initial system version, the identification of islanding events relied solely on topological analysis, in this iteration, the algorithm will be expanded with additional verification based on precise frequency measurements obtained through Phasor Measurement Unit (PMU) devices.
9
Mukundan, Mijaz, and P. Jayaprakash. "SPIDER: A GSM/GPRS based interconnected Phasor Measurement Unit (PMU) system for prevention of communication failures." In 2014 6th IEEE Power India International Conference (PIICON). IEEE, 2014. http://dx.doi.org/10.1109/34084poweri.2014.7117673.
Full text
10
Mukundan, Mijaz, and P. Jayaprakash. "SPIDER: A GSM/GPRS based interconnected Phasor Measurement Unit (PMU) system for prevention of communication failures." In 2014 6th IEEE Power India International Conference (PIICON). IEEE, 2014. http://dx.doi.org/10.1109/poweri.2014.7117673.
Full text