Phasor Measurement Units Placement Research Articles

Phasor Measurement Units Optimal Placement and Performance Limits for Fault Localization

In this paper, the performance limits of faults localization are investigated using synchrophasor data. The focus is on a non-trivial operating regime where the number of Phasor Measurement Unit (PMU) sensors available is insufficient to have full observability of the grid state. Proposed analysis uses the Kullback Leibler (KL) divergence between the distributions corresponding to different fault location hypotheses associated with the observation model. This analysis shows that the most likely locations are concentrated in clusters of buses more tightly connected to the actual fault site akin to graph communities. Consequently, a PMU placement strategy is derived that achieves a near-optimal resolution for localizing faults for a given number of sensors. The problem is also analyzed from the perspective of sampling a graph signal, and how the placement of the PMUs i.e. the spatial sampling pattern and the topological characteristic of the grid affect the ability to successfully localize faults. To highlight the superior performance of presented fault localization and placement algorithms, the proposed strategy is applied to a modified IEEE 34, IEEE-123 bus test cases and to data from a real distribution grid. Additionally, the detection of cyber-physical attacks is also examined where PMU data and relevant Supervisory Control and Data Acquisition (SCADA) network traffic information are compared to determine if a network breach has affected the integrity of the system information and/or operations.

Research on Optimal D-PMU Placement Technology to Improve the Observability of Smart Distribution Networks

With the continuous development of smart distribution networks, their observable problems have become more serious. Research on the optimal placement of the distribution phasor measurement unit (D-PMU) is an important way to improve the measurability, observability and controllability of a smart distribution network. In this paper, the optimal D-PMU placement methods and implementation technology were studied to determine the optimal D-PMU placement scheme. Considering the bus vulnerability index and the different operating states of the system, the more practical one-time optimal placement methods to ensure complete system observability was proposed. On this basis, the system's measurement redundancy and unobservable depth were considered to realize the multistage optimal D-PMU placement. The corresponding mathematical model and solution flow were given. Then the implementation technology of the methods was studied and the optimal D-PMU placement assistant decision-making software for smart distribution network was developed. Thereby, the structure and requirements of different distribution networks can be satisfied. The application analysis, functional architecture and the overall design process were given. Finally, the methods and software were analyzed by using the IEEE 33 bus system and an actual project, the Guangzhou Nansha Yuan'an Substation. The verification results showed that the method and software mentioned in this paper can provide convenient and quick operation for optimal D-PMU placement, improve the efficiency of smart distribution network planning work, and promote the theoretical application level of smart distribution network planning results.

A Fault-Tolerance Based Approach to Optimal PMU Placement

Phasor measurement units (PMUs) have offered significant advancements in power system operation and control. Despite these advantages, the industry has been slow in adopting PMU technology. This slow adoption is partially due to the high cost of installing PMUs, which motivates the optimal PMU placement (OPP) problem. The work presented in this paper is motivated by the idea that the value of a high cost asset can be increased by deploying it to improve network fault-tolerance. This strategy of deploying PMUs in the proximity of higher probability contingencies increases the likelihood of more effective remedial actions, both preventive and corrective. The proposed OPP therefore considers both the cost and the extent to which the PMU placements will benefit system observability in the presence of network vulnerabilities. A bi-level framework is used for optimizing the network vulnerability and the installation cost of PMUs. In the proposed framework, the installation cost of PMUs is treated as the primary objective, and the observability, which incorporates the vulnerability analysis, is treated as the secondary objective. The proposed approach can be used as a multistage installation process or as a single-stage installation process. This approach uses evolutionary algorithms to optimize and prioritize locations and installation cost of the PMUs. The proposed approach is tested on the IEEE 14-bus, IEEE 30-bus, and IEEE reliability test system.

Real-Time Faulted Line Localization and PMU Placement in Power Systems Through Convolutional Neural Networks

Diverse fault types, fast reclosures, and complicated transient states after a fault event make real-time fault location in power grids challenging. Existing localization techniques in this area rely on simplistic assumptions, such as static loads, or require much higher sampling rates or total measurement availability. This paper proposes a faulted line localization method based on a convolutional neural network (CNN) classifier using bus voltages. Unlike prior data-driven methods, the proposed classifier is based on features with physical interpretations that improve the robustness of the location performance. The accuracy of our CNN-based localization tool is demonstrably superior to other machine learning classifiers in the literature. To further improve the location performance, a joint phasor measurement units placement strategy are proposed and validated against other methods. A significant aspect of our methodology is that under very low observability ( ${7\%}$ of buses), the algorithm is still able to localize the faulted line to a small neighborhood with high probability. The performance of our scheme is validated through simulations of faults of various types in the IEEE 39-bus and 68-bus power systems under varying uncertain conditions, system observability, and measurement quality.

Placement of PMU Optimally and Detection of Events in Power System

Smart grid is an advanced electrical supply system in which data is conveyed bi directionally utilizing computerized correspondence innovation. Observing, investigating, controlling and correspondence happens inside the inventory network accordingly improving proficiency, lessening vitality utilization and so on. A Phasor Measurement Unit (PMU) measures electrical signals in system. PMUs are utilized in the transmission side of the system. These are introduced at different places on the network and are time synchronized utilizing Global Positioning System (GPS). Thus real time synchronized continuous estimations are obtained from different estimation points on the network. PMU helps in automating the system. A system of PMUs called Wide Area Measurement System (WAMS) can be utilized for huge scale monitoring of the network. Power outages and load shedding in the system can avoided. PMUs can synchronously gauge voltage and current, phase angle, power, energy import & export, frequency, frequency deviations, etc. These parameters can be utilized to tell about the state of the system. The optimal placement of PMUs & Event detection techniques from the synchronized PMU data are determined using MATLAB software. Programming PMUs to detect the events in the system & placing it optimally can help diminish the huge expense and equipment intricacy.

Optimal placement of PMUs and communication links for distributed state estimation in distribution networks

With the expansion in scale and complexity of distribution networks, distributed state estimation (DSE), a real-time database for other on-line applications, is becoming popular for large-scale active distribution networks (ADN). Measurements from phasor measurement units (PMUs) with the same time stamp can assist DSE to obtain faster and more accurate estimation; however, the configuration of PMUs and communication links should be updated to support data collection and transmission. This paper proposes an optimal PMUs and communication links placement method for DSE in distribution networks. A network partitioning method is presented with the aim of balancing calculation times among subareas. Then, a binary integer linear programming model that simultaneously considers the optimal placement of PMUs, phasor data concentrators (PDCs) and communication links is proposed. The economy of the configuration scheme is guaranteed on the premise that the network is fully observable. Finally, case studies on the IEEE 33-node, PG&E 69-node and IEEE 123-node systems verify the feasibility of the proposed method.

Optimal placement of phasor measurement units considering islanding contingency, communication infrastructure, and quality of service

In this study, the PMUs are placed to operate in normal and islanded cases taking into account power system observability, reliability, Communication Infrastructure (CI), and latency time associated with this CI. Moreover, the economic study for additional new data transmission paths is considered as well as the preexisting Communication Devices (CDs) and the availability of predefined locations of some PMUs in some buses. The PMUs placement and their communication network topology and link channel capacity are co-optimized simultaneously. Two different approaches are applied to optimize the objective function; the first approach is combined from Binary Teaching Learning Based Optimization Algorithm (BTLBOA) and the Minimum Spanning Tree (MST) algorithm, while the second approach is based on BTLBOA. The proposed approaches are examined using IEEE 118-bus systems.

Optimal PMU Placement using Binary Particle Swarm and Artificial Bee Colony with Channel Limitations and Redundancy.

Phasor Measurement Unit (PMU) being expensive and to be placed optimally, a meta-heuristic approach of Binary particle swarm optimization (BPSO) and Binary artificial bee colony optimization (BABC) is made for the optimal allocation of PMU in a power system. The PMU locations resulted are served by basic system conditions like network configuration, critical generators, and loads. The pattern of locations on including Zero-Injection Buess (ZIB) is also discussed. The redundancy in case of PMU loss is coined so as to obtain a complete observability of the power system. the channel limitations of device is also taken into consideration for better results in real-time systems. Optimal PMU locations for IEEE 30-bus and 14-bus systems with channel limits are compared with all above considerations. The number of PMU locations is reduced as channel limits increases. The simulated PMU locations are decreased with improved observability by Binary Artificial Bee Colony Optimization as compared to Binary Particle Swarm Optimization.

Optimal Design of a Wide Area Measurement System Using Hybrid Wireless Sensors and Phasor Measurement Units

Real-time monitoring of the power system by phasor measurement units (PMUs) leads to the development of such devices in a wide area measurement system (WAMS). However, the power system observability cannot be obtained by employing only PMUs. The communication infrastructure (CI) is a significant part of the WAMS that has to be optimally designed and implemented to collect data from PMUs and deliver them to control centers. In this paper, a novel hybrid wireless sensor network is proposed for the connection of PMUs throughout the system to enable convenient and low-cost communication media. The problem of observability in the communication system is checked along with the optimal placement of PMUs in the power system to reach full observability. A hybrid wireless sensor network including plug-in powered sensor nodes (PPSNs) and energy harvesting sensor nodes (EHSNs) is utilized for increasing the reliability of the communication system. In the proposed co-optimal PMU-sensor placement problem, the main objective is to minimize the total cost of PMU placement and the related communication system, considering full observability of the power system and CI. To achieve better results, the zero-injection bus (ZIB) effect and system observability redundancy index (SORI) are considered as a constraint in the objective function. A binary-coded genetic algorithm is used for solving the proposed mixed-objective optimization problem subject to different technical operating constraints. The proposed method is examined on IEEE 13-bus and IEEE 37-bus test feeder systems. The results show the applicability and effectiveness of the proposed method compared with the conventional methods in this subject area.

Placement of Distribution-Level Phasor Measurements for Topological Observability and Monitoring of Active Distribution Networks

This article presents a new method for the placement of distribution-level phasor measurement units (D-PMUs) in the active distribution networks (ADNs). The new objective function and constraints are proposed to ensure the minimization of capital cost as well the maximization of system observability, in the presence of distributed generations (DGs), zero injection buses (ZIBs), and tie-switches. The integer linear programming (ILP) is used to solve the framed objective function and the constraints. Furthermore, the accuracy of ADN state estimation (ADN-SE), in various system conditions, such as network reconfiguration, change in load demand, and measurement error degradation, is analyzed to check the impact of the proposed placement. The uncertainties caused by D-PMUs, DGs, and pseudomeasurements are considered well in ADN-SE using Monte Carlo simulations. The IEEE 69, 123, Indian 85, and UKGDS 95 bus distribution systems are used in the case studies.

Enhancing Performance of Wide-Area Back-Up Protection Scheme Using PMU Assisted Dynamic State Estimator

Wide-area measurements consisting of phasor measurement information, are lately used for monitoring and protection purposes. However, due to certain constraints related to usage of phasor measurement units (PMU) at all the buses, optimal placement of PMUs are needed for wide area applications. Further, limitations of supervisory control and data acquisition measurements and erroneous PMU measurements due to noise and communication link failure at some instant leads to the requirement of dynamic state estimation (DSE) using PMU information. The proposed scheme deals with wide area back-up protection scheme utilizing cubature Kalman filtering-based DSE in conjunction with fewer PMU measurements for obtaining full observability. A voltage-based index is derived using the DSE information to identify the faulty line. The scheme is tested for several faulted as well as stressed conditions such as line outage, generator outage, load encroachment and voltage stressed conditions including measurement error and missing data at some of the PMU buses. Extensive test on New England 39-bus system indicate that the proposed wide-area back-up protection scheme can reliably take appropriate action for back-up zone.

Optimal Allocation of Phasor Measurement Units Considering Various Contingencies and Measurement Redundancy

This article presents an efficient and comprehensive method to find out the minimum number of and the corresponding locations of phasor measurement units (PMUs) guaranteeing full numerical observability of a power system as well as maximize the measurement redundancy in conjunction with preexisting conventional measurements. Furthermore, the effect of number of available channels of PMUs on their optimal placement can be taken into account. The proposed optimal PMU placement (OPP) formulation is extended to consider the case of two types of contingencies, single PMU loss and single branch outage. The objective of the OPP method is the numerical observability, unlike the majority of earlier works which are based on topological observability and do not always ensure numerical observability required for the successful execution of state estimation (SE). The problem is formulated as a binary semidefinite programming (BSDP) model with binary decision variables, minimizing a linear objective function subject to linear matrix inequality (LMI) observability constraints. The BSDP problem is solved using an outer approximation scheme based on binary integer linear programming. The effectiveness of the proposed method is verified on different IEEE test systems.

PMU Placement With Channel Limitation for Faulty Line Detection in Transmission Systems

This paper presents a new phasor measurement unit (PMU) placement methodology to provide the required data for wide-area backup protection scheme. The presented placement method is primarily a binary linear optimization problem whose constraints are defined to detect faults on transmission lines based on the difference between voltage values of a bus obtained from two different paths, while the full observability of the system is also guaranteed. To consider the limitation on the number of PMU channels, a new bi-level approach is also proposed in this paper, in which the upper level is aimed to find the best solution among different submatrices, while the lower level finds the best PMU placement solution for each submatrix. Therefore, the contribution of this paper is to propose a methodology to optimally locate minimum number of PMUs in a power system in a way that while full observability of the system and its wide-area backup protection are assured, the types of each PMU—in terms of its number of channels as well as the lines whose currents should be measured by the PMU to satisfy the constraints—are determined. The performance of the proposed methodology is evaluated on standard test power systems.

Co-optimal PMU and communication system placement using hybrid wireless sensors

Abstract In smart distribution networks, the problem of measuring and estimating the state of the system is vital. Communication infrastructure, as an inseparable part of the wide area measurement system (WAMS), has to be optimally designed and placed to collect information from phasor measurement units (PMUs) and deliver them to control centers. In this paper, a novel hybrid wireless sensor network (WSN) is proposed for connecting of PMUs throughout the system to enable a convenient and low cost communication media. Having found the optimal placement of PMUs in power system to reach a full observability, the problem of observability in communication system will be handled to provide proper transmission of measured data to the control centers. In the proposed co-optimal PMU-sensor placement problem, the main objective is to minimize the total cost of PMU placement in power system and related communication system considering full observability and reliability constraints. For increasing the reliability of communication system, a hybrid WSN including plug-in powered sensor nodes (PPSNs) and energy harvesting sensor nodes (EHSNs) is utilized. A binary-coded genetic algorithm (BCGA) is used for solving the proposed mixed-objective optimization problem subject to different technical operating constraints. The proposed method in examined on a sample 11-bus test system and IEEE 37-bus test feeder systems. The results show the applicability and effectiveness of the proposed algorithm compared to the conventional methods in this subject area.

Groebner bases algorithm for optimal PMU placement

In this paper a new method for solving optimal phasor measurement units (PMU) placement problem for full observability in power systems is proposed. A new algorithm is based on forming and solving Groebner bases set of equations for a defined optimization problem. The technique of Groebner bases is applicable wherever the problem may be presented by the set of polynomials and as such, it can be found in a variety of applied mathematics problems. Groebner bases of the set of polynomials represents the canonical form equivalent to the original set, similar to the way the row echelon form for linear systems represents the triangular form of the linear equations set. The canonical form of the Groebner bases polynomials, along with the utilization of recursive algorithms, allows the solution to be effortlessly obtained. Optimal phasor measurement units placement (OPP) problem can be presented in a linear or nonlinear polynomial form, both of which are used in this paper. The settings of OPP problem have been proposed in this paper with the inclusion of zero injection buses (ZIBs), in normal system states and considering contingency related to PMU outage. The problem formulation is defined according to the application of Groebner bases technique. The proposed model is capable of obtaining the full set of optimal solutions instead of only one or partial solutions. The efficiency of the proposed method is tested on IEEE 14-bus, IEEE 24-bus, IEEE 30-bus, IEEE 118-bus and Polish 2383-bus test system and the results are compared with those of some recently reported methods.

An Effective Approach for the Probabilistic and Deterministic Multistage PMU Placement Using Cuckoo Search: Iran’s National Power System

In recent years, phasor measurement units (PMUs) as vital elements have been widely increased in control, monitoring and protection of power systems. In practice, as the size of a power system is large, it is not possible to install all PMUs over a short period of time mainly due to the financial and technical barriers. One solution would be installing the PMUs over different stages. Accordingly, the paper presents an effective approach for multistage PMU placement (MSPP) in power systems, called dynamic MSPP. Furthermore, since the probabilistic concept of observability reflects a more realistic image of power system observability compared to deterministic ones, this paper, unlike most of the existing MSPP models, investigates the MSPP model in both probabilistic and deterministic frameworks. Compared to the existing approaches and results, the obtained ones in this paper show a considerable improvement in the observability level during PMU installation period. In the proposed approach, PMUs are installed at intermediate stages aimed at maximizing the cumulative network observability in a single optimization process, instead of several subsidiary optimizations in conventional approaches. Briefly, the proposed approach offers a complete search space for the problem, while the existing models lead to limited ones. Moreover, because of the nonlinearity posed by the probabilistic concept of observability as well as the proposed MSPP, cuckoo search optimization algorithm is used to handle the complexity and a new problem encoding/decoding technique for the proposed MSPP is utilized. Eventually, the suggested framework is implemented on different case studies as well as Iranian Transmission Network to reveal the performance of the presented model.

Voltage Stability Index Calculation by Hybrid State Estimation Based on Multi Objective Optimal Phasor Measurement Unit Placement

Operation of a power system close to the voltage stability limit due to increasing of load demand and limited power sources may result in disastrous economic loss with voltage collapse of the entire power system. A system operator has to understand how far the system is from the critical boundary of the voltage collapse. This paper investigated the influence of State Estimation (SE) in the calculation of the Critical Boundary Index (CBI) as a voltage stability index. For SE, Hybrid State Estimation (HSE), including the measurement set of both Remote Terminal Unit (RTU) in Supervisory Control and Data Acquisition (SCADA) and Phasor Measurement Unit (PMU), is employed. Concurrently, the CBI is estimated using voltage phasor estimated by HSE based on optimal PMU location, which is selected from a Pareto optimal front obtained by the Non-dominated Sorting Genetic Algorithm II (NSGA-II). As a result of CBI estimation, HSE using PMU is relatively accurate in voltage stability index estimation compared to SCADA SE, which uses the RTU alone. However, when a mixed measurement condition in some lines affects the CBI estimation, it is suggested that it may be necessary to discard PMU measurements in some cases.

Analysis of Hybrid State Estimators: Accuracy and Convergence of Estimator Formulations

This paper provides a comprehensive analysis of several hybrid state estimators (HSEs) to assess their performance and identify their unique characteristics in transmission network. The results reveal that the formulation of an HSE can have a significant impact on both the estimation accuracy and the convergence properties of the estimator, which are the two most important performance factors for an HSE. Furthermore, the analysis performed has identified the formulation that maximizes these factors. The assessment can be divided into three parts. The first part conducts comprehensive simulations for the IEEE 14 bus test system for every possible phasor measurement units (PMU) placement. The second part validates the conclusions made in the first part using simulations of the IEEE 118 bus test system with both random PMU placements and optimally and suboptimally selected placements. The third part further validates these conclusions and directly explains the reasons for the differences in estimation accuracy observed for the different formulations of HSEs through mathematical analysis.

Optimal PMU-Communication Link Placement for Smart Grid Wide-Area Measurement Systems

Due to the relatively high costs of phasor measurement units (PMUs), the optimal PMU placement problem of minimizing the number of PMUs for full system observability has long been a popular research topic. However, PMUs alone will not make a system observable. An appropriate communication network that transmits all PMU data to the phasor data concentrator plays a key role. This paper proposes the optimal PMU-communication link placement (OPLP) problem that investigates the placement of PMU and communication links (CLs) for full observability in a power system. In addition to the location of PMUs and CLs, to ensure the reliable and timely transmission of PMU data, the communication capacity needed on every CL is captured by the OPLP problem. We carry out numerical studies on the IEEE 30-bus, 57-bus, 118-bus, and 300-bus systems for the proposed models. The results reveal that, when compared to the traditional optimal PMU placement model, OPLP can reduce the total installation cost significantly.

PMU Optimal Placement for Fault Detection in Wide Area Monitoring Systems based on the Drone Squadron Optimization

Wide area monitoring systems require the integration of new technologies that provide real time synchronized phase angle measurements. The Phasor measurement units (PMUs) are the most advanced devices to achieve this task so far. The objective of this work is to find the minimum number and optimal placement of PMUs in some standardized IEEE systems. The relatively new drone squadron optimization (DSO) technique is used to solve this problem. Next, fault location is studied based on the measurements collected from these PMUs. The simulations are carried out using MATLAB SIMULINK. The results show that it is possible to achieve the observability of the overall system; however, more PMUs are needed to locate the faults.