Optimal PMU Placement Problem Research Articles

Optimal PMU Placement to Enhance Observability in Transmission Networks Using ILP and Degree of Centrality

The optimal PMU placement problem is placing the minimum number of PMUs in the network to ensure complete network observability. It is an NP-complete optimization problem. PMU placement based on cost and critical nodes is solved separately in the literature. This paper proposes a novel approach, a degree of centrality in the objective function, to combine the effect of both strategies to place PMUs in the power network optimally. The contingency analysis and the effect of zero-injection buses are solved to ensure the reliability of network monitoring and attain a minimum number of PMUs. Integer linear programming is used on the IEEE 7-bus, IEEE 14-bus, IEEE 30-bus, New England 39-bus, IEEE 57-bus, and IEEE 118-bus systems to solve this problem. The results are evaluated based on two performance measures: the bus observability index (BOI) and the sum of redundancy index (SORI). On comparison, it is found that the proposed methodology has significantly improved results, i.e., a reduced number of PMUs and increased network overall observability (SORI). This methodology is more practical for implementation as it focuses on critical nodes. Along with improvement in the results, the limitations of existing indices are also discussed for future work.

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.

A novel comprehensive optimal PMU placement considering practical issues in design and implementation of a wide-area measurement system

• Several WAMS-based applications are considered in the OPP problem. • Concept of the line-wise observability is presented. • Observability of multi-TSO power systems in the OPP problem is investigated • The proposed OPP model is originally a MILP one and its global solution can be easily found. Since phasor measurement units (PMUs) are increasingly installed in power systems, many research works have investigated the optimal PMU placement (OPP) problem with the sake of maximizing observability over the power grid, while minimizing the cost of purchasing PMUs. However, there are still some practical challenges that have not been considered in the previous research studies, and are needed to be addressed for a real wide-area measurement system (WAMS) implementation. In this paper, a comprehensive OPP model is proposed which employs a set of basic and novel constraints for a WAMS design. In this regard, the line-wise observability concept is proposed for the first time to consider the requirements of observability for a range of WAMS-based applications such as restoration management, model validation of power system components, and dynamic line rating (DLR) monitoring. In addition, observability constraints for multi-transmission system operator (multi-TSO) power systems that are operated by different legal entities are provided, which can considerably affect the OPP result. The proposed model is formulated based on a mixed-integer linear programming (MILP) formulation which enables the optimization problem to be solved easily and effectively by existing commercial optimization tools, without any need for linearization. The performance of the proposed OPP model is first verified through simulation results on an 86-bus real power system. Then, simulations are applied to IEEE 118-bus and 300-bus test systems, to certify the performance of the proposed model in comparison with other OPPs in the literature.

Robust PMU Placement in Branch Switching Power Networks for Minimum Variance State Estimation

Phasor Measurement Units (PMUs) are measurement devices that measure voltage phasor data of a bus and current phasors of adjacent branches in a power network. With information on the power network impedance, a finite number of PMUs are used to estimate the voltage on all buses, also known as the state of the power network. Traditionally, the problem of Optimal PMU Placement (OPP) focuses on having complete observability of the network state by strategically placing a minimum number of PMUs. A change in network topology caused, for example, by network switches, changes the solution to the OPP problem. Since it is not feasible to change the locations of PMUs after every change in topology, the contribution of this paper is a PMU placement optimization algorithm which minimizes the variance on the estimated voltages and is also robust to the changes to the network topology. The optimization guarantees robustness to the change in network topology. Since it considers each change in the switch position as a different network topology, the optimization criterion is a multi-objective optimization function for different network topologies caused by changing the switch positions of the same network. The proposed robust optimal placement algorithm can be used for single current-channel PMUs and multi-current channel PMUs. The algorithm is tested on IEEE 14 bus network. The results show that the robust optimal placement can significantly reduce the effects of PMU measurement noise on the estimated states on average for different switch positions.

Artificial Intelligence based Optimal Placement of Phasor Measurement Unit for Smart Grid

A Phasor Measurement Unit (PMU) device ensures the stability, reliability, and proper visibility of critical areas of the power grid by providing a synchro phasor measurement of both voltage and current in real-time. Since it is not practical to place them at each branch of the system, the main concern lies in achieving entire network observability either by direct or indirect measurement through an optimal set of PMUs placed at the optimal location. This gives rise to the Optimal PMU Placement Problem (OPP). In this paper, OPP is solved by an optimization technique i.e., a Genetic Algorithm. The constraints that can greatly affect obtaining optimal solutions are reviewed and the effect of including Zero Injection Bus (ZIB) on the proposed method in solving OPP is studied. The algorithm is applied to IEEE-14 and IEEE-30 bus test systems for validation purposes. Since optimal sets of solutions are obtained from the proposed method, the solutions are ranked by the system observability redundancy index to find the best one. Further, a comparative analysis of the result is done with the depth first search algorithm and other widely used algorithms.

PMU placement with multi-objective optimization considering resilient communication infrastructure

A Phasor Measurement Unit (PMU) is the most advanced equipment used to bring a good level of situational awareness to Wide-Area Measurement System (WAMS) in power systems. However, the underlying cost for such PMU-based supervisory systems is the limiting factor that affects the extent of installed syncrophasor devices in a power network. This work aims to formulate the optimal PMU placement problem in a power transmission system which seeks to jointly minimize the risk of inobservability for State Estimation and also the overall total cost. Thus, it is proposed a multi-objective algorithm that uses numerical observability indicators to characterize measurement plan robustness and also graph theory tools to address the total cost optimization problem, which considers practical and more realistic aspects of the installation of PMUs, as well as addressing costs for the network communication infrastructure. Moreover, non-dominated Pareto solutions are built, which in a real scenario, would serve better for judicious decisions by the planners of a measurement system.

Optimal PMU Placement in the Presence of Conventional Measurements

This article presents a novel method for optimal phasor measurement unit placement (OPP) for full power system observability in the presence of conventional measurements. The method considers eligible PMU placements that may be omitted by existing OPP methods and hence may provide a better solution and can guarantee that the PMU placement can restore network observability. This is achieved by creating a new observability criterion and a network transformation scheme. The new observability criterion uses injection and zero injection measurements to improve the solution and the network transformation scheme reduces the size of the OPP problem and is a prerequisite for applying the proposed observability criterion. The OPP problem is solved using binary integer linear programming (BILP) or binary integer linear programming (BILP). Therefore, the proposed OPP method can be easily combined with other OPP methods, considering other constraints/scenarios using BILP, such as OPP considering PMU current channel limits. The new method is tested using simulations of the IEEE 14-, 118-, and 2736-bus test systems. These results show that the proposed new method is feasible in terms of execution time, is free of solutions that fail to make the system fully observable, and is capable of identifying optimal placement solutions that may be overlooked by existing OPP methods.

Power System State Estimation using Non-Iterative Weighted Least Square method based on Wide Area Measurements with maximum redundancy

The power system state estimation (PSSE) accuracy is crucial for monitoring and surveillance in an energy management system (EMS). Wide-area measurement systems (WAMS) are a pivotal technology to enhance the accuracy of PSSE. Further, with the advent of phasor measurement units (PMUs), state estimation got revolutionized by its performance. To attain better estimation accuracy, the main considerations for a power system are; observability and redundancy. In order to achieve full observability with maximum redundancy, the problem of optimal PMU placement (OPP) in power systems is investigated. This paper proposes a Modified- Integer Linear Programming (M-ILP) technique to achieve full observability with minimal PMU placement and maximum redundancy. Furthermore, A Non-iterative Weighted Least Square (NI-WLS) approach has been developed to improve the accuracy of power system state estimation by leveraging hybrid measurements consisting of traditional SCADA data and phasor measurements. The efficacy and precision of the proposed algorithms have been demonstrated through extensive simulations on a wide range of test systems, including standard IEEE- 14, 30, 57, 118 systems and real-time Indian Northern Region Power Grid-246 (NRPG-246) bus system. Moreover, the proposed methods show significant improvement in the accuracy and stability of the state estimate solution.

Evaluating Performance of a Linear Hybrid State Estimator Utilizing Measurements From RTUs and Optimally Placed PMUs

Synchro-phasor technology, using Phasor Measurement Unit (PMU), has improved the way power system data is collected for monitoring through state estimation. The placement of PMUs in a power system presents technical benefits, but it comes with high infrastructural costs. It is, therefore, necessary to install the minimum number of PMUs at optimal locations subject to power system observability, creating the Optimal PMU Placement Problem (OPPP). Some factors may be considered constraints in the OPPP, such as PMU outage. The main challenge with incorporating such constraints in the PMU placement problem is that the minimum number of PMUs required for system observation increases, contributing to the high infrastructural costs. This paper, therefore, proposes using a Linear Hybrid State Estimator (LHSE) that considers existing Remote Terminal Unit (RTU) measurements randomly distributed within the system and optimally placed Phasor Measurement Unit (PMU) measurements. The proposed LHSE addresses challenges associated with nonlinearity in state estimation. The LHSE is also based on the Weighted Least Absolute Value (WLAV) criterion, considered robust and able to detect and discard bad data during the estimation process. The proposed LHSE can address state estimation reliability and resiliency, specifically the PMU outage contingency, by employing existing RTU measurements and optimally placed PMU measurements based on the Artificial Bee Colony (ABC) optimization technique. The proposed approach also leverages RTU and PMU measurements to address PMU loss contingency instead of utilizing PMU measurements only as in existing studies. Three test cases (IEEE 14 Bus, IEEE 30 Bus, and IEEE 57 Bus) are considered, with the simulations performed in MATLAB using MATPOWER data. The performance of LHSE is evaluated considering PMU/RTU measurements and PMU measurements only scenarios. Both RTU/PMU measurements present a lower Normalized Cumulative Error (NCE) performance index than PMU measurements only. In case of a single PMU outage, the proposed LHSE can estimate all states based on RTU/PMU measurements instead of only PMU measurements that fail.

Optimization of Phasor Measurement Unit (PMU) Placement: A Review

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.

A multi-objective grey wolf optimizer (GWO)-based multi-layer perceptrons (MLPs) trainer for optimal PMUs placement

PurposeThis paper aims to find the minimum possible number of phasor measurement units (PMUs) to achieve maximum and complete observability of the power system and improve the redundancy of measurements, in normal cases (with and without zero injection bus [ZIB]), and then in conditions of a single PMU failure and outage of a single line.Design/methodology/approachAn efficient approach operates adequately and provides the optimal solutions for the PMUs placement problem. The finest function of optimal PMUs placement (OPP) should be mathematically devised as a problem, and via that, the aim of the OPP problem is to identify the buses of the power system to place the PMU devices to ensure full observability of the system. In this paper, the grey wolf optimizer (GWO) is used for training multi-layer perceptrons (MLPs), which is known as Grey Wolf Optimizer (GWO) based Neural Network (“GW-NN”) to place the PMUs in power grids optimally.FindingsFollowing extensive simulation tests with MATLAB/Simulink, the results obtained for the placement of PMUs provide system measurements with less or at most the same number of PMUs, but with a greater degree of observability than other approaches.Practical implicationsThe efficiency of the suggested method is tested on the IEEE 14-bus, 24-bus, New England 39-bus and Algerian 114-bus systems.Originality/valueThis paper proposes a new method for placing PMUs in the power grids as a multi-objective to reduce the cost and improve the observability of these grids in normal and faulty cases.

Novel Optimal PMU Placement Approach Based on the Network Parameters for Enhanced System Observability and Wide Area Damping Control Capability

The placement of phasor measurement units (PMUs) in modern power systems provides improved monitoring and control characteristics of the entire electrical network. Nevertheless, the installation of additional PMU devices is associated with relatively high cost and complicated communication infrastructure. As a result, the allocation of the PMU devices needs to be optimized to achieve complete observability of the system while minimizing the related cost. This paper proposes a new method for solving the optimal PMU placement (OPP) problem using integer linear programming (ILP) such that the global optimal solution is guaranteed. As opposed to the reported studies in the literature, the proposed method considers the network parameters such as the series impedances and the shunt admittances of the transmission lines and transformers impedances in the formulation of the OPP problem. These parameters are found to have a crucial impact on the observability of the entire network. A distinguishing feature of the proposed approach is that it decomposes the network into smaller subnetworks, with reduced dependence between them, thus making it scalable when applied to typical networks. In addition, the proposed method seeks to achieve the maximum measurement redundancy while considering the impact of failures among individual PMU devices (N-1 contingency), the PMU channel limitation and the pre-existing conventional measurements. Furthermore, the presented approach incorporates additional constraints which are associated with the control feedback signals of the supplementary damping controllers and thus enhance the small signal stability of the power grid. The effectiveness of the proposed method is tested using different standard IEEE systems as well as a large practical network.

An Approach to Unravel the Optimal PMU Placement Problem for Full Observability of Power Network in View of Contingencies

An Approach to Unravel the Optimal PMU Placement Problem for Full Observability of Power Network in View of Contingencies

Minimizing the Total Cost of WAMS Using Artificial Electric Field Algorithm

Wide area monitoring system (WAMS) is one of the most important technologies in modern power systems, it gathers the synchronized time stamped measurements from wide area across power system through a high reporting measuring device such as synchronized phasor measurement units (PMUs).Due to the high cost of PMU itself and its installation cost, it is often difficult to install PMU at each bus in the power system. However, there are several approaches to solve the optimal PMU placement (OPP) with various optimization algorithms. In this paper, a realistic cost model has been proposed to provide optimal PMUs placement (OPP). The proposed model has been solved using artificial electric field algorithm (AEFA), which is a novel optimization algorithm, it was proposed by 2019. In this paper, a binary form of AEFA has been proposed to solve the proposed cost model. AEFA has been implemented in MATALB programming environment, and the results demonstrate that the proposed cost model provides a realistic view of WAMS cost. Additionally, the results have been compared with other optimization algorithm, and it demonstrates that the AEFA is efficient to solve the OPP problem.

Modified branch‐and‐bound algorithm for unravelling optimal PMU placement problem for power grid observability: A comparative analysis

Modified branch‐and‐bound algorithm for unravelling optimal PMU placement problem for power grid observability: A comparative analysis

Optimal PMU Placement Using Genetic Algorithm for 330kV 52-Bus Nigerian Network

The phasor Measurement Unit is a modern tracking tool mounted on a network to track and manage power systems. PMU is accurate and time-synchronized device that gives voltage phasor measurements in nodes and current phasor measurements connected to those nodes where the PMU is installed. This study introduces the Genetic Algorithm for optimization of allocation of PMUs to enable maximum observation of the power network. The optimal PMU placement (OPP) problem is developed to minimize the quantity of PMU to be placed. The set and optimized model can efficiently position PMU in any network, considering the regular operation and zero injection (ZIN). Thus, the allocation algorithm implemented on IEEE 14-bus systems, the result was compared to that of existing works which achieved the same system of redundancy index. As a further study, the proposed approach is applied to the Nigerian 330kV new 52-bus systems, under operational arrangements for maximum observability of the network system. The technique formulated to handle normal operation and zero injection node succeeded in producing comparable results with other available techniques.

Optimal Allocation of Synchrophasor Units in the Distribution Network Considering Maximum Redundancy

Phasor Measurement Unit (PMU) is a smart measuring device commonly used in wide-area monitoring systems. It provides the synchronized phasor values and the magnitudes of voltages and currents in real-time for the proper state calculation of the electrical network in a common time reference frame. But in order to avoid unnecessary placements, minimize installation cost, and due to the lack of communication facilities at the substations, the placing of PMUs at every location is not possible. Therefore several optimization techniques have been developed to solve the Optimal PMU Placement (OPP) problem. The OPP problem aims to reduce the number of PMUs by achieving a completely observable network. Many solutions to the OPP problem have been proposed for the transmission networks with the use of conventional and heuristic-based approaches, but very few for distribution networks. In this paper, the Binary Grey Wolf Optimization (BGWO) algorithm is proposed to solve the OPP problem considering the measurement redundancy (MR) to achieve complete observability of the distribution network. Finally, case studies have been done by implementing the proposed algorithm on different IEEE test feeders such as the IEEE -13, -33, -37, and -123 node feeder systems. The obtained results are compared with previous studies to verify the feasibility and efficiency of the proposed technique.

Optimal PMU placement approach for power systems considering non-Gaussian measurement noise statistics

This paper investigates how to add a limited number of Phasor Measurement Units (PMUs) to the existing monitoring system so as to improve the estimation accuracy further. The existing methods are usually based on Gaussian noise assumption and the weighted least squares (WLS) estimator is taken into account. However, the Gaussian noise assumption is not always true in reality and the WLS is non-robust in this case. This paper proposes a new optimal PMU placement approach where the distribution of measurement noise can be non-Gaussian or Gaussian and many robust estimators such as the maximum likelihood estimator, Multiple-Segment, Quadratic-Linear, Square-Root and Schweppe-Huber Generalized-M estimator are considered. Based on the new Gain matrix obtained from the influence function approximation, the D-optimal and E-optimal experiment criterions are exploited in the optimal PMU placement problem. A convex relaxation in conjunction with an optimization improvement method based on the Fedorov exchange algorithm is utilized to solve the optimizing problem. Simulations on the IEEE 57-bus system and the Polish 2383-bus system are carried out to evaluate the effective performance of the proposed approach.

Optimal PMU arrangement considering limited channel capacity and transformer tap settings

The transition from the conventional power systems to smart grids has led to the modernisation of the measuring infrastructure used for their monitoring and control. Among the devices used to accomplish these tasks, phasor measurement units (PMUs) play a key role since they can provide extremely accurate synchronised voltage and current phasor measurements. The optimal PMU placement (OPP) problem, which focuses on minimising the number of PMUs for full system observability, has long been a popular research topic. The vast majority of the available OPP techniques have treated each transformer tap setting (voltage turns ratio and phase-shifting angle) as a fixed network parameter. Such an assumption can lead to misdirecting residuals in adjacent valid measurements when the modelled tap setting is incorrect. The aim of this study is to propose a substation-oriented OPP method based on a binary semidefinite programming algorithm, considering the observability of the transformer tap settings and the limited PMU channel capacity. The method is illustrated using an 8-bus test system. Numerical results using different size IEEE systems are presented and discussed. The proposed approach is further applied to the Polish 3120-bus system to show its efficacy in solving the OPP problem for large-scale power systems.

Optimal placement of PMU for complete observability of the interconnected power network considering zero-injection bus: A numerical approach

<div data-canvas-width="397.3623059866966">This paper presents an approach to place the phasor measurement unit (PMU)</div><div data-canvas-width="397.3623059866962">optimally, which minimizes the setup cost of PMU. This methodology attains complete state estimation of the interconnected power networks. An integer linear programming (ILP) method is explored for the optimal PMU placement problem. It is used to determine the optimal location and minimum number of PMUs necessary to make the interconnected power network completely observable. ILP may provide many solutions if acquainting buses to zero injection buses are unhandled. In the case of more than one solution, a bus observability redundancy index and total system observability redundancy index is proposed to find the most promising solutions set for redundancy measurement. The proposed algorithm is applied to benchmark the optimal PMU placement solutions for the IEEE 14-bus, IEEE 30-bus, New England 39-bus, IEEE 118-bus, and NRPG 246-bus test systems. The obtained results of the proposed approach are compared with the existing standard algorithm, and it is observed that the proposed approach achieves complete observability of the interconnected power network under base-load conditions.</div>