Installation Of Phasor Measurement Units Research Articles

The Branch-and-Bound Algorithm in Optimizing Mathematical Programming Models to Achieve Power Grid Observability

Phasor Measurement Units (PMUs) are the backbone of smart grids that are able to measure power system observability in real-time. The deployment of synchronized sensors in power networks opens up the advantage of real-time monitoring of the network state. An optimal number of PMUs must be installed to ensure system observability. For that reason, an objective function is minimized, reflecting the cost of PMU installation around the power grid. As a result, a minimization model is declared where the objective function is defined over an adequate number of constraints on a binary decision variable domain. To achieve maximum network observability, there is a need to find the best number of PMUs and put them in appropriate locations around the power grid. Hence, maximization models are declared in a decision-making way to obtain optimality satisfying a guaranteed stopping and optimality criteria. The best performance metrics are achieved using binary integer, semi-definite, and binary polynomial models to encounter the optimal number of PMUs with suitable PMU positioning sites. All optimization models are implemented with powerful optimization solvers in MATLAB to obtain the global solution point.

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.

An Optimal Scheme for Installation of PMUs and IEDs to Reinforce Electricity Market Immunity Against Data Attacks in Smart Grid

An intruder can disrupt the electricity market operation by injecting malicious data into the sensor measurements to induce profit/loss to a utility/consumer. Robustness in the electricity market operation against false data injection attacks (FDIAs) can be achieved by optimal deployment of phasor measurement units (PMUs) and intelligent electronic devices (IEDs). The nonlinear relationship between sensor measurements, state variables, and nodal electricity price, along with the financial constraints associated with deploying high-cost measurement devices, increases the complexity of solving the FDIA resilient sensor placement task. The solution demands a tradeoff between the financial implications of installing PMUs/IEDs and the nodal price deviation during FDIA. To overcome the above challenges, the task of identifying strategic sensor locations has been formulated as a binary optimization problem. The solution of the problem derived using binary Harris hawks optimization identifies the most vulnerable bus/branch measurements with regard to nodal price deviation due to FDIA. To generalize the applicability of the proposed scheme, the formulation has been carried out while considering the realistic constraints related to PMU channel limitations and the location of the zero injection bus. The effectiveness of the proposed work has been validated for benchmark test systems against different degrees of FDIAs.

Optimal placement of PMU for enhancing power system monitoring

Phasor Measurement Units (PMUs) have emerged as crucial tools in the field of power system monitoring, control, and safety. Extensive research has been conducted on enhancing the capabilities of PMUs. Traditional SCADA techniques, which have been employed for many years, gather data on power system parameters at intervals of 4 to 10 seconds, offering a static perspective of the system's behavior. However, relying solely on static data may limit the effectiveness of the monitoring and control. On the other hand, PMUs provide real-time information about the dynamic state of the system, enabling more comprehensive insights. For the optimal and cost-effective installation of PMUs, it is vital to strategically position them in locations that effectively monitor the state of the system. The Instruction Level Parallelism (ILP) approach was employed to identify the ideal PMU placement for power system observability. The ILP approach determines the most suitable positions for PMUs by considering factors such as the redundancy of measurements and cost efficiency. To validate the effectiveness of the ILP approach, it was tested using the widely recognized IEEE 14 bus system, which serves as a standard benchmark for power-system analysis. Through the ILP approach, the optimal placement of the PMUs can be determined, thereby enhancing the observability of the power system. This in turn improves situational awareness, enables effective fault detection, and facilitates coordinated control strategies. By integrating PMUs and the ILP approach, the power system monitoring and control can be significantly enhanced. Ongoing research and development in PMU technology and placement methodologies continues to advance the field, enabling more efficient and effective management of modern power grids.

Optimalno pozicioniranje sinhrofazorskih jedinica primenom genetičkog algoritma

Energy transition implies a larger share of the intermittent renewable energy sources connected to the power grid. These utilities can change their production within a short period of time, thus, significantly affecting the voltage conditions and load flows in the grid. This adds to the complexity in achieving required reliability and stability of the system. Proper and timely insight into the grid parameters plays an important role in regulation of such power system. Implementation of Phasor Measurement Units (PMUs) provides information about electrical parameters of the grid with as much as microsecond precision. Therefore, possible occurring dynamical processes could also be observed and regulated in a proper manner. Considering PMU can give information regarding voltage phasor as well as currents of adjacent branches, the observability of the system can be achieved even if some nodes are not equipped with their own PMU. Furthermore, installation of PMU in every node is not economical solution considering the size of the power grid and the number of PMUs accordingly. One should assess the sufficient number of PMUs cautiously and locate them carefully in order to maintain observability, but also to reduce expenses as much as possible. In the grid topology with a vast number of nodes and branches, the usage of metaheuristic optimization algorithms with adequate criteria function and limiting conditions could reduce the computing time compared to the linear and non-linear programming algorithms. In addition, the quality of such solution is also preserved. In this paper, the usage of genetic algorithm is proposed in order to determine the number and position of PMUs for several different grid samples.

Optimal PMU Allocation Strategy for Completely Observable Networks With Enhanced Transient Stability Characteristics

The installation of phasor measurement units (PMUs) in contemporary electrical networks provides enhanced monitoring and control capabilities of the entire system. However, the placement of additional PMU devices is constrained by the relatively high cost and complicated communication infrastructure. Consequently, optimizing the allocation of PMU units is required to achieve complete visibility of the power system operation while minimizing the associated cost. This paper presents a coherent approach for solving the optimal PMU placement (OPP) in order to reduce the total number of PMUs that is required to completely observe the network. Furthermore, the proposed formulation of the OPP allocation problem considers several objectives such as cost minimization, redundancy and efficiency maximization in addition to various constraints like incorporation of zero-injection buses, single PMU failure, single line outage and consideration of flow measurements. Moreover, a two-stage approach is proposed to ensure the numerical observability of the obtained PMU placement. The proposed framework relies on solving a mixed integer linear programming problem for the OPP placement problem based on conventional measurements. The rank of the gain matrix is thereafter computed to check if the solution is numerically observable. In contrast to reported studies in the literature, transient stability enhancement is augmented in the formulation of the optimization problem such that the redundancy of predetermined buses is guaranteed without increasing the total number of installed PMU units. A novel spectral cluster-based online coherency grouping is employed to identify buses which possess the ideal characteristics in terms of transient stability support.

Application of solar cells and wireless system for detecting faults in phasor measurement units using non-linear optimization

This research study examines the integration of wireless system and solar cells for detection and location of faults in power grids by implementing minimum number of Phasor Measurement Units (PMUs) after considering zero injection buses. A fault in the grid networks indicates a failure in the entire network that interfaces the normal flow of current which can be measured using wireless systems. The fault location in power grid is problematic because of high existence in several lateral tap-offs. In addition, the identification of exact location with presence of faults in the power system and severity of the faults are challenging tasks due to bulk and complex nature of the electrical power system state estimation. The major requirement of PMU placement approach is to find the minimum number of PMUs and their location with maximum wireless coverage under fault conditions with a prerequisite for the projected algorithm. The integrated algorithm is tested and validated for different fault conditions where the results are compared with different conventional methods using different optimization models such as heuristics, decision rules and mathematical programming where the outcomes proves to be much effective in terms of number of PMU installation for proper placements and detection, location in number of fault systems thus achieving 82% reliability using Ant Lion Optimizer (ALO).

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 Placement of PMU to Enhance Supervised Learning-Based Pseudo-Measurement Modelling Accuracy in Distribution Network

This paper introduces a framework for optimal placement (OP) of phasor measurement units (PMUs) using metaheuristic algorithms in a distribution network. The voltage magnitude and phase angle obtained from PMUs were selected as the input variables for supervised learning-based pseudo-measurement modeling that outputs the voltage magnitude and phase angle of the unmeasured buses. For three, four, and five PMU installations, the metaheuristic algorithms explored 2000 combinations, corresponding to 40.32%, 5.56%, and 0.99% of all placement combinations in the 33-bus system and 3.99%, 0.25%, and 0.02% in the 69-bus system, respectively. Two metaheuristic algorithms, a genetic algorithm and particle swarm optimization, were applied; the results of the techniques were compared to random search and brute-force algorithms. Subsequently, the effects of pseudo-measurements based on optimal PMU placement were verified by state estimation. The state estimation results were compared among the pseudo-measurements generated by the optimal PMU placement, worst PMU placement, and load profile (LP). State estimation results based on OP were superior to those of LP-based pseudo-measurements. However, when pseudo-measurements based on the worst placement were used as state variables, the results were inferior to those obtained using the LP.

Realistic Method for Placement of Phasor Measurement Units through Optimization Problem Formulation with Conflicting Objectives

The Phasor Measurement Unit (PMU) is a modern metering device installed to monitor and control the power system network. However, the number of PMUs and their placements ought to be optimized to satisfy the techno-economic demand. In this paper, the PMU placement problem has been expressed as a multi-objective problem. Modified whale optimization algorithm (MWOA) is proposed to solve Optimal Placement of PMUs (OPP) problem formulation aiming at minimizing the required number of PMU installation subjected to complete network observability and maximizing the reliability for better operation of power systems. Here, the simultaneous optimization of the two conflicting objectives is performed using a fuzzy-based modified whale optimization algorithm (FMWOA). Besides, single objective optimization problems with and without considering the zero-injection bus constraint and multi-objective optimization problem with zero injection bus constraint have been investigated. The proposed method is validated on small and larger test systems, namely IEEE 14, 30, 57, 118 bus systems, and the polish 2383-bus system. Also, the proposed algorithm results are compared with those of previously published for better clarity.

Identification of Optimal Sensor Location Based on Trade-Off Approach to Improve Resiliency of Electricity Market in Smart Grid

The integrity of control operations in the smart grid (SG) heavily depend on its monitoring system, which relies on the sensors mounted across the wide-area network (WAN). Utilizing the monitoring capability of SG for a conducive electricity market operation demands high accuracy in real-time sensor measurement. While synchronized measurements from phasor measurement units (PMUs) have improved the reliability compared to the classical sensors (CSs), the high installation cost often hinders the installation of PMUs throughout the WAN. The selection of sensors for wide-area monitoring dependent operations like the electricity market involves maintaining a trade-off between the conflicting objectives of sensor installation cost and accuracy in measurement. Although the objective of the necessary requirement of network observability using sensor data can be fulfilled through various configuration, the impact of sensor information on the electricity market differs as per their location. In this regard, the present work proposes a binary optimization-based approach for identifying strategic sensor placement locations in SG to minimize the disruption in the electricity market. The strategic sensor location aims at improving the resiliency of electricity market operation by minimizing the impact of sensor accuracy on nodal electricity price. The resiliency is achieved while simultaneously meeting the objectives of reduced sensor installation cost and fulfilment of network observability criterion. The effectiveness of the trade-off solution has been validated for standard IEEE 14, 30, and 57 test systems.

Synchrophasor Data Under GPS Spoofing: Attack Detection and Mitigation Using Residuals

The installation of Phasor Measurement Units (PMUs) is a step towards achieving wide-area situational awareness for the power grid. PMUs utilize GPS signals for time synchronization and are vulnerable to GPS Spoofing Attacks (GSAs) as civilian GPS signals are unencrypted and have low signal power. We propose a novel Residual-based Spoofing Detection and Measurement Correction (RSDMC) algorithm for the power grid that detects GSAs and corrects spoofed PMU measurements. During one or multiple GSAs, RSDMC iteratively minimizes the residual norm to correct spoofed PMU measurements. We derive a necessary condition for our proposed algorithm to show that the residual norm increases during GSAs. We perform Monte Carlo simulations to verify our derived necessary condition. We further simulate the IEEE 14, IEEE 118, and Illinois 200 bus test cases to validate RSDMC against multiple GSAs.

Real-time dynamic security analysis of power systems using strategic PMU measurements and decision tree classification

Fast and accurate online dynamic security analysis (DSA) is the key enabler for secure operation of modern power systems. Real-time assessment of the current power system operating state and increased awareness about plausible future insecurity can enable necessary operational and control measures to ensure secure operation. This paper proposes an ensemble decision tree (DT)-based online DSA method for large-scale interconnected power system networks using wide area measurement (WAMS) with phasor measurement units (PMU). A novel attribute selection method has been demonstrated for optimizing PMU installation at strategic buses in large-scale power networks. Multi-stage screening of the initial measurements has been done to minimize the data acquisition cost and computation overhead, which are the key challenges in real-time DSA. The ensemble DT classifier was trained offline using data from the operational model of the power system under different system loading and contingency conditions. The trained classifier provides online security assessment and classifies the power system’s current operating state as secure or insecure based on real-time measurements of the key attributes by selective PMUs. The proposed scheme was tested on IEEE 118-bus system, and the results demonstrate that it has the potential to be used as a reliable online DSA method.

A comprehensive review for optimal placement of phasor measurement unit for network observability

Real time synchronized phasor measurement in power network is obtained by the improvement in monitoring, control and, protection of the power system. In recent time, the installation ratio of Phasor Measurement Units (PMUs) is constantly increasing for the real time measurement throughout worldwide. The increment in the number of PMU installation is to only focus on the improvement of system state estimation (SE) performance. However, the expensive nature of the metering device requires huge amount of installation cost with the other communication facilities, therefore an optimal placement of PMU is necessary. Different techniques have been designed and used to overcome this matter. The paper presents numerous optimization algorithms such as, Mathematical programming, Heuristic, and Meta-Heuristic techniques which are specially used for the optimization of PMU placement with complete network observability. Furthermore, each PMU technique is explained, and performances are compared for the most appropriate and optimal placement of PMU methods, which can be recommended for a future work to get complete network observability.

Optimization of Phasor Measurement Units Placement Under Contingency Using Reliability of Network Components

This study reports an optimization technique to reduce the requirement of phasor measurement units (PMUs) for complete observability under contingency with the use of component reliability. The present methodology secures the data measurement of unreliable and weak-load buses of power network considering hybrid observability for multiphase PMUs installation. The (N - 1), (N - 2) contingency present in the power network requires redundancy for data measurement. The network components with high reliability decrease the contingency of power networks. This reduces the requirement of data measurement redundancy for the network component having high reliability. This article utilizes this relationship between network component reliability and power network contingency to propose the concept of hybrid observability for PMU placement. It combines the concept of complete and redundant observabilities. Power network reliability is determined by incorporating the component reliability of the PMU data measurement system. Weak-load buses responsible for voltage collapse are determined by varying reactive power loading. Furthermore, the proposed weak-load bus closeness criteria (WLCC) and reliability observability criterion (ROC) are utilized for performing ranking of PMU locations using an analytical hierarchical process. These criteria identify the most significant location for initial phases of PMU installation. This strengthens the data measurement of weak-load buses through the most reliable network preventing voltage collapse due to data unavailability even during initial phases of PMU placement. The proposed methodology is illustrated on the IEEE 30-bus and NRPG 246-bus system.

A multi-constrained binary ILP method for optimal allocation of PMUs in network

This paper proposes multi-constrained binary integer linear programming (MBILP) method for optimal installation of phasor measurement units in IEEE networks considering Fast Load Voltage Stability Index (FLVSI), branch weight and redundancy constraints to minimize the cost of installation and to accomplish complete network observability. The weak buses of IEEE network are sorted based on their severity through the proposed strategy. A new FLVSI is programmed along with branch weight and redundancy constraints in MBILP to place PMUs in network. As installation cost of PMU for different buses varies with the number of branches or number of channels connected, PMUs should be allotted at bus with minimum cost. Redundancy of bus is computed to measure redundancy of bus network. Priority of PMU placement is considered at weak bus with proposed FLVSI in such a way that the cost is minimized and redundancy is adequate considering both branch weight and redundancy constraints. Ranking is proposed for PMU placement to find weak load bus in network along with the consideration of branch weight and redundancy. Zero injection (ZI) constraint modeling is recommended to minimize allocations further in system without losing observability. Contingency constraints for single-line or PMU loss are considered for allocation of PMUs. The proposed method is compared with ZI and without ZI modeling under general and line-outage or PMU loss cases to show efficacy of method. To estimate observability performance of complete network, a Complete Network Bus Observability Index is suggested. IEEE 14-, 24-, 30- and 57-bus networks are programmed with MATLAB software and compared with standard approaches to validate their efficacy.

Fault Location Method Using Phasor Measurement Units and Short Circuit Analysis for Power Distribution Networks

This paper proposes a fault location method for power distribution networks using phasor measurement units (PMU) and short circuit analysis. In order to improve the problems of the existing studies, we focused on several approaches as follows. First, in order to minimize the number of PMU installations, a fault location estimation of lateral feeders through short circuit analysis was presented. Second, unbalanced faults and impacts of photovoltaic (PV) were considered. The proposed method consists of two stages. In Stage 1, the fault location was estimated for the main feeder using PMU installed at the start and end points of the main feeder. Symmetrical components of voltage and current variation were calculated by considering the impact of PVs interconnected to the lateral feeders. If the result of Stage 1 indicated a connection section of lateral feeder on the main feeder, Stage 2 would be performed. In Stage 2, the fault location was estimated for the lateral feeder by comparing the results of the short circuit analysis and measurements of PMUs. The short circuit analysis was based on an unbalanced power flow that considered dynamic characteristics of the PV inverter. The proposed method was verified through various fault situations in a test system. For the applicability of the proposed algorithm to the actual system, a noise test was also performed.

Multi-objective MILP model for PMU allocation considering enhanced gross error detection: A weighted goal programming framework

This paper proposes a multi-objective mixed-integer linear programming (MILP) model for the optimal phasor measurement unit (PMU) placement (OPP) problem. A majority of the solutions presented for the OPP problem focus on minimizing cost while guaranteeing system observability. While this is a good approach to the OPP problem, the effect of PMU allocation on various energy management system applications should also be considered. This paper addresses the OPP problem considering PMU installation costs, system observability, and gross error detection. In order to allocate PMUs considering gross error detection, the Vulnerability Index (VI) is used to quantify the vulnerability of each element in the system. A weighted goal programming (WGP) framework, which allows for the optimization of contradictory goals, which is a characteristic of the goals considered in this paper, is presented. The goals and weights of the framework are user inputs to the program besides a hard budget restriction. The results of this paper show how the WGP framework allows the priorities of the decision maker to influence the final PMU allocation presented by the MILP, making this model a valuable framework for utilities planning to install PMUs on their network.

Operational‐based techno‐economic PMU installation approach using grey wolf optimisation algorithm (GWOA)

Phasor measurement units (PMUs) are currently the most useful devices to obtain fast, precise, and synchronised measurement data. Owing to the high cost of installation, the minimum number of PMUs required for the full observability of a network must be determined. However, power companies do not consider such optimal PMU installation (OPI), because their main concerns are preventing cascaded tripping and secure grid separation, for which critical buses (CBs) should be prioritised for direct observability. In practice, utility grids (UGs) may lose their full observability status during islanding, which the OPI problem should account for. On the other hand, actual bus-to-bus variations in the PMU installation cost are not properly addressed in the PMU installation problem. Considering these practical aspects, an operational-based multiphase PMU installation approach is proposed here using the grey wolf optimisation algorithm for CB prioritisation. A PMU cost minimisation-based OPI problem that considers the full observability of each UG during islanding is formulated. To determine quality outputs, logical and unique mathematical equations are developed. A novel multiple bus selection approach is proposed for a phase-wise bus assortment. The results of the proposed algorithm are compared with those of other existing methods.

PMU-based Online Monitoring of Short-term Voltage Stability using Lyapunov Exponents

Online monitoring of voltage stability is an important task to identify operating conditions of the system that lead to instability and/or voltage collapse and to decide on automatic corrective control actions. In recent years, the installation of phasor measurement units (PMU) in power systems has increased significantly, which is why a large amount of information in real time is available for online analysis of the dynamic response to contingencies. This paper proposes a new methodology based on PMU for online monitoring of short-term voltage stability under large disturbances from estimating the maximal Lyapunov exponent (MEL) in the post-contingency voltage time series. The methodology includes an offline procedure with a stochastic approach based on the Monte Carlo simulation and the particle swarm optimization (PSO) method to adjust the embedding parameters of the MEL estimation algorithm. Case studies are analyzed in the New England 39-bus test system to present the performance of the MEL estimation with different embedding parameters and to demonstrate the effectiveness of the proposed methodology for monitoring short-term voltage stability under different operating conditions.