Sensitivity analysis‐based optimal PMU placement for fault observability

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

Optimal PMU placement for power system observability using BICA, considering measurement redundancy

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.

This paper presents a study on optimal placement of phasor measurement units (PMU) with Global Positioning System (GPS) receivers for more accurate monitoring of a power system. The optimal PMU placement (OPP) problem is, in general, expressed as a combinatorial optimization problem subjected to the observability constraints of the studied power system, which consumes much time to solve. Three approaches, in this paper, are proposed aiming at reducing computational burden in OPP problems. First, a modified simulated annealing (MSA) method, is proposed. The conventional simulated annealing method is slightly modified in setting the initial temperature and in cooling procedure to consider the current state of solution sets. Second, a direct combination (DC) method is suggested using a simple but very effective heuristic rule. When selecting test and neighboring solution sets, this heuristic rule is used to select most effective sets in the observability sense. And the last one is tabu search (TS) method, in which the heuristic rule used in DC method is also used to reduce the searching spaces effectively. Suggested optimization methods are applied, in this paper, to solve OPP problems in IEEE 14, 30 and 57 bus systems. The simulation results show that the proposed methods can find the optimal solutions in an efficient manner.

This article presents a novel algorithm to find optimal sets of Phasor Measurement Units (PMUs) in power systems using measurement sensitivity analysis aiming for fault detection without multi-estimation. The algorithm generalizes the impedance method in fault detection through optimizing PMU utilization in order to detect a fault with desired precision in interconnected power systems. By deriving bus voltage and currents sensitivity indices to the fault location and impedance, possible deviations of the estimated fault location and/or impedance due to measurement noise, accuracy, precision limits, or simply the inability of a measurement point to sense a fault is evaluated. Therefore, the algorithm can solve Optimal PMU Placement (OPP) for desired fault detection precision based on these indices for various points of measurement observing faults in the system. Finally, avoiding multi-estimation guarantees the unique mapping between measurements of the selected PMU sets and faults throughout the system. The proposed algorithm is performed on the IEEE 7-bus and 14-bus benchmark systems and the fault location capability is evaluated through neural networks.

This paper presents a detailed bibliographic analysis of papers concerning the optimal PMU placement (OPP) problem that have more than ten citations and sorted in descending order by the number of citations. The results from this analysis show that IEEE journal and IEEE conference papers are the most influential. The most productive and high-impact authors, institutions, and countries/regions are also identified. According to this analysis, U.S.A. researchers and institutions dominate the research on OPP problem, whereas the most productive and influential authors are A. Abur and B. Gou. Moreover, Texas A&M University, Virginia Polytechnic Institute & State University, and University of Cyprus are the three most productive and influential institutions in OPP research.

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

In this paper, a novel hybrid optimization method to solve the phasor measurement unit (PMU) placement problem is presented. The optimal PMU placement (OPP) problem is formulated to guarantee both full observability of the network and minimal number of PMUs. In the hybrid optimization method, the mechanism of simulated annealing (SA) is involved into original particle swarm optimization (PSO) to prevent the method from premature convergence; crossover and mutation operators are applied to increase the diversity of swarm. The proposed method keeps the advantage of PSO to find the optimum result quickly, and is still simple to implement, and can further improve the ability of jumping out of local optimum results. Simulation results on several IEEE systems show the effectiveness of the method. (5 pages)

Application of heuristic algorithms to optimal PMU placement in electric power systems: An updated review

Post-mortem studies carried out after recent power system blackouts have shown that time-stamped measurements from Phasor Measurement Units (PMUs) would have helped to avert these blackouts if they were available. Consequently, there is the need to optimally locate these PMUs to provide information about the system’s state. This paper proposes a novel method incorporating modal participation factors computed from the eigenvalues and eigenvectors of the reduced Jacobian matrix obtained from the system’s power flow with Binary Integer Programming (BIP), in solving the Optimal PMU Placement (OPP) problem while considering the system’s voltage stability. The proposed method identifies the critical buses prone to voltage instability, determines the minimum number of PMUs required for complete topological observability, and the best locations to site the PMUs. The proposed method was tested on benchmark IEEE 14-bus, 30-bus, and 57-bus test networks. Analyses of the results show that the proposed method provides a better procedure for the strategic placement of PMUs in practical networks for voltage stability monitoring especially for the cases of phased (multi-stage) PMU placement limited by the availability of funds and communication channels. Thereby making it necessary to give priority to critical/voltage weak buses during the phased installation process.

The Phasor Measurement Unit (PMU) is an important instrument for power system monitoring and control. It provides continuous, synchronized voltage measurements at the buses, as well as current stage esteem for such buses in which this PMUs can be found. The aim of the best possible PMU location (OPMUL) problem is to choose a small number of PMUs that will allow the entire network to be visible. To solve the optimal PMU placement (OPMUP) problem, several meta-heuristic optimization methods have been proposed. The proposed description is put to the test on IEEE 14 test systems, and the findings for full observability of the system under normal conditions are presented in this paper. In IEEE 14 bus systems, the proposed PMU placement has been tested.

The invention of phasor measurement unit (PMU) is considered to be one of the most important breakthroughs in the field of electrical grids monitoring and control. PMUs can be used to obtain accurate voltage and current phasors' measurements. The high cost of installation related to PMU limited its usage and increased the need for optimal allocation of PMUs. A binary bat optimization algorithm is proposed in this paper for solving the optimal PMU placement (OPP) problem to obtain a fully observable system. Simulations are carried on various IEEE bus test systems to ensure the algorithm's effectiveness and feasibility. A comparison is made between the obtained results and the other algorithms' results. The execution time of the proposed algorithm is also compared with other algorithms to illustrate the algorithm's ability to obtain the problem solution with lower execution time and better convergence curve.

Phasor measurement units (PMUs) are becoming popular and populating the power system grids rapidly due to their wide range of benefits and applications. This research paper proposes a comprehensive, effective, and revised formulation of the optimal PMU placement (OPP) problem with a view to minimizing the required number of PMU and ensuring the maximum number of measurement redundancy subjected to the full observability of the distribution grids. The proposed formulation also incorporates the presence of passive measurements/zero injection buses (ZIB) and the channel availability of the installed PMU. Additionally, the formulation is extended to various contingency cases i.e., the single line outage and single PMU loss cases. This paper solves the proposed OPP formulation employing a heuristic technique called backtracking search algorithm (BSA) and tests its effectiveness through different IEEE standard distribution feeders. Additionally, this study compares the obtained results with the mixed integer linear programming (MILP)-based approach and the referenced works. The obtained results demonstrate the superiority of the proposed formulation and solution methodology compared to other methodologies.

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.

Phasor measurement units (PMUs) become a necessity in the modern distribution system especially with the direction towards smart grid. The PMUs should be placed appropriately in the distribution network. The problem of optimal PMU placement for full observability is analyzed in literature. Distribution network reconfiguration for loss reduction is also analyzed in literature. This paper studies the placement problem of PMUs in distribution system considering the system reconfiguration. System reconfiguration is achieved using the ant colony optimization (ACO) algorithm to solve the minimum losses problem. Greedy algorithm is used as an optimization tool to obtain the minimal number of PMUs and their corresponding locations. The 33-node distribution system is tested for optimally locating the PMUs with different network reconfiguration.