Explore the vast range of titles available.

Phasor Measurement Units (PMUs) have enabled real-time power grid monitoring and control applications realizing an integrated power grid and communication system. The communication network formed by PMUs has strict latency requirements. If PMU measurements cannot reach the control centre within the latency bound, they will be invalid for calculation and may compromise the observability of the whole power grid as well as related applications. To address this issue, this study proposes a model to account for the power grid observability under communication constraints, where effective capacity is adopted to perform a cross-layer statistical analysis in the communication system. Based on this model, three algorithms are proposed for improving power grid observability, which are an observability redundancy algorithm, an observability sensitivity algorithm and an observability probability algorithm. These three algorithms aim at enhancing the power system observability via the optimal communication resource allocation for a given grid infrastructure. Case studies show that the proposed algorithms can improve the power system performance under constrained wireless communication resources.

Summary In this paper, an efficient and comprehensive formulation for the optimal placement of phasor measurement units (PMUs) is proposed to minimize the number of PMU installation subject to full network observability. Moreover, the formulation is extended for assuring complete observability under single PMU loss or single line outage cases. Since the proposed optimization formulation is regarded to be a multiple‐solution one, both the installation cost and measurement redundancy are employed to differentiate the solutions with the same number of PMUs to be installed. In all of the investigations, the effect of zero‐injection buses in the power system is considered. The effectiveness of the proposed method is verified via some IEEE standard systems and compared with some newly reported methods. Results show that the proposed method is simple to implement and more accurate compared to other existing methods. Moreover, by considering the presented method, the minimum number of required PMUs is decreased in some cases. Copyright © 2014 John Wiley & Sons, Ltd.

Summary Effective phasor measurement unit (PMU) placement is a key to the implementation of efficient and economically feasible wide area measurement systems in modern power systems. This paper proposes a pragmatic approach for cost‐effective stage‐wise deployment of PMUs while considering realistic constraints. Inspired from a real world experience, the proposed approach optimally allocates PMU placement in a stage‐wise manner. The proposed approach also considers large‐scale wind integration for effective grid state monitoring of wind generation dynamics. The proposed approach is implemented on the Danish power system projected for the year 2040. Furthermore, practical experience learnt from an optimal PMU placement project aimed at PMU placement in the Danish power system is presented, which is expected to provide insight of practical challenges at ground level that could be considered by PMU placement software developers as well as for future research in this field. Copyright © 2016 John Wiley & Sons, Ltd.

The size and complexity of power network and the cost of monitoring equipments, make it unfeasible to monitor the whole system variables. Conventional system analysers use voltages and currents of the network for monitoring purposes, which affects the system analysis, control and protection. A strategic placement of phasor measurement units (PMUs) is crucial to monitor the whole system with minimum number of devices. This study improves a topological circuit observation method to find essential PMUs. Besides the observability of the normal network, observability of abnormal network is considered. Consequently, a high level of system reliability is achieved. The reliability is maintained by observability under bad current data (CT errors) and all possible single single-line outage. These limitations are taken into the account in a hybrid genetic particle swarm optimisation strategy to minimise monitoring cost and avoiding unobservability under abnormal conditions. Proposed algorithm is tested on 14, 30, 39 and 118-bus IEEE standard test systems and a 24-bus network of Mazandaran Regional Electric Company located in north of Iran.

Phasor measurement units (PMUs), which provide time-synchronized measurements of current and voltage phasors, are considered as an advanced tool for monitoring, protection and management of modern power systems. In this paper, a novel method for optimal placement of PMUs for complete observability of power network is presented. However the installation cost of the PMUs in different places differ with each other, which is related to some factors like as the number of branches connectedto the placed bus, a big quantity of reported methods for optimal PMU placement problem considered an equal cost for PMU installation in different places. An upgraded binary harmony search algorithm is utilized in this paper as an optimization method to attain the minimum number of PMUs and their relevant locations considering the installation costs of the PMUs. The proposed method is applied to IEEE 14-bus, IEEE 30-bus, IEEE 39-bus and IEEE 118-bus standard test systems to obtain the optimal PMU placement. The simulation results confirm that the proposed method is efficient in optimal PMUs placement with minimum cost of configuration.

The PMU placement problem is an optimization problem abstracted from an approach to supervising an electrical power system. The power system is modeled as a graph, and adequate supervision of the system requires that the voltage at each node and the current through each edge be observable. A phasor measurement unit (PMU) is a monitor that can be placed at a node to directly observe the voltage at that node, as well as the current and its phase through all incident edges. The PMU placement problem is to place PMUs at a minimum number of nodes so that the entire electric power system is observed. A new simpler definition of graph observability and several complexity results for the PMU placement problem are presented. The PMU placement problem is shown to be NP-complete even for planar bipartite graphs. Several fundamental properties of PMU placements are proven, including the property that a minimum PMU placement requires no more than 1/3 of the nodes in a connected graph of at least 3 nodes.

This paper presents a robust and optimal metering systems and optimal Phasor Measurement Unit (PMU) placement for real time power system monitoring taking into account of both normal and contingency cases. Two types of contingencies are named as single branch/meter outage and single branch/PMU outage for optimal meter and PMU placement respectively. The placement of meter and PMU are solved by Biogeography Based Optimization. In the PMU placement study, the virtual bus reduction technique is applied for reducing the scale of the system. Developed placement algorithm is illustrated using IEEE standard systems to demonstrate the effectiveness of the proposed algorithm.

Phasor measurement units (PMUs) are essential tools for monitoring, protection and control of power systems. The optimal PMU placement (OPP) problem refers to the determination of the minimal number of PMUs and their corresponding locations in order to achieve full network observability. This paper introduces a recursive Tabu search (RTS) method to solve the OPP problem. More specifically, the traditional Tabu search (TS) metaheuristic algorithm is executed multiple times, while in the initialisation of each TS the best solution found from all previous executions is used. The proposed RTS is found to be the best among three alternative TS initialisation schemes, in regard to the impact on the success rate of the algorithm. A numerical method is proposed for checking network observability, unlike most existing metaheuristic OPP methods, which are based on topological observability methods. The proposed RTS method is tested on the IEEE 14, 30, 57 and 118-bus test systems, on the New England 39-bus test system and on the 2383-bus power system. The obtained results are compared with other reported PMU placement methods. The simulation results show that the proposed RTS method finds the minimum number of PMUs, unlike earlier methods which may find either the same or even higher number of PMUs.

Distribution network state inference refers to the process of calculating the state variables of each node by using measurement data and network models in the operation of the distribution system. However, the uneven measurement layout and insufficient measurement accuracy in the distribution network have brought great challenges to the state inference of the distribution network. This paper proposes a low-observable distribution network state inference method based on a graph convolution network (GCN), which uses sparse measurement data to infer missing measurement information. Firstly, the observability of the distribution network is analyzed by the numerical probability analysis method. Secondly, the GCN is employed to extract feature information from measurement data and integrate these features. The state inference model of the distribution network based on the GCN is established. Subsequently, power flow constraints of the distribution network are incorporated into the GCN training process to enhance the precision of the generated data. Ultimately, the efficacy of the proposed method is validated using the IEEE 33-node distribution system.

This paper considers the problem of estimating the states in an unobservable power system, where the number of measurements is not sufficiently large for conventional state estimation. Existing methods are either based on pseudo-data that is inaccurate or depends on a large amount of data that is unavailable in current systems. This study proposes novel graph signal processing (GSP) methods to overcome the lack of information. To this end, first, the graph smoothness property of the states (i.e., voltages) is validated through empirical and theoretical analysis. Then, the regularized GSP weighted least squares (GSP-WLS) state estimator is developed by utilizing the state smoothness. In addition, a sensor placement strategy that aims to optimize the estimation performance of the GSP-WLS estimator is proposed. Simulation results on the IEEE 118-bus system show that the GSP methods reduce the estimation error magnitude by up to two orders of magnitude compared to existing methods, using only 70 sampled buses, and increase of up to 30% in the probability of bad data detection for the same probability of false alarms in unobservable systems The results conclude that the proposed methods enable an accurate state estimation, even when the system is unobservable, and significantly reduce the required measurement sensors.