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This paper proposes an algorithm that finds the optimal sets of phasor measurement units (PMUs) to achieve a fault observable system, while it addresses the multi‐estimation issue. The optimal PMU placement (OPP) problem here is to find a set of PMU locations with minimum number of members that enables fault observability in a system and satisfies...
Citations
... Many researchers have discussed the OPP scheme for locating faults in power systems [28][29][30][31][32][33][34]. Ref. [28] presented a proposed fault location algorithm that depended on the measurements of the synchronized phasor voltages at both faulted TL terminals and the phasor currents fed from one terminal. ...
... Many researchers have discussed the OPP scheme for locating faults in power systems [28][29][30][31][32][33][34]. Ref. [28] presented a proposed fault location algorithm that depended on the measurements of the synchronized phasor voltages at both faulted TL terminals and the phasor currents fed from one terminal. Although the measurements detected an accurate fault location for the studied system, the manual technique used to detect PMUs' locations may be difficult for larger power systems. ...
... Moreover, the average values of the performance indices are illustrated in Fig. 7. It can be observed that; the proposed algorithm has a good result for wide-range fault conditions with slightly average errors of 0.2312 %. 16 1,4,5,6,9,10,12,15,17,19,21,24,26,27,28,29 New England 39bus 20 2,3,4,6,8,10,12,14,16,17,19,20,21,22,24,25,26,29,36,39 IEEE 118-bus 64 1, 5, 6, 8, 10, 11, 12, 15, 17, 19, 21, 23, 26, 27, 29, 32, 36, 37, 38, 40, 42, 43, 44, 46, 47, 49, 50, 51, 3,5,8,10,13,15,18,23,25,26,28,29,30,31,32,33,34,36,42,43,44,45,48,49,50,51,53,54,55,56,59,63,65,66,67,68,70,71,72,73,74,75,77,78,83,84,89,92,93,94,95,96,99,101,102,103,105,106,108,109,111,112,118,120,124,126,127,128,129,130,136,137,142,143,145,146,148,149,156,160,162,166,167,168,169,171,174,175,181,182,183,185,187,189,191,196,198,199,204,207 1,2,5,6,9,10,11,13,14,17,19,22 23 1,3,4,5,6,7,9,10,11,13,14,16,18,19,20,21,22,23,25,27,28,29,9,30,37,38, 166,169,171,172,175,176,178,181,182,185,188,189,190,191,198,199,204,206,207,211,212,213,217,220,221,222,224,225,227,228 ...
... Just to provide a few instances, an integer quadratic programming optimal μ-PMU placement model is presented in [8], and it consists of two parts including the level of redundancy and other one is the investment cost of μ-PMUs. By increasing network observability and reducing sensitivity to grid factors, the cost function used in [9] seeks to reduce the μ-PMUs installed in the system. The goal function described in [10] incorporates extra parameters that take into consideration the costs of network unobservability and redundancies to improve system observability in both normal operating settings and contingencies, in addition to the overall deployment costs. ...
... The choice to use rectangular variables instead of simplifying the linear system equations used for state estimation comes with associated advantages from a computational viewpoint [21]. R I R I T T T T T T T V V I (9) where the eigenvalues of the argument matrix are returned by the function Eig(.) [22]. ...
A tri-objective optimal Micro Phasor Measurement Units ({\mu}-PMUs) Placement method is presented, with a focus on minimizing the following three parameters: i) the total number of {\mu}-PMU channels, (ii) the maximum state estimation uncertainty, and (iii) the sensitivity of state estimation to line parameter tolerances. The suggested formulation takes single-line and {\mu}-PMU failures into consideration while guaranteeing the complete observability of the system in the presence and absence of contingencies. It also takes into account the impact of zero injection nodes and the quantity of {\mu}-PMU channels carried out at every node. The suggested placement issue is addressed using a customized version of the nondominated sorting genetic algorithm II (NSGA-II). According to the results achieved utilizing three test systems of varying sizes, {\mu}-PMU channels beyond predetermined thresholds only result in higher costs and negligible further decreases in state estimation uncertainty and sensitivity to line parameter tolerances. Additionally, we may omit to instrument between 30 and 40% of buses if {\mu}-PMUs with only two three-phase channels are utilized, with only a modest negative effect on state estimate performance even in the event of contingencies.
... The first level minimizes PMUs number, and the second level maximizes the observability probability. In addition, a sensitivity analysis has been carried out in [37] to consider fault observability which leads to increase the OPP efficiency in WAMS-based fault location. Authors in [38] have considered the effect of network parameters including impedances of transmission lines and transformers on observability of the power system. ...
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.
... PMU can be widely used in many professional fields such as power system state estimation, transient stability analysis and prediction, fault location, system protection and so on, and has a very important position [17][18]. Therefore, a lot of work has been done in the unified planning and deployment of PMU in China. ...
Voltage sags are unavoidable and cause serious harm to sensitive loads. Reasonable configuration of limited monitors can reduce monitoring costs and provide data support for sag management and reduction of sag hazards. Therefore, the optimal configuration of sag monitors is of great significance. Aiming at the traditional method that ignores the inconsistency of the degree of sag damage in different areas, an optimal configuration model of sag monitor considering the reliability of monitoring in sag sensitive areas and the location of phasor measurement unit (PMU) is proposed. The model takes sag observability as a constraint, takes the smallest number of monitors and covers the widest range of sag sensitive areas as the goal, and further configures PMU to assist in monitoring voltage sags. In addition, the Zeroin method is proposed to improve the accuracy of the exposed area calculation. The IEEE-30 system simulation shows that the proposed method can ensure the minimum number of monitor and high redundancy coverage of sensitive loads, ensuring its economic benefits. The proposed method overcomes the difficulty of balancing the monitoring cost with the monitoring capability of sensitive areas.
Various impedance-based fault location algorithms have been presented in the related studies. The algorithms need some phasor data of the power system provided by phasor measurement units (PMUs), implying the necessity of PMU placement to attain fault location observability. This paper develops fault location
observability rules associated with some important impedance-based fault location algorithms based on known state observability theories. The algorithms include two-ends measurements, one-end measurements, one bus space, only synchronized voltage measurements, and wide-area measurements. The developed rules are used
to obtain an index that indicates the number of transmission lines that fault location on them is not possible. The index forms a main constraint or a part of the objective function for the defined PMU placement problem to determine the optimal placement of PMUs for state estimation observability and fault location observability.
The proposed rules and optimization problem are applied to IEEE 14, 30, 39, and 57 buses test networks to study different scenarios.
A problem of great interest for power distribution companies is ensuring uninterrupted service in extensive power distribution systems. Thus, the monitoring of networks and identification of system faults become essential. This work focuses on identifying a fault’s occurrence from a small number of low-cost measurements in a power distribution system. The determination of sensor locations is based on the recent feature selection approach LassoNet, where the measurement locations are ranked. It provides the most informative measures during a fault resulting in a shortening data set. It is used as input to a deep neural network without a significant loss in accuracy. We validate our method on the IEEE 13 and 34 node test feeders for distribution systems to conduct the suggested approach’s experimental studies.
Observability ensured for one distribution topology by a set of μPMUs may overlooks state variables for another one. This paper proposes optimal micro-Phasor Measurement Unit (μPMU) placement in distribution networks, satisfying complete system observability to all possible spanning trees of a radial network, attained by Kirchhoff's matrix tree theorem. Since communication infrastructure is imperative to secure the data transfer from μPMU to Phasor Data Concentrator (PDC), a holistic PDC-communication link placement strategy is indispensable. A convenient procedure for simultaneous PDC and communication link placement is proposed in this paper. This aims at minimizing communication costs and escalating the maximum channel throughput for an optimal number of μPMUs. Costs of PDCs, communication channels, and bandwidth for μPMU to PDC & PDC to PDC are incorporated to attain minimum communication cost. To enhance the maximum channel throughput, minimization of maximum channel load is consolidated within the cost-effective, objective framework. Binary Carnivorous Plant Algorithm (BCPA) is utilized first to get the optimal number of μPMUs. Later, PDC and Communication links are placed optimally. The simulation is carried out for IEEE 33, 34 & 69 test bus systems. The proposed method requires 5.88% lesser μPMUs considering topology changes for IEEE 33 bus system compared to existing literature. The savings in communication cost, and maximum channel load are 35.18% and 21.43%, respectively, for the same system. Whereas, for IEEE 69 bus system, the savings in communication cost, and maximum channel load are 17.65% and 47.06%, respectively.
