Optimal placement of PMUs with limited number of channels

Miljanic, Zoran; Djurović, Igor; Vujošević, Ilija

doi:10.1016/j.epsr.2012.04.010

Cited by 67 publications

(29 citation statements)

References 15 publications

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“…Therefore, the complicated monitoring and control issues of modern power systems, turns power engineers to make use of PMU capabilities to avoid or to mitigate the impact of the line outage or the loss of the PMU itself. For the above purpose, new tools like the Cellular Genetic Algorithm (CGA) have been developed to obtain the reliability goal by Miljanic et al [19]. The CGA is used for computing the minimum number of PMUs and their placement in case of limited availability of communication channels and branch outage as well.…”

Section: Pmu's Placement Approaches With Simulation Resultsmentioning

confidence: 99%

“…Again, graph theory plays a significant role in analyzing methods due to its ability to represent the topological configuration of power systems. Thus, Anderson et al [19] use graph theory for the topological analysis of the placement problem by considering the number of available channels and branch outages. The Binary Integer Programming method has its role in state estimation reliability studies, where the researcher of [20] has used this method for achieving a complete topological observability using minimum number of PMUs.…”

Section: Pmu's Placement Approaches With Simulation Resultsmentioning

confidence: 99%

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Recent Development in Power System Dynamic State Estimation

Khandelwal¹,

Saxena²,

Tandon³

2017

IJERMT

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Abstractue to the expansion of power systems there is a challenge of real time monitoring and control by placing important parameters at various points for efficient functioning of the power system. There can be drastic changes during hourly load fluctuations, component outages, or network switching. In such conditions, the inclusion of predicted values could degrade the power system state estimation hence the need of state estimation is must. Synchronized Phasor Measurement Units (PMU) are being placed along with the GPS (global positioning system) to enhance the monitoring of the power system. It depends on the measurement numbers, types and locations. This paper aims to present the main categories for PMUs placement strategies which considers main factors that required for enhancing the performance of a state estimation process such as reliability, accuracy and the special requirements of the modern distribution grid.Keywords-Phasor Measurement Unit, Global Positioning Systems, State Estimations, Weighted Least Square Method, Observability I. INTRODUCTIONThe enlargement of power system has made more and more intricacy so real time checking and control became very significant for the consistent operation of power system and which the Energy Management System (EMS) cures. In this system, the State estimation forms the spine of the energy management system by providing a database of the real time state of the system for using in other EMS functions [1]. Therefore, efficient and accurate state estimation is a prerequisite for an efficient and consistent operation of the power system.State estimation is a technique where the voltage, magnitude and angles at all the buses of a power system are recorded from the existing measurements. These measurements are obtained through a suitable communication standard and are processed through state estimation procedures, to obtain the voltage magnitude and angle at all the buses of the network under consideration. As we know that the power system is a quasi-static system, hence changes slowly but progressively which are driven by dynamic load so the generations also have to be adjusted accordingly, which in turn changes the flows and injections across the system, which makes the entire system dynamic in nature. Therefore, in order to have a continuous monitoring of the power system, we must perform the state estimation at regular interval of time. However, by the expansion of power system, along with addition of generations and loads, this system becomes more complex for such monitoring, which requires heavy computing resources. Hence, static state estimators may not capably capture this dynamic behavior of the power system. This lead to the necessity of another set of procedures called the "Dynamic State Estimation" (DSE) techniques, where we use the actual physical modeling of the time varying nature of the power system. These procedures have dual advantages of being more accurate and possessing the ability to predict the state of the system at next step. That is, from the ...

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Section: Pmu's Placement Approaches With Simulation Resultsmentioning

confidence: 99%

Section: Pmu's Placement Approaches With Simulation Resultsmentioning

confidence: 99%

Recent Development in Power System Dynamic State Estimation

Khandelwal¹,

Saxena²,

Tandon³

2017

IJERMT

View full text Add to dashboard Cite

show abstract

“…For the above purpose, new tools like the Cellular Genetic Algorithm (CGA) have been developed to obtain the reliability goal by Miljanic et al [17]. The CGA is used for computing the minimum number of PMUs and their placement in case of limited availability of communication channels and branch outage as well.…”

Section: B Reliability Requirementsmentioning

confidence: 99%

A review on phasor measurement units placement for state estimation studies

Abood

Sreeram

2014

2014 Australasian Universities Power Engineering Conference (AUPEC)

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State estimation operation depends on the measurement numbers, types and locations. Therefore, the adoption of an efficient placement method for selecting the required numbers of meters and their location is an essential process for power systems monitoring. In fact, the Phasor measurement Unit (PMU) is, currently, one of the most efficient devices for measuring real-time electrical quantities. Consequently, this paper aims to present the main categories for PMUs placement strategies according to the objectives of PMUs employment. The PMUs placement strategy should take into consideration main factors that required for enhancing the performance of a state estimation process such as reliability, accuracy and the special requirements of the modern distribution grid. A review of literatures that address PMUs placement methods is presented in this paper in addition to suggestions for developing the PMUs placement methods to be more feasible for modern power networks.

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“…they can measure currents of multiple lines (or branches), and are able to consider specific cases of outages [2], [3]. The common way to include multiple input channels is to use measurement Jacobian matrices, which are formed and analysed separately for every outage case.…”

Section: Introductionmentioning

confidence: 99%

Optimal placement of branch PMUs for specified redundancy and line observability

Tuttelberg

Kilter

2015

2015 IEEE Power &Amp; Energy Society General Meeting

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This paper presents a solution for the optimal placement of branch PMUs (PMUs that measure a single set of three-phase voltage and current phasors) considering specific measurement redundancy requirements for the observability of buses. The classical bus observability condition in optimal PMU placement assumes the measurement of currents of all lines connected to the PMU bus, making most developed optimisation methods impractical in real-world systems. Compared to existing methods for the optimal placement of branch PMUs (or PMUs with input channel limits), the proposed method inherently enables to consider the outages of all lines or PMUs, distinguishes between the ends of the branches (i.e. for each branch PMU the optimal bus is also chosen), enables to specify conditions for direct observability of transmission lines, and is simple to implement and solve.

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Optimal placement of PMUs with limited number of channels

Cited by 67 publications

References 15 publications

Recent Development in Power System Dynamic State Estimation

Recent Development in Power System Dynamic State Estimation

A review on phasor measurement units placement for state estimation studies

Optimal placement of branch PMUs for specified redundancy and line observability

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