Optimal PMU Placement Technique to Maximize Measurement Redundancy Based on Closed Neighbourhood Search

Hyacinth, Lourdusamy Ramya; Venugopal, G.

doi:10.3390/en14164782

Cited by 8 publications

(5 citation statements)

References 38 publications

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“…Semi-definite programming optimizes a linear objective function under linear matrix inequality (LMI) constraints, whereas the solution is found in a binary decision domain [26][27][28]. An optimization strategy is presented in which the task of maximum measurement redundancy is considered based on a neighborhood search [29].…”

Section: Introductionmentioning

confidence: 99%

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

Theodorakatos,

Babu,

Moschoudis

2023

Axioms

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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.

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Section: Introductionmentioning

confidence: 99%

“…A three-phase algorithm is utilized to find the minimum number of PMUs required to render the system entirely observable [29]. The numerical outcome illustrates that the proposed methodology is easy to implement and gives optimal placement sites to achieve effective observation in wide area monitoring systems (WAMS).…”

Section: Introductionmentioning

confidence: 99%

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

Theodorakatos,

Babu,

Moschoudis

2023

Axioms

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“…Hyacinth et al [64] proposed optimal PMU placement with maximized measurement redundancy based on the three major attributes in deciding placement locations: the degree of the vertex (DOV), the average neighborhood degree of the vertex (ANDOV), and the bus observability index (BOI) in the first stage and minimized the number of PMUs in next stage.…”

Section: Linear Programming (Lp) Based Oppmentioning

confidence: 99%

A Critical Review of State-of-the-Art Optimal PMU Placement Techniques

et al. 2022

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Phasor measurement unit (PMU) technology is a need of the power system due to its better resolution than conventional estimation devices used for wide-area monitoring. PMUs can provide synchronized phasor and magnitude of voltage and current measurements for state estimation of the power system to prevent blackouts. The drawbacks of a PMU are the high cost of the device and its installation. The main aspect of using PMUs in electrical networks is the property to observe the adjacent buses, thereby making it possible to observe the system with fewer PMUs than the number of buses through their optimal placement. In the last two decades, exhaustive research has been done on this issue. Considering the importance of this field, a comprehensive review of the progress achieved until now is carried out and the limitations of existing reviews in the literature are highlighted. This paper can be seen as a major attempt to provide an up-to-date review of the research work carried out in this all-important field of PMU placement and indicates that some perspectives of optimal PMU placement still need attention. Eventually, the work will open a new standpoint for the research community to fill the research gap.

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“…To achieve complete observability of the system, it is crucial to address the Optimal Placement of PMUs (OPP) by strategically installing them on selected buses and minimizing their number. Achieving OPP through improvement in redundancy is essential to eliminate inaccurate evaluations of operational status by discarding unreliable data from critical measurements during the process of state estimation 9 . Thus, the emphasis of OPP should be on utilizing the fewest possible phasor units while maximizing the number of measurements.…”

Section: Introductionmentioning

confidence: 99%

“…Achieving OPP through improvement in redundancy is essential to eliminate inaccurate evaluations of operational status by discarding unreliable data from critical measurements during the process of state estimation. 9 Thus, the emphasis of OPP should be on utilizing the fewest possible phasor units while maximizing the number of measurements.…”

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confidence: 99%

Multi‐objective precise phasor measurement locations to assess small‐signal stability using dingo optimizer

Logeshwari,

Abirami,

Subramanian

et al. 2023

Optim Control Appl Methods

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Small‐signal stability is an important task and key research in electrical engineering for networks. This research article focuses on the implementation of a multi‐objective approach for choosing an optimal location for Phasor Measurement Units (PMUs) to quantify a power system's small‐signal stability by maximizing the signal‐to‐noise ratio (SNR) in the system. The novelty of this research lies in the implementation of Dingo Optimization (DOX) technique along with the Prony Analysis (PA) approach for the assessment of small‐signal stability in standard grid networks. The voltage angle, amplitude and the range of frequencies are measured by the optimal placement of PMUs, which primarily focus on the multi‐signal PA. To achieve the objective of this research, DOX integrated with the multi‐signal PA approach is used to determine the ideal position for PMU placement by considering maximum redundancy and optimizing the signal to noise ratio to a maximum level. The effectiveness of the DOX strategy is established with improved accuracy and fewer disturbances by optimizing the electromechanical oscillations of the system. The implementation of the DOX approach for attaining the best value of the maximized SNR is obtained by analyzing a wide set of conditions, perturbations, and additive noise, which provides an accurate assessment of damping ratio (DR) and frequency (f) of electromechanical oscillations. Numerical results obtained from the standard IEEE test systems (14, 39, 57, 118, and 300 bus systems) are compared with the existing methods in the literature. The statistical indices demonstrate that under the highly limited optimization context selected, the intended optimizer functions satisfactorily.

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Optimal PMU Placement Technique to Maximize Measurement Redundancy Based on Closed Neighbourhood Search

Cited by 8 publications

References 38 publications

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

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

A Critical Review of State-of-the-Art Optimal PMU Placement Techniques

Multi‐objective precise phasor measurement locations to assess small‐signal stability using dingo optimizer

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