A novel Optimal PMU Location Method in Smart Grids

Amiri, Karim; Kazemzadeh, Rasool; Eghbali, Omid

doi:10.1109/sgc.2018.8777896

Cited by 2 publications

(3 citation statements)

References 14 publications

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“…However, it is expensive and requires further development to reduce costs with high performance. In [3], the author discussed the optimal allocation of PMUs to cover the grid with a minimum number of PMUs for microgrids.…”

Section: Figure 1: Elements Of Smart Gridmentioning

confidence: 99%

“…The measurement equation is expressed by z(k), which involves the observation matrix H, and the measurement noisev (k). The application of the second-order Kalman filter indicates a mathematical model for the system's phase in the state space variables where the time update equation includes the transition matrix with the addition to the noise in (3). The PMU's general plant dynamical solution takes its place in both the time update equation and the measurement equation to update the estimation process to the phase error minimization.…”

Section: The Model Function Of the Pmumentioning

confidence: 99%

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A Robust Asynchrophasor in PMU Using Second-Order Kalman Filter

Alqahtani¹,

Alqahtani²

2023

Computers, Materials &Amp; Continua

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Phasor Measurement Units (PMUs) provide Global Positioning System (GPS) time-stamped synchronized measurements of voltage and current with the phase angle of the system at certain points along with the grid system. Those synchronized data measurements are extracted in the form of amplitude and phase from various locations of the power grid to monitor and control the power system condition. A PMU device is a crucial part of the power equipment in terms of the cost and operative point of view. However, such ongoing development and improvement to PMUs' principal work are essential to the network operators to enhance the grid quality and the operating expenses. This paper introduces a proposed method that led to lowcost and less complex techniques to optimize the performance of PMU using Second-Order Kalman Filter. It is based on the Asyncrhophasor technique resulting in a phase error minimization when receiving the signal from an access point or from the main access point. The MATLAB model has been created to implement the proposed method in the presence of Gaussian and non-Gaussian. The results have shown the proposed method which is Second-Order Kalman Filter outperforms the existing model. The results were tested using Mean Square Error (MSE). The proposed Second-Order Kalman Filter method has been replaced with a synchronization unit into the PMU structure to clarify the significance of the proposed new PMU.

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Section: Figure 1: Elements Of Smart Gridmentioning

confidence: 99%

Section: The Model Function Of the Pmumentioning

confidence: 99%

A Robust Asynchrophasor in PMU Using Second-Order Kalman Filter

Alqahtani¹,

Alqahtani²

2023

Computers, Materials &Amp; Continua

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“…The emergence of 5G communication network greatly promotes the development of distributed information collection and real-time information transmission and processing services required by smart grid systems. Conventionally, studies on the communication network and the smart grid system is done separately, for example [1], [2]. However, to better serve the needs of the smart grid system, joint study of the communication network and the power network is needed.…”

Section: Introductionmentioning

confidence: 99%

Statistical Power Grid Observability under Finite Blocklength

Zhan

Liu

Pan

et al. 2022

2022 3rd International Conference on Computing, Networks and Internet of Things (CNIOT)

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We study the stochastic observability of the power grid system under communication constraints in the finite blocklength regime. Compared to the study under the assumption of infinite blocklength, we introduce two new elements: probability of decoding error and transmission delay. An optimization problem to maximize the observability of the smart grid over all possible bandwidth allocation is proposed, incorporating these two new elements. To solve the optimization problem, for a given bandwidth allocation, we first solve parallel subproblems, one for each synchronous phasor measurement unit (PMU), using alternating optimization, to find the optimal QoS exponent, transmission delay and probability of decoding error for each PMU. Then, simulated annealing method is used to find the optimal bandwidth allocation among PMUs. Numerical results verify that the assumption of infinite blocklength is indeed too optimistic and instead, finite blocklength should be studied. Large bandwidth saving gains of the proposed scheme are demonstrated compared to the equal bandwidth allocation scheme.

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A novel Optimal PMU Location Method in Smart Grids

Cited by 2 publications

References 14 publications

A Robust Asynchrophasor in PMU Using Second-Order Kalman Filter

A Robust Asynchrophasor in PMU Using Second-Order Kalman Filter

Statistical Power Grid Observability under Finite Blocklength

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