Optimal Placement of PMU in Distribution Systems Considering State Estimation Error

Chen, Tengpeng; Ren, He; Chen, Xuebing; Sun, Yuhao

doi:10.23919/ccc52363.2021.9550481

Cited by 4 publications

(9 citation statements)

References 33 publications

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“…On the basis of the optimization problem in [30], the objective of the proposed OPP method is to obtain the minimum number of PMUs while considering the PMU CLs, ZI-Bs, single PMU loss contingency, SCADA measurements, SEE, and MSEEV.…”

Section: Proposed Opp Methodsmentioning

confidence: 99%

“…The influence function (IF) can be further used to derive the SEE variance matrix of an estimator [30], [36], [37]:…”

Section: A Preliminaries Of Proposed Opp Methodsmentioning

confidence: 99%

“…1 if q j0 = 1 and the g th channel of PMU placed at bus j is available 0 otherwise (30) The dimension of the new PMU placement decision vector q is given as:…”

Section: Opp Problem Considering Pmu Cls Zibs Single Pmu Loss Conting...mentioning

confidence: 99%

“…According to (29) and (32), it is clear that the dimension of the problem given in (33) is larger than that presented in [30]. The ZIBs, single PMU loss contingency, and existing SCADA measurements are widely considered in OPP problems [14], [39], [40].…”

Section: Opp Problem Considering Pmu Cls Zibs Single Pmu Loss Conting...mentioning

confidence: 99%

“…However, [27] and [28] find that the distribution of PMU measurement noise is non-Gaussian. Therefore, the previous work in [29], [30] introduces an optimal PMU selection method, in which the measurement noise is considered as non-Gaussian and the maximum likelihood estimator (MLE) is applied. However, this method is one kind of PMU selection methods and is based on the assumption that a sufficient number of PMUs are installed in the monitoring system.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Optimal Placement of Phasor Measurement Unit in Smart Grids Considering Multiple Constraints

Chen

He²,

Sun³

et al. 2023

Journal of Modern Power Systems and Clean Energy

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The distribution of measurement noise is usually assumed to be Gaussian in the optimal phasor measurement unit (PMU) placement (OPP) problem. However, this is not always accurate in practice. This paper proposes a new OPP method for smart grids in which the effects of conventional measurements, limited channels of PMUs, zero-injection buses (ZIBs), single PMU loss contingency, state estimation error (SEE), and the maximum SEE variance (MSEEV) are considered. The SEE and MSEEV are both obtained using a robust t-distribution maximum likelihood estimator (MLE) because t-distribution is more flexible for modeling both Gaussian and non-Gaussian noises. The A-and G-optimal experimental criteria are utilized to form the SEE and MSEEV constraints. This allows the optimization problem to be converted into a linear objective function subject to linear matrix inequality observability constraints. The performance of the proposed OPP method is verified by the simulations of the IEEE 14-bus, 30-bus, and 118-bus systems as well as the 211-bus practical distribution system in China.

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Section: Proposed Opp Methodsmentioning

confidence: 99%

“…The influence function (IF) can be further used to derive the SEE variance matrix of an estimator [30], [36], [37]:…”

Section: A Preliminaries Of Proposed Opp Methodsmentioning

confidence: 99%

“…1 if q j0 = 1 and the g th channel of PMU placed at bus j is available 0 otherwise (30) The dimension of the new PMU placement decision vector q is given as:…”

Section: Opp Problem Considering Pmu Cls Zibs Single Pmu Loss Conting...mentioning

confidence: 99%

Section: Opp Problem Considering Pmu Cls Zibs Single Pmu Loss Conting...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Optimal Placement of Phasor Measurement Unit in Smart Grids Considering Multiple Constraints

Chen

He²,

Sun³

et al. 2023

Journal of Modern Power Systems and Clean Energy

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show abstract

Optimal placement of distribution-level synchrophasor sensors for distribution system

Chen¹,

Liu²,

Chen³

et al. 2022

Meas. Sci. Technol.

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This paper proposes a new method for the placement of the important synchrophasor sensors, the Distribution-level Phasor Measurement Units (DPMUs). The new objective function and constraints are developed to achieve the minimization of distribution system state estimation error, in the presence of the limited number of DPMUs, the zero injection buses, the limited DPMU channels and the Supervisory Control And Data Acquisition (SCADA) measurements. The A-optimal experimental design criterion is utilized to formulate the proposed objective function and constraints. The state estimation error is obtained using the maximum likelihood estimator under non-Gaussian measurement noise since the traditional assumption of Gaussian noise may violate the reality. The performance of the proposed method is demonstrated by simulations on the IEEE 34-bus and 123-bus distribution systems.

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Power Quality Meter Placement in Distribution Networks for Identification of Cryptocurrency Miners using Harmonic State Estimation

Es’Haghi,

Abbaspour,

Marini

2024

2024 28th International Electrical Power Distribution Conference (EPDC)

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Optimal Placement of PMU in Distribution Systems Considering State Estimation Error

Cited by 4 publications

References 33 publications

Optimal Placement of Phasor Measurement Unit in Smart Grids Considering Multiple Constraints

Optimal Placement of Phasor Measurement Unit in Smart Grids Considering Multiple Constraints

Optimal placement of distribution-level synchrophasor sensors for distribution system

Power Quality Meter Placement in Distribution Networks for Identification of Cryptocurrency Miners using Harmonic State Estimation

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