Model Order Reduction for PMU-Based State Estimation in Distribution Grids

Carta, Daniele; Benigni, Andrea; Muscas, Carlo

doi:10.1109/jsyst.2017.2697309

Cited by 26 publications

(15 citation statements)

References 23 publications

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“…However, compared to smart meters, the use of PMUs in distribution networks is still very restricted due to their prohibitive costs. Hence, a critical research direction related to PMUs is optimizing the number and location of PMUs to enhance system observability, while limiting the measurement infrastructure costs [81] (also see Section VI-A).…”

Section: B Pmu Applications and Impacts On Dssementioning

confidence: 99%

A Survey on State Estimation Techniques and Challenges in Smart Distribution Systems

Dehghanpour

Wang

et al. 2019

IEEE Trans. Smart Grid

359

173

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This paper presents a review of the literature on State Estimation (SE) in power systems. While covering some works related to SE in transmission systems, the main focus of this paper is Distribution System State Estimation (DSSE). The paper discusses a few critical topics of DSSE, including mathematical problem formulation, application of pseudomeasurements, metering instrument placement, network topology issues, impacts of renewable penetration, and cyber-security. Both conventional and modern data-driven and probabilistic techniques have been reviewed. This paper can provide researchers and utility engineers with insights into the technical achievements, barriers, and future research directions of DSSE.

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Section: B Pmu Applications and Impacts On Dssementioning

confidence: 99%

A Survey on State Estimation Techniques and Challenges in Smart Distribution Systems

Dehghanpour

Wang

et al. 2019

IEEE Trans. Smart Grid

359

173

View full text Add to dashboard Cite

show abstract

“…Due to the great advantages of using PMU measurements, it is expected that most power systems install redundant enough PMUs in the future. Thus, in line with many recent SE works, such as [10][11][12][13][14][15], in this paper, it is assumed that the number of installed PMUs is sufficient to make the network observable. However, despite the advantages of the PMU-based LAV estimator, it is not robust against parameter error and its estimations might be inaccurate in the presence of parameter errors.…”

Section: Introductionmentioning

confidence: 95%

Robust optimisation‐based state estimation considering parameter errors for systems observed by phasor measurement units

Kabiri

Amjady

2018

IET Generation, Transmission & Distribution

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“…The proposed routine relies on the voltage measurements of a crucial set of buses and the neighboring state variables are adjusted iteratively to fit the measured values. In the same context, a model order reduction method is performed on the DG in [12]. The algorithm selects a number of nodes and branches and reduces them to an equivalent one.…”

Section: Introductionmentioning

confidence: 99%

“…However, we have to take into account that (in contrast to the case of substation transformers), the voltage base (used for the per-unit calculations) in both areas aside from ILVRs is equal. That given, the ILVRs (when active) will break down the feeders in areas of different per-unit voltage levels, leading the total variation regularization term in (12) to possible inefficiency. In order to deal with this specificity of WTVSE, for the numerical treatment of the ILVRs we will follow a decomposed formulation based on their location.…”

mentioning

confidence: 99%

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A regularized state estimation scheme for a robust monitoring of the distribution grid

Tsitsimelis

Antón-Haro

2020

International Journal of Electrical Power & Energy Systems

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In this paper, we propose a regularized state estimation (SE) scheme for the distribution grid. The ultimate goal is to track accurately the system state at a faster time scale according to the requirements of the new operational environment. The SE algorithm operates at two different time scales in which the set of available measurements are different. At the main time instants (every 15 minutes) the set of observations comprises SCADA measurements, pseudomeasurements and micro Phasor Measurement Units (µPMUs). In this case, we resort to a Regularized version of the Normal Equations based SE (R-NESE). In the intermediate time instants, only a reduced number of µPMU measurements is available. To circumvent observability issues, we exploit the fact that the voltage drop in adjacent buses is limited and, on that basis, a regularized weighted total variation estimation (WTVSE) problem is formulated. Then, the impact of in-line voltage regulators (IVLRs) is explicitly taken into consideration and that, forces us to decompose and solve the original SE problem for a number of smaller regions (D-WTVSE). The latter can be iteratively solved by resorting to the Alternating Direction Method of Multipliers (ADMM). Complementarily, we also present a µPMU placement method (µPP) in order to improve the conditioning of the R-NESE problem. This problem can be posed as a mixed integer semidefinite programming model (MISDP) and, thus, can be efficiently solved. The performance of the proposed scheme is numerically assessed on (mostly) a 95-bus distribution system for a number of realistic conditions of noise, load and photovoltaic generation profiles. A number of benchmarks are provided, as well.

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Model Order Reduction for PMU-Based State Estimation in Distribution Grids

Cited by 26 publications

References 23 publications

A Survey on State Estimation Techniques and Challenges in Smart Distribution Systems

A Survey on State Estimation Techniques and Challenges in Smart Distribution Systems

Robust optimisation‐based state estimation considering parameter errors for systems observed by phasor measurement units

A regularized state estimation scheme for a robust monitoring of the distribution grid

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