Possibility of enhancing classical weighted least squares State Estimation with linear PMU measurements

Bruno, Claudio; Candia, C.; Franchi, Loris; Giannuzzi, Giorgio Maria; Pozzi, M.; Zaottini, Roberto; Zaramella, M.

doi:10.1109/ptc.2009.5281817

Cited by 14 publications

(11 citation statements)

References 5 publications

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“…The WAMS developed in Italy consists of a set of PMUs, a dedicated data network and computer systems for data processing and management, including monitoring applications and intelligent display at the National Control Center of TERNA in Rome [2,[24][25][26][27][28][29].…”

Section: Overview Of the Italian Wamsmentioning

confidence: 99%

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Wide area monitoring in the Italian power system: architecture, functions and experiences

Cirio

Lucarella

Giannuzzi

et al. 2010

Int Trans Elec Energy Syst

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SUMMARYThe paper reports the main features of the Wide Area Measurement System (WAMS) in operation at the Italian power system. First, the architecture of the WAMS platform is described; then, the visualisation functions are presented. The latter provide the data measured by the phasor measurement units, together with the results of real time monitoring functions for enhanced operational awareness. Functions have been developed for oscillatory stability analysis, network separation detection, voltage stability margin evaluation, load shedding intervention evaluation, line thermal estimation. Application examples are shown, drawn from real cases. The WAMS platform, running in real time in the control room, has proved useful in normal and especially in critical operating conditions, when the limitations of traditional SCADA systems and analysis tools are most apparent. The development of real-time functions is still ongoing, also in view of implementing Wide Area Control/Protection System solutions.

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Section: Overview Of the Italian Wamsmentioning

confidence: 99%

“…It works as an independent data source. However, following a preliminary phase of off-line studies [29], the introduction of PMU measurements into the state estimation algorithm is currently under way, with the objective to improve convergence and accuracy of the results.…”

Section: Level Of Integrationmentioning

confidence: 99%

Wide area monitoring in the Italian power system: architecture, functions and experiences

Cirio

Lucarella

Giannuzzi

et al. 2010

Int Trans Elec Energy Syst

Self Cite

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“…Assume that the noise for each measurement has zero mean and is independent [8]. The covariance matrix for all measurement noise is:…”

Section: Weighted Least Squares Estimationmentioning

confidence: 99%

Basic Concepts and Control Architecture of Microgrids

Gao

2015

Energy Storage for Sustainable Microgrid

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“…The authors of [7,8] [7,8]. The contribution of phasor measurements units to enhance distribution SE algorithms has been analyzed in detail in [9][10][11]. In other works, such as [2,12], authors have applied artificial neural networks (ANN) to estimate system state variables.…”

Section: Introductionmentioning

confidence: 99%

Exploiting autoencoders for three-phase state estimation in unbalanced distributions grids

Barbeiro

Teixeira

Krstulovic

et al. 2015

Electric Power Systems Research

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a b s t r a c tThe three-phase state estimation algorithms developed for distribution systems (DS) are based on traditional approaches, requiring components modeling and the complete knowledge of grid parameters. These algorithms are capable of dealing with the particular characteristics of DS but cannot be used in cases where grid topology and parameters are unknown, which is the most common situation in existing low voltage grids.This paper presents a novel three-phase state estimator for DS that enables the explicit estimation of voltage magnitudes and phase angles in all phases, neutral, and ground wires even when grid topology and parameters are unknown. The proposed approach is based on the use of auto-associative neural networks, the autoencoders (AE), which only require an historical database and few quasi-real-time measurements to perform an effective state estimation.Two test cases were used to evaluate the algorithm's performance: a low and a medium voltage grid. Results show that the algorithm provides accurate results even without information about grid topology and parameters. Several tests were performed to evaluate the best AE configuration. It was found that training an AE for each network feeder leads generally to better results than having a single AE for the entire system. The same happened when different AE were trained for each network phase in comparison with a single AE for the three phases.

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Possibility of enhancing classical weighted least squares State Estimation with linear PMU measurements

Cited by 14 publications

References 5 publications

Wide area monitoring in the Italian power system: architecture, functions and experiences

Wide area monitoring in the Italian power system: architecture, functions and experiences

Basic Concepts and Control Architecture of Microgrids

Exploiting autoencoders for three-phase state estimation in unbalanced distributions grids

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