Consumer phase identification in a three phase unbalanced LV distribution network

Pezeshki, Houman; Wolfs, P.

doi:10.1109/isgteurope.2012.6465632

Cited by 80 publications

(67 citation statements)

References 16 publications

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“…Paper [6] proposes a method using graph theory based on a principal component analysis (PCA), whereas [7], [8] use a correlation-based approach exploiting the similarities between the voltage measurements of the same phase (k-means clustering). Papers [1], [9], [10] explicitly identify the phases with either energy or voltage measurements. [9] applies graph theory and PCA to identify the phases of a simulated dataset, taking into account the effect of noise.…”

Section: B Automatic Methodsmentioning

confidence: 99%

“…[9] applies graph theory and PCA to identify the phases of a simulated dataset, taking into account the effect of noise. [10] uses correlation to find how to locally associate the phases of each smart meter to the phases of a reference meter. Finally, instead of directly employing correlation, [1] extracts features on which they perform a k-means clustering.…”

Section: B Automatic Methodsmentioning

confidence: 99%

“…Correlation-based approaches seem very well adapted to the phase identification problem and have been successfully used in [8], [10]. The proposed algorithms also use Pearson's correlation to assess the similarities between two time series M 1 and M 2 , gathering the measurements of the phase-toneutral voltage magnitudes:…”

Section: A Definition Of the Distance Between Two Voltage Measurementsmentioning

confidence: 99%

See 2 more Smart Citations

Phase Identification of Smart Meters by Clustering Voltage Measurements

Frédéric

Sutera

Geurts

et al. 2018

2018 Power Systems Computation Conference (PSCC)

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Abstract-When a smart meter, be it single-phase or threephase, is connected to a three-phase network, the phase(s) to which it is connected is (are) initially not known. This means that each of its measurements is not uniquely associated with a phase of the distribution network. This phase information is important because it can be used by Distribution System Operators to take actions in order to have a network that is more balanced.In this work, the correlation between the voltage measurements of the smart meters is used to identify the phases. To do so, the constrained k-means clustering method is first introduced as a reference, as it has been previously used for phase identification. A novel, automatic and effective method is then proposed to overcome the main drawback of the constrained k-means clustering, and improve the quality of the clustering. Indeed, it takes into account the underlying structure of the low-voltage distribution networks beneath the voltage measurements without a priori knowledge on the topology of the network. Both methods are analysed with real measurements from a distribution network in Belgium. The proposed algorithm shows superior performance in different settings, e.g. when the ratio of single-phase over threephase meters in the network is high, when the period over which the voltages are averaged is longer than one minute, etc.

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Section: B Automatic Methodsmentioning

confidence: 99%

Section: B Automatic Methodsmentioning

confidence: 99%

Section: A Definition Of the Distance Between Two Voltage Measurementsmentioning

confidence: 99%

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Phase Identification of Smart Meters by Clustering Voltage Measurements

Frédéric

Sutera

Geurts

et al. 2018

2018 Power Systems Computation Conference (PSCC)

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“…The load signatures are similar for all loads in this paper, however, upon availability of data, different load patterns can easily be included in this approach. The data is derived from reference [15], which is based on a study in Western Australia. The data for summer, autumn, and spring were measured from 11/0.4KV transformer side for each load point and PV.…”

Section: Load Flow Analysismentioning

confidence: 99%

Impact of PV units in LV feeders on distribution system reliability

Zamanabadi

Nourbakhsh

Ledwich

2014

2014 Australasian Universities Power Engineering Conference (AUPEC)

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Re-supplying loads on outage through cross-connect from adjacent feeders in a distribution system may cause voltage drop and hence require load shedding. However, the surplus PV generated in some of the LV feeders can prevent load shedding, and improve reliability. In order to measure these effects, this paper proposes the application of Direct Load Flow method[1] in reliability evaluation of distribution systems with PV units. As part of this study, seasonal impacts on load consumption together with surplus PV output power injection to higher voltage networks are also considered. New indices are proposed to measure yearly expected energy export, from LV to MV and from MV to higher voltage network.

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“…Exact lengths between houses, or of the connecting cable between smart meter and distribution feeder are often not available. Moreover, the phase to which each household with a single phase connection is connected is often unknown [32]- [34]. This information is crucial for the previously mentioned algorithms.…”

Section: Introductionmentioning

confidence: 99%