State estimation of low voltage distribution network with integrated customer-owned PV and storage unit

Motaz Ayiad; Hugo Martins; Onyema Nduka; Bikash Pal

doi:10.1109/PTC.2019.8810929

State estimation of low voltage distribution network with integrated customer-owned PV and storage unit

Motaz Ayiad, Hugo Martins, Onyema Nduka, Bikash Pal

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The growing integration of rooftop photovoltaics (PVs) and energy storage units (ESUs) in customer households has resulted in changes in the customer load profiles. This is likely to influence the accuracy of state estimation (SE) carried out based on previously assumed load profiles. In this paper, a statistical model for modern low voltage (LV) customers was developed using Gaussian mixture model (GMM). The resulting model was subsequently applied to SE using weighted least squares (WLS) algorithm. LV network with high penetration of customer-owned PV and ESUs have been simulated. Different scenarios which include load profiles: with PVs integrated but without ESUs, ESUs alone, and with hybrid systems (combination of PVs and ESUs) have been considered. The results are presented and discussed.

Original language	English
Title of host publication	2019 IEEE Milan PowerTech
Publisher	IEEE
Pages	1-6
Number of pages	6
ISBN (Electronic)	978-1-5386-4722-6
ISBN (Print)	978-1-5386-4723-3
DOIs	https://doi.org/10.1109/PTC.2019.8810929
Publication status	Published - 26 Aug 2019

Access to Document

10.1109/PTC.2019.8810929

Cite this

@inproceedings{9d6012d11d2143b1bc245b92f50e9daa,

title = "State estimation of low voltage distribution network with integrated customer-owned PV and storage unit",

abstract = "The growing integration of rooftop photovoltaics (PVs) and energy storage units (ESUs) in customer households has resulted in changes in the customer load profiles. This is likely to influence the accuracy of state estimation (SE) carried out based on previously assumed load profiles. In this paper, a statistical model for modern low voltage (LV) customers was developed using Gaussian mixture model (GMM). The resulting model was subsequently applied to SE using weighted least squares (WLS) algorithm. LV network with high penetration of customer-owned PV and ESUs have been simulated. Different scenarios which include load profiles: with PVs integrated but without ESUs, ESUs alone, and with hybrid systems (combination of PVs and ESUs) have been considered. The results are presented and discussed.",

author = "Motaz Ayiad and Hugo Martins and Onyema Nduka and Bikash Pal",

year = "2019",

month = aug,

day = "26",

doi = "10.1109/PTC.2019.8810929",

language = "English",

isbn = "978-1-5386-4723-3",

pages = "1--6",

booktitle = "2019 IEEE Milan PowerTech",

publisher = "IEEE",

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T1 - State estimation of low voltage distribution network with integrated customer-owned PV and storage unit

AU - Ayiad, Motaz

AU - Martins, Hugo

AU - Nduka, Onyema

AU - Pal, Bikash

PY - 2019/8/26

Y1 - 2019/8/26

N2 - The growing integration of rooftop photovoltaics (PVs) and energy storage units (ESUs) in customer households has resulted in changes in the customer load profiles. This is likely to influence the accuracy of state estimation (SE) carried out based on previously assumed load profiles. In this paper, a statistical model for modern low voltage (LV) customers was developed using Gaussian mixture model (GMM). The resulting model was subsequently applied to SE using weighted least squares (WLS) algorithm. LV network with high penetration of customer-owned PV and ESUs have been simulated. Different scenarios which include load profiles: with PVs integrated but without ESUs, ESUs alone, and with hybrid systems (combination of PVs and ESUs) have been considered. The results are presented and discussed.

AB - The growing integration of rooftop photovoltaics (PVs) and energy storage units (ESUs) in customer households has resulted in changes in the customer load profiles. This is likely to influence the accuracy of state estimation (SE) carried out based on previously assumed load profiles. In this paper, a statistical model for modern low voltage (LV) customers was developed using Gaussian mixture model (GMM). The resulting model was subsequently applied to SE using weighted least squares (WLS) algorithm. LV network with high penetration of customer-owned PV and ESUs have been simulated. Different scenarios which include load profiles: with PVs integrated but without ESUs, ESUs alone, and with hybrid systems (combination of PVs and ESUs) have been considered. The results are presented and discussed.

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DO - 10.1109/PTC.2019.8810929

M3 - Conference contribution

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EP - 6

BT - 2019 IEEE Milan PowerTech

PB - IEEE

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