A linearized probabilistic load flow method to deal with uncertainties in transmission networks

J. Reinders; N. Paterakis; J. Morren; J.G. Slootweg

doi:10.1109/PMAPS.2018.8440326

A linearized probabilistic load flow method to deal with uncertainties in transmission networks

J. Reinders, N. Paterakis, J. Morren, J.G. Slootweg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

5 Citations (Scopus)

Abstract

Increasing decentralized solar and wind power production, introduces uncertainty in the electricity network and especially at the interface between transmission and distribution network. Analytical probabilistic load flow methods provide a way to incorporate uncertainty in the load flow equation, retaining acceptable accuracy without requiring significant computational power. However, the assumption that is commonly adopted is that the uncertain variables are normally distributed. The integration of wind and solar power may lead to the deprecation of the normality assumption. By comparing different distributions describing nodal powers on a standard test network, this paper assesses the usability of first order Taylor approximation to incorporate uncertainty in load flow equations in comparison with a Monte-Carlo based probabilistic load flow.

Original language	English
Title of host publication	2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Number of pages	6
ISBN (Electronic)	978-1-5386-3596-4
ISBN (Print)	9781538635964
DOIs	https://doi.org/10.1109/PMAPS.2018.8440326
Publication status	Published - 17 Aug 2018
Event	2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) - Boise, United States Duration: 24 Jun 2018 → 28 Jun 2018

Conference

Conference	2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)
Abbreviated title	PMAPS
Country/Territory	United States
City	Boise
Period	24/06/18 → 28/06/18

Keywords

Analytical probabilistic load flow
Case study
Computational efficiency
Transmission network
Uncertainty

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10.1109/PMAPS.2018.8440326

Cite this

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title = "A linearized probabilistic load flow method to deal with uncertainties in transmission networks",

abstract = "Increasing decentralized solar and wind power production, introduces uncertainty in the electricity network and especially at the interface between transmission and distribution network. Analytical probabilistic load flow methods provide a way to incorporate uncertainty in the load flow equation, retaining acceptable accuracy without requiring significant computational power. However, the assumption that is commonly adopted is that the uncertain variables are normally distributed. The integration of wind and solar power may lead to the deprecation of the normality assumption. By comparing different distributions describing nodal powers on a standard test network, this paper assesses the usability of first order Taylor approximation to incorporate uncertainty in load flow equations in comparison with a Monte-Carlo based probabilistic load flow.",

keywords = "Analytical probabilistic load flow, Case study, Computational efficiency, Transmission network, Uncertainty",

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Reinders, J, Paterakis, N , Morren, J & Slootweg, JG 2018, A linearized probabilistic load flow method to deal with uncertainties in transmission networks. in 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)., 8440326, Institute of Electrical and Electronics Engineers, Piscataway, 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) , Boise, Idaho, United States, 24/06/18. https://doi.org/10.1109/PMAPS.2018.8440326

A linearized probabilistic load flow method to deal with uncertainties in transmission networks. / Reinders, J.; Paterakis, N.; Morren, J. et al.
2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). Piscataway: Institute of Electrical and Electronics Engineers, 2018. 8440326.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Morren, J.

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Y1 - 2018/8/17

N2 - Increasing decentralized solar and wind power production, introduces uncertainty in the electricity network and especially at the interface between transmission and distribution network. Analytical probabilistic load flow methods provide a way to incorporate uncertainty in the load flow equation, retaining acceptable accuracy without requiring significant computational power. However, the assumption that is commonly adopted is that the uncertain variables are normally distributed. The integration of wind and solar power may lead to the deprecation of the normality assumption. By comparing different distributions describing nodal powers on a standard test network, this paper assesses the usability of first order Taylor approximation to incorporate uncertainty in load flow equations in comparison with a Monte-Carlo based probabilistic load flow.

AB - Increasing decentralized solar and wind power production, introduces uncertainty in the electricity network and especially at the interface between transmission and distribution network. Analytical probabilistic load flow methods provide a way to incorporate uncertainty in the load flow equation, retaining acceptable accuracy without requiring significant computational power. However, the assumption that is commonly adopted is that the uncertain variables are normally distributed. The integration of wind and solar power may lead to the deprecation of the normality assumption. By comparing different distributions describing nodal powers on a standard test network, this paper assesses the usability of first order Taylor approximation to incorporate uncertainty in load flow equations in comparison with a Monte-Carlo based probabilistic load flow.

KW - Analytical probabilistic load flow

KW - Case study

KW - Computational efficiency

KW - Transmission network

KW - Uncertainty

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BT - 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)

PB - Institute of Electrical and Electronics Engineers

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Y2 - 24 June 2018 through 28 June 2018

ER -

A linearized probabilistic load flow method to deal with uncertainties in transmission networks

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Keywords

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