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Probabilistic dynamic cable rating algorithms

Probabilistic dynamic cable rating algorithms
Probabilistic dynamic cable rating algorithms
Offshore wind farm (WF) power cables are often sized using static rating calculations as is traditionally done with cables on land. However, in practice wind farm export cables face intermittent generation product of wind speed variations which along with the relatively long thermal transients in the cable generate low cable temperatures. As a consequence, offshore cables rating capabilities are often under-utilized. Wind farm over-planting (WFO) has became a common practice to optimise offshore cable utilisation by increasing the installed generation capacity over the static rating limits. However, in order to avoid unnecessary power curtailment, it is necessary to have knowledge of the actual and likely future temperatures that the cable could attain. The use of real-time thermal rating (RTTR) methodologies is seen in the literature as an alternative to static rating calculations in conventional installations. Nonetheless, the use of RTTR is not enough to optimise curtailment decisions in offshore WFs as information of future load current scenarios and conductor temperatures is needed hours in advance.

The present research was focused on the development of probabilistic algorithms for the hours ahead estimation of future load currents, cable temperatures and estimation of likely risk of cable overheating. The proposed algorithms are based on a limited amount of historical offshore data which is statistically analysed to extract seasonal behaviour and patterns to perform the estimations. The proposed algorithms can be used as a tool for decision making that could help the system operators to avoid power curtailment when WFO is applied.

Further more the algorithms developed could be used as a computational tool to optimise sizing in offshore power cables for projects in which it is necessary to reduce the levelised cost of energy (LCOE). The application of the methodology can contribute to increase the power delivery and decreases the cable contribution price to the LCOE.
University of Southampton
Hernandez Colin, Maria Angelica
8f523b8a-5c1d-4742-a72b-dd94bd5afa3d
Hernandez Colin, Maria Angelica
8f523b8a-5c1d-4742-a72b-dd94bd5afa3d
Pilgrim, James
4b4f7933-1cd8-474f-bf69-39cefc376ab7

Hernandez Colin, Maria Angelica (2020) Probabilistic dynamic cable rating algorithms. University of Southampton, Doctoral Thesis, 164pp.

Record type: Thesis (Doctoral)

Abstract

Offshore wind farm (WF) power cables are often sized using static rating calculations as is traditionally done with cables on land. However, in practice wind farm export cables face intermittent generation product of wind speed variations which along with the relatively long thermal transients in the cable generate low cable temperatures. As a consequence, offshore cables rating capabilities are often under-utilized. Wind farm over-planting (WFO) has became a common practice to optimise offshore cable utilisation by increasing the installed generation capacity over the static rating limits. However, in order to avoid unnecessary power curtailment, it is necessary to have knowledge of the actual and likely future temperatures that the cable could attain. The use of real-time thermal rating (RTTR) methodologies is seen in the literature as an alternative to static rating calculations in conventional installations. Nonetheless, the use of RTTR is not enough to optimise curtailment decisions in offshore WFs as information of future load current scenarios and conductor temperatures is needed hours in advance.

The present research was focused on the development of probabilistic algorithms for the hours ahead estimation of future load currents, cable temperatures and estimation of likely risk of cable overheating. The proposed algorithms are based on a limited amount of historical offshore data which is statistically analysed to extract seasonal behaviour and patterns to perform the estimations. The proposed algorithms can be used as a tool for decision making that could help the system operators to avoid power curtailment when WFO is applied.

Further more the algorithms developed could be used as a computational tool to optimise sizing in offshore power cables for projects in which it is necessary to reduce the levelised cost of energy (LCOE). The application of the methodology can contribute to increase the power delivery and decreases the cable contribution price to the LCOE.

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Published date: January 2020

Identifiers

Local EPrints ID: 442020
URI: http://eprints.soton.ac.uk/id/eprint/442020
PURE UUID: 942e5483-fbab-4f3a-bb9a-3cfc19734d4b
ORCID for James Pilgrim: ORCID iD orcid.org/0000-0002-2444-2116

Catalogue record

Date deposited: 03 Jul 2020 16:39
Last modified: 04 Jul 2020 00:30

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