The University of Southampton
University of Southampton Institutional Repository

Offshore cable optimization by probabilistic thermal risk estimation

Offshore cable optimization by probabilistic thermal risk estimation
Offshore cable optimization by probabilistic thermal risk estimation
This paper presents a probabilistic methodology for the estimation of cable temperature exceedance 6h, 12h and 24h ahead. The use of this method with the dynamic calculation of cable temperature can enable increases in the amount of power transferred from offshore wind farm installations by estimating the likelihood of the cable exceeding its temperature limit (90°C for XLPE). The methodology is based on historical data from the offshore wind farm site and a Monte Carlo Analysis. The estimations of risk can be used as a decision tool to avoid curtailment of power generation when the load is higher than the continuous rating but the calculated risk of exceeding 90°C is acceptably low. Increments of 7%, 9.9% and 13.7% over the continuous rating of the cable are studied considering three lengths of training sets. The simulated results show that the temperature estimations are consistent with the year of testing data in as much as 98.9% of the time. The application of the proposed methodology could represent 93GWh of additional energy delivery in one year for the case mentioned above.
Hernandez Colin, Maria Angelica
8f523b8a-5c1d-4742-a72b-dd94bd5afa3d
Pilgrim, James
4b4f7933-1cd8-474f-bf69-39cefc376ab7
Hernandez Colin, Maria Angelica
8f523b8a-5c1d-4742-a72b-dd94bd5afa3d
Pilgrim, James
4b4f7933-1cd8-474f-bf69-39cefc376ab7

Hernandez Colin, Maria Angelica and Pilgrim, James (2018) Offshore cable optimization by probabilistic thermal risk estimation. Probabilistic methods applied to power systems, PMAPS 2018, , Boise, United States. 24 Jun - 30 Aug 2018. 6 pp .

Record type: Conference or Workshop Item (Paper)

Abstract

This paper presents a probabilistic methodology for the estimation of cable temperature exceedance 6h, 12h and 24h ahead. The use of this method with the dynamic calculation of cable temperature can enable increases in the amount of power transferred from offshore wind farm installations by estimating the likelihood of the cable exceeding its temperature limit (90°C for XLPE). The methodology is based on historical data from the offshore wind farm site and a Monte Carlo Analysis. The estimations of risk can be used as a decision tool to avoid curtailment of power generation when the load is higher than the continuous rating but the calculated risk of exceeding 90°C is acceptably low. Increments of 7%, 9.9% and 13.7% over the continuous rating of the cable are studied considering three lengths of training sets. The simulated results show that the temperature estimations are consistent with the year of testing data in as much as 98.9% of the time. The application of the proposed methodology could represent 93GWh of additional energy delivery in one year for the case mentioned above.

Text
PMAPS_2018MAHC - Accepted Manuscript
Restricted to Registered users only
Download (1MB)
Request a copy

More information

Published date: 25 June 2018
Venue - Dates: Probabilistic methods applied to power systems, PMAPS 2018, , Boise, United States, 2018-06-24 - 2018-08-30

Identifiers

Local EPrints ID: 422849
URI: http://eprints.soton.ac.uk/id/eprint/422849
PURE UUID: 77bec9aa-d221-43f9-9ac1-16e0d4d1b586
ORCID for James Pilgrim: ORCID iD orcid.org/0000-0002-2444-2116

Catalogue record

Date deposited: 07 Aug 2018 16:30
Last modified: 16 Mar 2024 03:49

Export record

Contributors

Author: Maria Angelica Hernandez Colin
Author: James Pilgrim ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×