dc.contributor.author |
Hassell Sweatman, Catherine Zoe Wollaston |
|
dc.contributor.author |
Wichitaksorn, N |
|
dc.contributor.author |
Jiang, A |
|
dc.contributor.author |
Farrell, Troy |
|
dc.contributor.author |
Bootland, N |
|
dc.contributor.author |
Miskell, G |
|
dc.contributor.author |
Pritchard, G |
|
dc.contributor.author |
Chrystall, C |
|
dc.contributor.author |
Robinson, G |
|
dc.date.accessioned |
2021-05-24T02:05:47Z |
|
dc.date.available |
2021-05-24T02:05:47Z |
|
dc.date.issued |
2020-6-25 |
|
dc.identifier.citation |
ANZIAM Journal 60:m1-m40 25 Jun 2020 |
|
dc.identifier.issn |
1446-1811 |
|
dc.identifier.uri |
https://hdl.handle.net/2292/55130 |
|
dc.description.abstract |
<jats:p>With limited data beyond the grid exit point (GXP) or substation level, how can Transpower determine the effect of the aggregated behaviour of solar photovoltaic power generation and battery energy storage systems on GXP load in order to maintain an accurate load forecast? In this initial study it is assumed that the GXP services a residential region. An algorithm based on non-linear programming, which minimises the financial cost to the consumer, is developed to model consumer behaviour. Input data comprises forecast energy requirements (load), solar irradiance, and pricing. Output includes both the load drawn from the grid and power returned to the grid. The algorithm presented is at the household level. The next step would be to combine the load drawn from the grid and the power returned to the grid from all the households serviced by a GXP, enabling Transpower to make load predictions. Various means of load forecasting are considered including the Holt--Winters methods which perform well for out-of-sample forecasts. Linear regression, which takes into account comparable days, solar radiation, and air temperature, yields even better performance. </jats:p> |
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dc.publisher |
Australian Mathematical Publishing Association, Inc. |
|
dc.relation.ispartofseries |
ANZIAM Journal |
|
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
|
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
|
dc.rights.uri |
https://journal.austms.org.au/ojs/index.php/ANZIAMJ/about |
|
dc.subject |
01 Mathematical Sciences |
|
dc.subject |
09 Engineering |
|
dc.title |
Challenge from Transpower: Determining the effect of the aggregated behaviour of solar photovoltaic power generation and battery energy storage systems on grid exit point load in order to maintain an accurate load forecast |
|
dc.type |
Journal Article |
|
dc.identifier.doi |
10.21914/anziamj.v60i0.14619 |
|
pubs.begin-page |
m1 |
|
pubs.volume |
60 |
|
dc.date.updated |
2021-04-19T22:18:18Z |
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dc.rights.holder |
Copyright: Australian Mathematical Society |
en |
pubs.end-page |
m40 |
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pubs.publication-status |
Published online |
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dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |
pubs.elements-id |
848096 |
|
dc.identifier.eissn |
1445-8810 |
|
pubs.online-publication-date |
2020-6-25 |
|