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Grant Award View - GA2023-V1
Machine vision techniques for solar power forecasting and generation
GA ID:
GA2023-V1
Agency:
Australian Research Council
Approval Date:
10-Nov-2017
Variation Publish Date:
26-Jul-2019
Variation Date:
26-Jul-2019
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
10-Apr-2018 to 10-Apr-2021
Value (AUD):
$368,446.00
(GST inclusive where applicable)
Varies:
GA2023
- Machine vision techniques for solar power forecasting and generation
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 17/18 Discovery
Grant Program:
Discovery Early Career Researcher Award
Grant Activity:
Machine vision techniques for solar power forecasting and generation
Purpose:
This project aims to advance the research in short-term solar power forecasting and optimise the generation process using machine vision techniques. This project will use cameras to capture images of sky and mirror surfaces of heliostats. The scientific novelties are the exploration of geometry-aware feature representations for solar power prediction and building three-dimensional models of mirror surfaces of heliostats to optimise the solar power generation process. The outcome is a working prototype to boost the solar power forecasting accuracy and a three-dimensional reconstruction system to be helpful for the solar power generation. These outcomes will highly benefit the short-term solar power forecasting, generation and electricity grid management systems.
Internal Reference ID:
DE18 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
The Australian National University
Recipient ABN:
52 234 063 906
Grant Recipient Location
Suburb:
ACTON
Town/City:
ACTON
Postcode:
2601
State/Territory:
ACT
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
ACT
Postcode:
2601
Country:
AUSTRALIA