Using AI and a hybrid ESS solution to fully integrate solar generation into the distribution system

R&D Focus Areas:
Advanced manufacturing, Technology integration process improvement, Computational modelling

Lead Organisation:
Providence Investment Management Pty Ltd

Partners:
University of Technology Sydney, Queensland Electricity Transmission Corporation Limited, Risen Energy (Australia) Pty Ltd, University of New South Wales, Tongyu Heavy Industy Co. Ltd, Diamond Genest Pty Ltd, CSIRO, Sungrow Australia Group Pty Ltd, H2store Pty Ltd.

Status:
Completed

Start date:
September 2019

Completion date:
August 2022

Key contacts:
Professor Guandong Xu: guandong.xu@uts.edu.au

Funding:
CRC Projects

Project total cost:
AUD$3,000,000

Project summary description:
By 2020, Australia’s solar capacity is expected to double: but to be a predictable source of energy for the grid, solar power needs to be dispatchable—able to adjust output according to demand. This project will create solar farms with advanced energy storage—a hybrid of lithium batteries and hydrogen fuel cells, with DC loss detection technology. Combined with artificial intelligence to predict generation and demand, the project will deliver cost-effective and world-class energy efficiency.

Related publications and key links:
Dhruv Aditya Mittal, Shaowu Liu, Guandong Xu: Electricity Price Forecasting using Convolution and LSTM Models BESC 2020, Bournemouth, United Kingdom, DOI: 10.1109/BESC51023.2020.9348313

Higher degree studies supported:
One PhD student at University of Technology Sydney was supported by this project.

 

October 2022