student profile: Mr Rui Tang


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Thesis work

Thesis title: Optimisation of Battery Storage with PV Systems

Supervisors: Anthony VASSALLO , Philip Heng Wai LEONG

Thesis abstract:

The main purpose of this research would be performing data mining on real-time measurements of PV and battery systems and then building sophisticated machine learning models for battery customers. Machine learning has the ability to automatically produce accurate prediction models to guide better future actions and discover hidden patterns by learning from the new data feed. Hence, by applying machine learning methods in the optimisation, potentially we could build the analytic model that can learn from customer’s consumption and generation data and automatically make smart decisions to optimise the values to the grid and end-consumers. To further improve the optimisation results, the optimisation model will also make use of the solar and consumption forecasts by incorporating forecasted data as one of the inputs.�br /� This project will be supported by Solar Analytics, the largest independent solar monitoring company in Australia. Solar Analytics will not only provide the actual data from PV and battery systems, but also the opportunity to work with Solar Analytics engineering team and customer engagement team to make sure the research outcomes can be supported by appropriate hardware and will suit the demands and needs of solar and battery customers. �br /�

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