Prediction and Optimisation for Coordinating Battery Storage

Description

Residential solar PV, battery storage and electric vehicles provide both great challenges and great opportunities for the operation of our electricity networks. It will be crucial to coordinate the operation of these distributed energy technologies (DETs) so as to not overload the network or create large voltage swings. The state-based nature of storage makes it important to predict uncontrollable behaviour and to schedule operations into the future.

There are several potential summer scholar and honours projects in this area, which will contribute to the Bruny Island battery trial conducted as part of the CONSORT project:

  • Predicting Distribution Feeder Loads
  • Managing Network Operational Uncertainty
  • Managing Lost Communications with Robust Defaults
  • Efficient Models for Voltage and Capacity Management
  • Fair Allocation of Network Costs
  • Accelerated and Primal Decomposition Methods
  • Formation of a Bruny Island Microgrid

Requirements

Programming experience will be required for all these projects. Experience in fields such as renewable energy, power systems, machine learning, optimisation and artificial intelligence will also be valuable (depending on the topic).  For students looking to do one of these topics as a summer or 4th year engineering project a D average is required, preferably HD.  Contact me for further details on these projects.

Keywords

Battery storage, smart grid, renewable energy, optimisation, machine learning, prediction

Updated:  1 June 2019/Responsible Officer:  Dean, CECS/Page Contact:  CECS Marketing