Aspects of data science at Redback Technologies

#solar #smart #inverters #data
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Smart solar inverters can be used to store, monitor and manage a home’s solar energy.

We describe a smart solar inverter system with battery which can either operate in an automatic mode or receive commands over a network to charge and discharge at a given rate. In order to make battery storage financially viable and advantageous to the consumers, effective battery scheduling algorithms can be employed. Particularly, when time-of-use tariffs are in effect in the region of the inverter, it is possible in some cases to schedule the battery to save money for the individual customer, compared to the “automatic” mode.

We describe a novel battery scheduling algorithm for residential consumers of solar energy.

We also outline future research directions for the Redback Technologies Research Centre in the Network Intelligence area.

 



  Date and Time

  Location

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  Registration



  • Date: 02 Apr 2019
  • Time: 11:00 AM to 12:00 PM
  • All times are (GMT+10:00) Australia/Queensland
  • Add_To_Calendar_icon Add Event to Calendar
  • Staff House Road
  • The University of Queensland
  • Brisbane, Queensland
  • Australia 4072
  • Building: 49
  • Room Number: 502

  • Contact Event Host
  • Co-sponsored by ITEE PES Group
  • Starts 29 March 2019 10:56 AM
  • Ends 02 April 2019 10:56 AM
  • All times are (GMT+10:00) Australia/Queensland
  • No Admission Charge


  Speakers

Richard Bean of Redback Technologies

Topic:

Aspects of data science at Redback Technologies

Smart solar inverters can be used to store, monitor and manage a home’s solar energy.

We describe a smart solar inverter system with battery which can either operate in an automatic mode or receive commands over a network to charge and discharge at a given rate. In order to make battery storage financially viable and advantageous to the consumers, effective battery scheduling algorithms can be employed. Particularly, when time-of-use tariffs are in effect in the region of the inverter, it is possible in some cases to schedule the battery to save money for the individual customer, compared to the “automatic” mode.

We describe a novel battery scheduling algorithm for residential consumers of solar energy.

We also outline future research directions for the Redback Technologies Research Centre in the Network Intelligence area.

Biography:

Richard received his B. Sc. (Hons) and Ph. D. in mathematics from the University of Queensland in 1997 and 2001, respectively.

Since then, he has worked in academic research, government and industry positions in Iran and Australia. He has worked in research in combinatorics and statistics, for Queensland Health in public health research roles, and in energy market consulting (ROAM Consulting) and energy market operation (Australian Energy Market Operator). He has also performed research into bike sharing schemes with the School of Geography, Planning and Environmental Management at UQ.

Since July 2016, he has worked as a data scientist at Redback Technologies, developing algorithms for forecasting load and solar energy, and optimization techniques.