news and events

  • iGrid Perth ForumYou can view all the presentations made at the iGrid perth forum through the Engaging Stakeholders page
  • Upcoming Forum notification iGrid Showcase: Unlocking the Potential of Distributed Energy

The next forum will be held in Brisbane at the University of Queensland, Customs House on Tuesday 31st August 2010. For further details please see the attached brochure

  • D-CODE Model now available

The Description and Cost of Distributed Energy (D-CODE) Model is a working model, designed to be transparent and accessible. We would appreciate your input in making D-CODE as useful and robust as possible. If you have comments, additional data, or feedback about D-CODE, please complete the online feedback form: D-CODE Feedback Form

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Optimal Siting

Full name
Optimal siting and dispatch of distributed generators

Description
This project investigates a range of generation technologies and their placement within the network to find the best opportunities for investment in certain technologies. Specifically, the project will use dynamic programming to guide the optimal scheduling for wind, solar, fuel cell and combustion generation given a grid-operating condition, and from there develop practical algorithms to intelligently respond to the grid requirements and customer needs.

In recent years, inverter prices have been falling and significant advances have occurred in battery technology. This means distributed generation can be more competitive with traditional generation than in the past.  Further, distributed storage can provide an attractive method of providing distributed generation support to a grid that is disrupted. One type of high-energy battery can also absorb energy off-peak and return that energy at peak times to provided enhanced network capacity.

The network studies will seek to develop tools to quantify network benefits of distributed generations such as:

reliability of supply
voltage support
harmonic reduction
dynamic stability
reduction in system losses

Research Team:
Queensland University of Technology

Expected Outcomes
Optimised siting of distributed generation to maximise reliability of distribution networks.

Better management of distributed generators to avoid or eliminate oscillation and harmful feedback.

Improved protection systems to integrate and manage islanded distributed generation supplies.

Reduced network losses and associated greenhouse gas emissions, by optimal siting of distributed resources

Controller for network-optimized performance for gas turbines and inverters.


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