1. www.csiro.au Distributed Electrical Systems - the emergence of demand response John Ward CSIRO Energy Technology 9 August 2006

2. Distributed Electrical Systems – the emergence of demand response Introduction Background  National Electricity Market  Distributed Generation  Renewables / Cogeneration  Microgrids / robustness / resilliance  Regulatory - AS 4777 Problem Features  Agents as social proxies  time scales – transient vs long term  network is both electrical and economic  lossy  sources & sinks

3. Distributed Electrical Systems – the emergence of demand response Demand Management  Networks are increasingly constrained – particularly with widespread deployment of HVAC systems.  NOT exogenous disturbances – these are highly correlated with weather data – everyone wants AC on a hot day.  Traditional approach of peaking plants/ network augmentation yields low capacity factors Can a response from within the network provide a better solution?

4. Distributed Electrical Systems – the emergence of demand response Challenges How do we design agents that reacts individually on behalf of a consumer, but collectively on behalf of all consumers? Particular focus is on:  Learning to cooperate  Adaption to changes in network structure  The value of information / cost of communication  Decentralised control and robustness  Near optimal convergence with limited information

5. Distributed Electrical Systems – the emergence of demand response A (not very) Complex Example

6. Distributed Electrical Systems – the emergence of demand response Stability Example But with N…

7. Distributed Electrical Systems – the emergence of demand response Simulation Result

8. Distributed Electrical Systems – the emergence of demand response Conclusions Distributed Generation is happening  Cogeneration / Renewables DG has the potential to provide increased functionality and robustness to the electrical network. There are a number of complex problems that need to be addressed before this potential is realised  Learning to cooperate  Adaption to changes in network structure  The value of information / cost of communication  Decentralised control and robustness  Near optimal convergence with limited information

9. www.csiro.au Thank You CSIRO Energy Technology John Ward Research Engineer +61 2 49606072 John.K.Ward@csiro.au www.energy.csiro.au Contact CSIRO Phone1300 363 400 +61 3 9545 2176 Emailenquiries@csiro.au Webwww.csiro.au