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VIRTUAL STORAGE

Demand management is a form of ‘virtual storage’. Shifting a large load from one time to a later time has the same effect on an electricity network as using a large battery to store excess power and deliver that power at a later time.

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The goal of this subtheme is to develop a cost-effective way to use a virtual energy storage system (i.e. grid loads with flexible demand) that is as reliable and responsive as a large fleet of batteries, based on five objectives: develop models for a virtual energy storage system via local intelligence, which can ensure customers’ comfort constraints, while simultaneously providing reliable service to the grid; estimate real-time virtual energy storage system capacity as a function of customer comfort constraints; reveal cost and customer comfort trade-off curves for creation of market incentives for consumer engagement; propose local robust control at each virtual energy storage system as part of an overall distributed control architecture; and build prototype hardware for validation. ​

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FLEXIBLE DEMAND AS A VIRTUAL ENERGY STORAGE SYSTEM

The goal of this subtheme is to develop a cost-effective way to use a virtual energy storage system (i.e. grid loads with flexible demand) that is as reliable and responsive as a large fleet of batteries, based on five objectives:

  1. develop models for a virtual energy storage system via local intelligence, which can ensure customers’ comfort constraints, while simultaneously providing reliable service to the grid;

  2. estimate real-time virtual energy storage system capacity as a function of customer comfort constraints;

  3. reveal cost and customer comfort trade-off curves for creation of market incentives for consumer engagement;

  4. propose local robust control at each virtual energy storage system as part of an overall distributed control architecture; and

  5. build prototype hardware for validation.

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PROF JIE BAO

Theme Leader

Professor Jie Bao is a Process Control expert, particularly in dissipativity/passivity based process control. He leads the Process Control Research Group, School of Chemical Engineering.

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