New way to manage energy in the smart grid
Researchers at ECS-Electronics and Computer Science have developed a mechanism which uses smart computerised agents to control energy storage devices in the home, resulting in energy savings of up to 16 per cent.
In a paper entitled "Decentralised Control of Micro-Storage in the Smart Grid", which will be delivered at the Twenty-Fifth Conference on Artificial Intelligence (AAAI-11) in San Francisco on Thursday (11 August), Dr Thomas Voice describes how he and his colleagues developed a novel decentralised control mechanism to manage micro-storage in the smart grid.
The researchers developed a completely decentralised mechanism which uses agent-based techniques to allow energy suppliers to manage the demand from their consumers, which, in turn, allows them to reduce their wholesale purchasing costs, yielding savings of up to 16 per cent in energy cost for consumers using devices with an average capacity of 10 kWh.
The researchers’ approach involves using a real-time pricing scheme that is broadcast to consumers in advance of each daily period. Computerised agents then buy, sell, and store energy on behalf of the home-owners in order to minimise their net electricity costs. By adjusting the pricing scheme to match the conditions on the wholesale market, the supplier is able to ensure that, as a whole, consumer agents converge to a stable and efficient equilibrium where costs and carbon emissions are minimised.
“In this paper, we propose a novel algorithm for the decentralised control of widespread micro-storage in the smart grid,” said Dr Voice. “We see this as an important step to showing that the adoption of widespread, supplier-managed home energy micro-storage is a practical desirable technology to develop for the benefit of both suppliers and consumers. Using the techniques described in this paper, we can envisage energy suppliers providing new tariffs that will incentivise consumers to buy affordable small scale storage devices. In turn this will allow suppliers to manage aggregate load profiles, improve efficiency and reduce carbon output.”
This work as carried out as part of the industrially-funded IDEAS project, led by Dr Alex Rogers and Professor Nick Jennings of the Agents, Interaction and Complexity research group at ECS, University of Southampton.