"CVPPs that together have a higher total production and, crucially, can average out prediction errors is a promising solution, which does not require expensive additional infrastructure, just intelligent incentives."By using a mathematical technique called proper scoring rules (a scoring rule, is a measure of the performance of an entity, be it person or machine, which repeatedly makes decisions under uncertainty), intelligent software agents, representing the individual DERs, are incentivised to report accurate estimates of their electricity production.
Valentin adds: "Scoring rules with specific incentive properties have long been used to design payment mechanisms that incentivise agents to report private probabilistic predictions truthfully and to the best of their forecasting abilities. "We show that our mechanism incentivises real DERs to form CVPPs, and outperforms the current state of the art payment mechanism developed for this problem."
The researchers collected half-hourly wind-speed data for a 10-week period from 16 commercial wind farms in the UK in order to validate their approach. They will be presenting their paper at the AAAI conference (22-26 July), in Toronto, Canada this week.
The Southampton researchers have been exploring these ideas for some time through the iDEaS project, an industrially-funded project, which aims to explore the issues associated with the decentralised control, operation and management of future generation electricity networks. The other members of the research team are Dr Ramachandra Kota and Dr Georgios Chalkiadakis. The project is led by Dr Alex Rogers and Professor Nick Jennings from Electronics and Computer Science at the University of Southampton. http://www.ideasproject.info/
Glenn Harris | EurekAlert!
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