Renewable energy plants, such as wind and solar panels farms, otherwise known as small and distributed energy resources (DERs), have sprouted all across the world and are becoming an integral part of the electricity supply network (i.e. grid). Both electricity providers and consumers expect a continual electricity supply whenever they need it, and it is this fluctuation in demand combined with fluctuation in supply that is seen by many as a hurdle that must become overcome before renewable energy becomes more widespread. Researchers from the University of Southampton in the United Kingdom have devised a novel method for forming virtual power plants to provide renewable energy production in the country.
Power suppliers provide an estimate of their production and their confidence in meeting that estimate to ensure that energy demand is met without interruptions. Based on the confidence placed on the estimates, the grid is able to choose the appropriate number of conventional generators needed to produce and supply energy whenever it is needed. The grid is better able to schedule its activities the more accurate the estimates are, and the higher the confidence placed in those estimates. However, the uncertainty of renewable energy sources prevents individual DERs from profitably dealing with the grid directly, or participating in the wholesale electricity market because they are often unable to meet the set generation targets.
As a result, virtual power plants (VPPs) are fast emerging as a suitable means of integrating DERs into the grid. These are formed through the aggregation of a large number of such DERs, enabling them to reach similar size and supply reliability as conventional power plants.
In their study, the University of Southampton researchers promoted the formation of such 'cooperative' VPPs (CVPPs) using intelligent and multi-agent software systems. In particular, they designed a payment mechanism that encourages DERs to join CVPPs with large overall production.
Dr Valentin Robu, from the University's Agents, Interaction and Complexity Research Group, said: 'There is considerable talk about how to integrate a large number of small, renewable sources into the grid in a more efficient and cost effective way, as current feed in tariffs, that simply reward production are expensive and ineffective. 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.'
Through the use of 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.
The researchers devised a scoring rules-based payment mechanism that incentivises the provision of accurate predictions from the CVPPs, and through them the member DERs. They hope this will aid in the planning of the supply schedule at the grid.
'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,' said Dr Robu. '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.'