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Bakker, V. and Molderink, A. and Hurink, J.L. and Smit, G.J.M.
(2008)
Using heat demand prediction to optimise Virtual Power Plant production capacity.
In: Proceedings of the Nineteenth Annual Workshop on Circuits, Systems ans Signal Processing (ProRISC), 27-28 November 2008, Velthoven.
pp. 11-15.
Technology Foundation STW.
ISBN 978-90-73461-56-7
Full text available as:
 AbstractIn the coming decade a strong trend towards distributed electricity generation (microgeneration) is expected. Micro-generators are small appliances that generate electricity (and heat) at the kilowatt level, which allows them to be installed in households. By combining a group of micro-generators, a Virtual Power Plant can be formed. The electricity market/network requires a VPP control system to be fast, scalable and reliable. It should be able to adjust the production quickly, handle in the order of millions of micro-generators and it should ensure the required production is really produced by the fleet of microgenerators. When using micro Combined Heat and Power microgenerators, the electricity production is determined by heat demand. In this paper we propose a VPP control system design using learning systems to maximise the economical benefits of the microCHP appliances. Furthermore, ways to test our design are
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