Abstract
In 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
described.
Original language | Undefined |
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Title of host publication | Proceedings of the Nineteenth Annual Workshop on Circuits, Systems ans Signal Processing (ProRISC) |
Place of Publication | Utrecht |
Publisher | Technology Foundation |
Pages | 11-15 |
Number of pages | 5 |
ISBN (Print) | 978-90-73461-56-7 |
Publication status | Published - 27 Nov 2008 |
Event | 19th Annual Workshop on Circuits, Systems and Signal Processing, ProRISC 2008 - Veldhoven, Netherlands Duration: 27 Nov 2008 → 28 Nov 2008 Conference number: 19 |
Publication series
Name | |
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Publisher | STW Technology Foundation |
Number | 2008/16200 |
Conference
Conference | 19th Annual Workshop on Circuits, Systems and Signal Processing, ProRISC 2008 |
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Country/Territory | Netherlands |
City | Veldhoven |
Period | 27/11/08 → 28/11/08 |
Keywords
- EWI-14764
- Artificial Neural Networks
- Distributed Generation
- METIS-255063
- IR-65257
- Algorithm design
- Weather Sensitive Short-term Load Forecasting