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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Kirkmorris, Euan
Office of Gas and Electricity Markets
in Cooperation with on an Cooperation-Score of 37%
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report
A plug and play artificial intelligent architecture for smart local energy systems integration
Abstract
For smart local energy systems (SLES) to be truly 'smart' they must be capable of managing complex interactions between data, users and the physical devices which make up the network, while also meeting the key criteria of flexibility, scalability, and reusability.<br/> <br/>To investigate the potential for Plug and Play Artificial Intelligence techniques to help in meeting these aims, a Multi-Agent Systems approach was taken to facilitate the trading of energy between a range of simulated SLES units. This solution was successfully deployed on top of the existing control system for each of these units.<br/> <br/>The testing results look promising, with multi-agent systems being a good fit for the implementation of SLES functionality.