Projects per year
A fully distributed intelligence and control philosophy is needed for future flexible grids to facilitate the low carbon transition and the adoption of emerging network technologies. Future grids need scalable network management solutions in order to cope with the increase in uncertainty and complexity. Fundamental research in intelligent systems and network control will deliver the next generation of intelligent electricity network. This paper presents a network management function formalised as a Distributed Constraint Optimization (DCOP) problem, in particular power flow management. DCOP is an approach to negotiation and arbitration within decentralised control systems where conflicting control decisions arise. Furthermore, the problem will be visualized and decomposed as a factor graph which is a graphical presentation of factorization of a global function into a product of local functions. Additionally, a message passing algorithm, the max-sum algorithm, will be applied which can provide almost optimal results for decentralised coordination problems and limits the computation and communication problems.
|Title of host publication||2013 IEEE Power and Energy Society General Meeting (PES)|
|Place of Publication||Piscataway, NJ.|
|Pages||1 - 5|
|Number of pages||5|
|Publication status||Published - 2013|
|Event||2013 IEEE Power and Energy Society (PES) General Meeting - Vancouver, Canada|
Duration: 22 Jul 2013 → 25 Jul 2013
|Conference||2013 IEEE Power and Energy Society (PES) General Meeting|
|Period||22/07/13 → 25/07/13|
- artificial intelligence
- factor graphs
- max-sum algorithms
- power flow management
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- 1 Finished
EPSRC Energy Networks Grand Challenge - Autonomic Power System
McArthur, S., Ault, G. & Kockar, I.
EPSRC (Engineering and Physical Sciences Research Council)
1/10/11 → 31/10/16