Electrical Power Grid Network Optimisation by Evolutionary Computing | Zendy

John M. Oliver | Zendy; Timoleon Kipouros | Zendy; Mark Savill | Zendy

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Electrical Power Grid Network Optimisation by Evolutionary Computing

Author(s) -

John M. Oliver,

Timoleon Kipouros,

Mark Savill

Publication year - 2014

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2014.05.179

Subject(s) - computer science , power flow , grid , distributed computing , electric power transmission , power (physics) , evolutionary algorithm , line (geometry) , electric power system , electric power , transmission network , transmission (telecommunications) , mathematical optimization , electrical engineering , artificial intelligence , telecommunications , geometry , mathematics , quantum mechanics , engineering , physics

A major factor in the consideration of an electrical power network of the scale of a national grid is the calculation of power flow and in particular, optimal power flow. This paper considers such a network, in which distributed generation is used, and examines how the network can be optimized, in terms of transmission line capacity, in order to obtain optimal or at least high-performing configurations, using multi-objective optimisation by evolutionary computing methods

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