A Scalable Distributed Algorithm for Optimizing Distribution Power-Grids

Pezoa, Jorge E.; García-Santander, Luis; Cárcamo-Gallardo, Angely

doi:10.1109/sccc.2009.9

Cited by 3 publications

(1 citation statement)

References 23 publications

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“…The distribution grid reconfiguration belongs to the category of nondeterministic combinatorial optimization problems (NP-hard) [13,33]. The distribution feeder reconfiguration problem is conventionally considered a mixed-integer non linear programming problem.…”

Section: Application Of Genetic Algorithm To the Three Control Problemsmentioning

confidence: 99%

Relevance of voltage control, grid reconfiguration and adaptive protection in smart grids and genetic algorithm as an optimization tool in achieving their control objectives

Ramaswamy

Deconinck

2011

2011 International Conference on Networking, Sensing and Control

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Voltage control, grid reconfiguration and adaptive protection are considered in this paper since they are representative of the various control applications in the context of smart grids which can make significant use of the information and communication technology. All the three control applications have multiple objectives of which some are conflicting and these call for the use of multi-objective optimization in implementing the controls. The presence of non convex objectives and constraints calls for the use of evolutionary algorithms in solving the control problems. This paper enlists the generally dealt objectives and constraints for the three control applications. The presence of distributed generators in smart grids brings in factors that need additional consideration in solving the multi-objective optimization. The paper proposes that genetic algorithm is likely to be a good optimization technique in achieving the control objectives, the reasons for which are qualitatively described in this paper along with the challenges in using genetic algorithm.

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Section: Application Of Genetic Algorithm To the Three Control Problemsmentioning

confidence: 99%