Application of Multi-Objective Genetic Algorithms to Two Case Studies of Reliability Efficiency Analysis and Optimal Expansion of Electrical Transmission Networks

F. Cadini (1) , Enrico Zio (2) , L. R. Golea (1) , C. A. Petrescu (1)

1 Dipartimento di Energia [Milano]
2 SSEC - Chaire Sciences des Systèmes et Défis Energétiques EDF/ECP/Supélec

Two applications of multi-objective genetic algorithms to the analysis and optimization of electrical transmission networks are reported to show the potential of these combinatorial optimization schemes in the treatment of highly interconnected, complex systems. In a first case study, an analysis of the topological structure of an electrical power transmission system in the literature is carried out to identify the most important groups of elements of different sizes in the network. The importance is quantified in terms of group closeness centrality. In the second case study, an optimization method is developed for identifying strategies of expansion of an electrical transmission network by addition of new lines of connection which are optimally identified with respect to the objective of improving the transmission reliability, while limiting the investment cost.

Keywords: critical infrastructures; reliability efficiency; group closeness centrality measure; multi-objective genetic algorithms

Domains: Engineering Sciences [physics]; Other

F. Cadini, Enrico Zio, L. R. Golea, C. A. Petrescu. Application of Multi-Objective Genetic Algorithms to Two Case Studies of Reliability Efficiency Analysis and Optimal Expansion of Electrical Transmission Networks. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2011, 225 (3), pp.365-374. ⟨10.1177/1748006XJRR320⟩. ⟨hal-00609657⟩