ANALYSIS AND OPTIMIZATION OF POWER TRANSMISSION GRIDS BY GENETIC ALGORITHMS

Two applications of multi-objective genetic algorithms (MOGAs) are reported with regards to the analysis and optimization of electrical transmission networks. In a first case study, an analysis of the topological structure of a network system is carried out to identify the most important groups of elements of different sizes in the network. In the second case study, an optimization method is devised to improve the reliability of power transmission by adding lines to an existing electrical network. In this paper, two applications of multi-objective genetic algorithms (MOGAs) are reported with regards to the analysis and optimization of electrical transmission networks. In the first case study, Genetic Algorithms (GAs) are used within a multiobjective formulation of the search problem, in which the decision variables identify groups of components and the objectives are to maximize the importance of the groups while minimizing their dimension. In the second case study, a GA method is developed for identifying strategies of expansion of an electrical network in terms of new lines of connection to add for improving the reliability of its transmission service, while maintaining limited the investment cost. To realistically restrict the search space to small numbers of new connections, the so-called guided multi-objective genetic algorithm (G-MOGA) has been applied. In this approach, the search is based on the guided domination principle which allows to change the shape of the dominance region specifying maximal and minimal trade-offs between the different objectives so as to efficiently guide the MOGA towards Pareto-optimal solutions within these boundaries (Zio et al. 2009). The paper is organized as follows. Section 2 presents the group closeness centrality measure which can be used to quantify the importance of groups of nodes. The concept of network global reliability efficiency is also presented. In Section 3 and Section 4, the case studies regarding the IEEE 14 BUS network system (Christie 1993) and IEEE RTS 96 (Billinton & Li 1994) are presented and solved by MOGA. Conclusions on the outcomes of the analysis are eventually drawn in Section 5.