Optimizing Distribution Expansion Planning: Integrating SAIDI and SAIFI Indices with Genetic Algorithms.

Abstract

Distribution expansion planning is imperative for ensuring reliable electricity supply while minimizing operational costs. This paper presents a novel approach to distribution expansion planning that integrates the System Average Interruption Duration Index (SAIDI) and the System Average Interruption Frequency Index (SAIFI) with genetic algorithms (GA). By incorporating reliability indices, our methodology aims to minimize investment costs and electrical losses while adhering to accepted SAIDI and SAIFI values during the expansion of the distribution network. We enhance traditional GA techniques with strategies like elitism and variable recombination and mutation rates to improve the efficiency and effectiveness of the algorithm. The proposed methodology is applied to an 18-busbar network. Three scenarios are analyzed with different restrictions for SAIDI and SAIFI indices. The results show that it is possible to obtain an effective distribution expansion planning solution that also attends to the reliability indicators defined by the regulatory agencies, however it is necessary an increment of 18.5% on the investment costs.