A Genetic Algorithm for Distribution Expansion Planning Considering Financial Losses Due to Voltage Sags and Power Interruptions

Abstract

Distribution system planning is crucial to meet current and future electricity demands while optimizing investments. This paper introduces a novel approach to distribution expansion planning utilizing genetic algorithms (GA). The proposed methodology aims to minimize investment costs, electrical losses (CEle), and financial losses caused by voltage sags and power interruptions (CFin). To improve the GA's efficacy, we integrate techniques such as elitism and variable mutation rates. A distribution system with 18 busbars is used to demonstrate the efficiency of the GA proposed. The results show that it is possible to minimize CEle and CFin with minimal investments. The proposed methodology allows planners and operators to execute more efficient strategic planning considering the needs of the utilities and end-users at the same time.