Otimização de padrões para projetos de Iluminação Pública utilizando Python

Abstract

Among the documents that make up the Procel Reluz Public Calls street lighting projects, it is essential to include the electronic file, From the data entered, there is the possibility of forming street standardized models, merging streets with the same characteristics, decreasing the number of lighting projects. Although the streets rarely have the same characteristics, they are very similar, which implies the designer’s manual work to match these characteristics. Thereby, from the criteria definition in order to match similar streets according to the requirements of Procel Reluz, this work aims to present the development of a Python script that performs the optimization of street patterns generation, and consolidate its functionality from a case study of a neighborhood in the city of Rio Branco - AC. Information was collected from 28 streets, whose data from which street were used as input to the script. After running the code, 11 street models were obtained, which represents a 60% reduction in the number of street lighting projects required to complete the retrofit. The optimized standardized street models were validated by executing all their corresponding lighting projects and their respective streets using the same luminaire series, obtaining little difference between the luminaire powers on the original scenario and the scenario with number of projects decreased by the script.