Big Data and Systemic Geo-Intelligence: Innovation in optimizing scenarios for utility companies
Resumo
What will utility operations be like in 3 years’ time? And what about 30 years from now? How many operational bases will there be and in which locations? This research studies the influence of geographic variables and optimization models on operational KPIs of AES Eletropaulo, an energy distribution company in Brazil, in its emergency response service. Different information perspectives were used (traffic, microclimate, trees, real estate, occurrences and crew movements) on an innovative spatial discretization for computational purposes. Four algorithms (Brute Force, Hillclimbing, Genetic, K-Means) were developed to simulate base composition scenarios. The results enable assessments to be carried out that support better decisions for utility companies. This is, therefore, a Big Data platform with geographical optimization that is unprecedented in the Brazilian electricity sector.