Demand-Side Management Optimization Using Genetic Algorithms: A Case Study
Lauro Correa dos Santos, Jonathan Muñoz Tabora, Josivan R. Reis, Vinícius Andrade, Carminda Célia Moura de Moura Carvalho, Allan R. A. Manito, Maria Emília de Lima Tostes, Edson Ortiz de Matos, Ubiratan Holanda Bezerra
Abstract
This paper addresses the optimization of contracted electricity demand (CD) for commercial and industrial entities, focusing on cost reduction within the Brazilian time-of-use electricity tariff scheme. Leveraging genetic algorithms (GAs), this study proposes a practical approach to determining the optimal CD profile, considering the complex dynamics of energy demand on a city-like load. The methodology is applied to a case study at the Federal University of Pará, Brazil, where energy efficiency and demand response initiatives as well as renewable energy projects are underway. The findings highlight the significance of tailored demand management strategies in achieving energy-related cost reduction for large-scale consumers, with implications for economic efficiency in energy consumption.