Sustainable multi-objective optimization problem for environmental impact and electricity production analysis of dams

Abstract In this paper, we develop a multi-objective optimization framework that employs a variant of the Multi-Objective Particle Swarm Optimizer (MOPSO) to balance the competing objectives represented by the total electricity generation and the reduction of carbon emissions, due to the construction of dams. This challenge highlights two conflicting aspects in the context of climate change and sustainability: on the one hand, hydropower represents a renewable energy source; on the other hand, the construction of dams leads to large greenhouse gas emissions. We analyse a dataset of 509 dams in the Amazon basin, categorized by geographical and technical features, to assess the impact of site selection. We further inspect the key features of dams that compose the best configurations to maximize energy output while minimizing emissions. The results show that, in such configurations, the most efficient dams are located in the upland zones of Peru, while inefficient dams are located on Brazilian territory, whose geographic conformation allows the construction of only downland dams that have a greater environmental impact due to a larger reservoir to satisfy a determined energy need. Finally, it seems that some existing dams are completely inefficient from the optimization viewpoint.