Multicriteria analysis for the site selection of hydrokinetic turbines-HKT for renewable energy generation: A case study in Ecuador

Abstract

Identifying optimal sites for the deployment of hydrokinetic turbines (HKTs) is crucial to maximize renewable energy generation while ensuring environmental sustainability. This study proposes a methodology based on Multi-Criteria Decision Analysis (MCDA) integrated with Geographic Information Systems (GIS) to assess the suitability of the site for the installation of HKT. The approach considers hydrological, environmental, infrastructural, and socioeconomic factors, weighted using the analytical hierarchy process to generate spatial suitability maps. The methodology is validated through a case study in Ecuador, using its extensive river networks to identify promising locations for HKT projects. The analysis highlights dozens of high-potential sites, assessed through GIS spatial modeling and energy estimation. A comparative evaluation of energy output at two selected sites, Río Esmeraldas and Río Napo, demonstrates the feasibility and effectiveness of hydrokinetic energy exploitation in Ecuador. To validate the selected sites, high-resolution satellite imagery was used to confirm compliance with all predefined criteria and restrictions, providing a practical verification method in the absence of detailed on-site measurements. The estimated annual energy generation potential for the selected sites is approximately 1.25 GWh for Río Esmeraldas and 1.08 GWh for Río Napo, demonstrating the viability of HKT implementation in Ecuador’s riverine environments. Despite the effectiveness of the proposed approach, certain limitations must be acknowledged, including the resolution of available geospatial datasets, the lack of in situ flow velocity measurements, and the absence of detailed economic feasibility evaluations. Future research should focus on refining the methodology by incorporating real-time hydrological monitoring and exploring hybrid renewable energy solutions. The results confirm that GIS-based MCDA provides a scalable and data-driven decision support tool for researchers, policymakers, and industry stakeholders, facilitating strategic planning of renewable energy and accelerating the transition to sustainable power generation.