A Cloud-Based Decision Support System Framework for Hydropower Biological Evaluation

Hydropower is one of the most important energy sources: it accounts for more than 80% of the world's renewable electricity and 16% of the world's electricity. Significantly more hydropower capacity is planned to be developed. However, hydro-structures, including hydroelectric dams, may have adverse biological effects on fish, especially on migratory species. For instance, fish can be injured or even killed when they pass through turbines. This is why biological evaluations on hydro-structures are needed to estimate fish injury and mortality rates. The Hydropower Biological Evaluation Toolset (HBET) is an integrated suite of science-based desktop tools designed to evaluate whether the hydraulic conditions of hydropower structures are fish friendly by analyzing collected data and providing estimated injury and mortality rates. The Sensor Fish, a small autonomous sensor package, is used by HBET to record data describing the conditions that live fish passing through a hydropower structure will experience. In this paper, we present a plan to incorporate cloud computing into HBET, and migrate into a cloud-based decision support system framework for hydropower biological evaluation. These enhancements will make the evaluation system more scalable and flexible; however, they will also introduce a significant challenge: how to maintain security while retaining scalability and flexibility. We discuss the technical methodologies and algorithms for the proposed framework, and analyze the relevant security issues and associated security countermeasures.