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

Abstract

Hydropower has become one of the most important energy sources: it accounts for more than 80% of the world’s renewable energy and about 16% of all the energy in the world. Significantly more hydropower capacity is planned to be developed. However, hydro-structures, including powered dams, may have adverse biological effects on fishes, especially on migrating fish. For instance, fish can be injured or even killed when they pass through turbines. This is why biological evaluations on hydro-structures are greatly 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. 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 face. In this paper, we incorporated cloud computing into HBET, and migrated it into a cloud-based decision support system framework for hydropower biological evaluation. This will make the evaluation systems more scalable and flexible; however, this also introduces a significant challenge: how to maintain the security while retaining scalability and flexibility. We discuss the technical methodologies and algorithms implemented in the proposed framework, and analyze the countermeasures implemented therein.