OPTIMAL SELECTION AND DESIGN OF SMALL HYDROPOWER PROJECTS

Abstract

The number of small hydropower projects (SHP) worldwide has grown mul- tiple folds over the past few years. To support continued growth, reliable tools are needed for proper SHP selection and prioritization. A model was developed to identify optimal SHP along a given river reach based on a greedy genetic algorithm that maximizes net annual benefit. For each project, the model determines intake location, penstock diameter and length, and turbine number and capacity. Model performance was assessed through application to the Mamquam River in Canada and the Guder River in Ethiopia. The better performance of the optimization model in this study is attributed to the following model features: 1) the freedom to select intakes at any location along a river reach and not at specified intervals, and 2) the ability to select the appropriate number of turbines up to a specified maximum number. The model also runs efficiently and achieves relatively short runtimes by relying on separate optimization modules and parallel execution.