Abstract
As we move forward within the 21st century, global energy consumption is rising to record levels. Low-head hydropower is defined as the recovery of energy from stream flow with heads typically less than 20 m and is a clean and renewable energy source with a low impact on the environment and low carbon emission. Although significant research has focused on the construction of run of the river and low head hydroelectric installations using conventional methods such as concrete dams, there is a lack of information about best practices for siting alternative hydropower installations. A typical approach to estimating project costs requires detailed assessments of the size and the layout of the required structures and involves a fair amount of pre-evaluation of each site in order for the proper inputs to be evaluated and effective estimates of levelized cost of energy to be generated. Utilizing this approach as a screening tool for a large number of sites may prove to be costly and ineffective. In this thesis, an alternative method is developed, specifically for a modular low head hydropower system, utilizing a regression technique to approximate the results of a full cost analysis using basic hydrographic and geographic inputs. The resulting regressions are then used to quickly screen a large database of potential sites and identify those for which the modular approach would be most advantageous.