optimal design of vlh axial hydro-turbine using regression analysis and multi-objective function (ga) optimization methods

This research study was aimed to develop a new concept design of a very low head (vlh) turbine using advanced optimization methodologies. a potentially local site was chosen for the turbine and based on its local conditions, such as the water head level of <2 meters and the flow rate of <5 m^3/s. the study focused on the optimization of the turbine blade and guide vane profiles, because of their major impacts on the efficiency of the vlh axial flow turbine. the fluid flow simulation was firstly conducted for the axial turbine, followed by applying the regression analysis concept to develop a turbine mathematical model where the leading- and trailing-edge angles of the guide vanes and the turbine blades were related to the efficiency, total head and flow rate. the genetic algorithms (ga) with multi-objective function was also used to locate the optimal blade angles. thereafter, the refined design was re-simulated. following this procedure the turbine efficiency was improved from 82.59% to 83.96% at a flow rate of 4.2 m^3/s and total head of 2 meters.