A Study on the Optimization of the Blades of Variable-Speed Small Horizontal-Axis Wind Turbines

In order to reduce the production costs, the blades of small variable-speed horizontal axis wind turbines are made of polymer with fiber glass or fiber carbon added by mold injection. Due to the limitation of the 8 mm maximum thickness for mold injection pieces, relatively thin airfoil sections have to be used near blade root. The blades in this configuration are sensitive to the stall incident angle and can operate only in a narrow range of tip-speed-ratio (TSR). Although the peak power coefficient, CP, is high, the maximum rotor speed is low, which limits the output of the rotor. Present remedy for this is reducing the range of blade twist, which reduces the peak CP and enlarges the operation range of TSR at the same time. Another problem of blade design is the long chord length of the airfoil sections near blade root in accordance with the blade strength principle that chord length should be inversely proportional to the radius. The lengthy chord contributes only to the weight of the blade but not effectively to the power output. Most blade designers adapt a particular linear function to approximate the inverse proportion of the radius. However, the choices of the profile of twist angle or chord length should be accordance with some optimal solutions of an optimization process. In this plan, we propose to find the Pareto optimal solution to the multi-objective optimization problem. In the solution process, we intend to use the efficient particle swarm optimization (PSO) method to find the optimal design factors. With the optimal design factors, we design and fabricate the blades and test them in a test bench for comparison to and verification of the optimal blade. The measured maximum power coefficient of the optimal blade is only 55% of that predicted by theoretical analysis. Therefore, we change the factors for optimization and do the optimization to generate the second-generation blade. The result shows that the maximum power coefficient of the second blade reaches 85% of that predicted by theoretical analysis. This means the design factor set chosen for the second-generation blade is a better choice for the global optimization of blade performance.

Project ID:PB10408-5754
External Project ID:MOST104-2221-E182-070