Comparison of blade optimisation strategies for the IEA 15MW reference turbine

Abstract

Reference wind turbine models are crucial for enabling the research community to advance technology and meet the challenges associated with upscaling. The IEA 15 MW is one such reference model, designed using NREL’s WISDEM tool, which enables researchers to perform system-level analysis and optimisation. However, the authors have found the blade to be structurally infeasible when subject to aero-servo-elastic simulations and finite-element (FE) analyses. Given the shortcomings, this work aims to develop an updated blade model for the 15 MW turbine platform using the design tool Aeroelastic Turbine Optimisation Methods (ATOM). Two optimisation processes, with a comprehensive suite of feasibility constraints, are applied: 1) a frozen-loads mass minimisation with fixed planform, and 2) an aero-servo-structural levelised cost of energy (LCoE) minimisation. Results show the frozen-loads optimised design results in a 0.93% increase in LCoE due to the mass penalty of attaining feasibility. In contrast, the aero-structural optimised design results in a 2.29% reduction in LCoE due to mass reductions and increased energy capture—highlighting the benefits of an integrated design process. FE shell analysis of the optimised blades indicates the strength predictions in ATOM are accurate and the main load-bearing spar caps are optimally utilised. Whilst an improvement on the baseline, buckling load factors do not satisfy the target values, indicating the lower fidelity checks in ATOM are non-conservative. The WindIO yaml files for these optimised designs are freely available online.

Lifecycle Assessment of Strategies for Decarbonising Wind Blade Recycling toward Net Zero 2050

“…The design for the GF/CF hybrid WTB used in this work has been developed from the International Energy Agency (IEA) 15 MW reference wind turbine [29], developed as part of the IEA Wind Task 37 by NREL and Technical University of Denmark (DTU). Due to buckling and aeroelastic stability issues of this specific blade design (identified in a thorough analysis performed in [30]), a new round of calculations has been conducted, and an optimised blade design achieved, satisfying all the problematic constraints. The design calculations as well as main characteristics of this blade can be found in [30].…”

“…Due to buckling and aeroelastic stability issues of this specific blade design (identified in a thorough analysis performed in [30]), a new round of calculations has been conducted, and an optimised blade design achieved, satisfying all the problematic constraints. The design calculations as well as main characteristics of this blade can be found in [30]. The normalised bill of materials for the GF WTB and GF/CF hybrid WTB designs is given in Table 3.…”

A strategic approach to wind turbine blade recycling: Using life cycle assessment to enable data driven decision making

“…The design for the GF/CF hybrid WTB used in this work was developed from the IEA 15 MW reference wind turbine [8] developed as part of the IEA Wind Task 37 by NREL and Technical University of Denmark (DTU). Due to buckling and aeroelastic stability issues of this specific blade design (identified in a thorough analysis performed in [9]), a new round of calculations was conducted, and an optimised blade design was achieved satisfying all the problematic constraints. The design calculations as well as main characteristics of this blade can be found in [9].…”

“…Due to buckling and aeroelastic stability issues of this specific blade design (identified in a thorough analysis performed in [9]), a new round of calculations was conducted, and an optimised blade design was achieved satisfying all the problematic constraints. The design calculations as well as main characteristics of this blade can be found in [9].…”

Multi-material and thickness optimization of a wind turbine blade root section

“…It is therefore relevant to attempt including both disciplines in optimization to minimize post-optimization modifications and several works have shown the potential of carrying this out. Such optimization has been performed using either a coupled (Bottasso et al, 2012;Scott et al, 2020) or de-coupled (Bottasso et al, 2016;Scott et al, 2022;Mangano et al, 2022) workflow. It should be noted, that including aerodynamic considerations in the optimization problem increases the computational cost associated with analysis and computation of sensitivities.…”