Katherine Dykes

Sensitivity Analysis of Wind Plant Performance to Key Turbine Design Parameters: A Systems Engineering Approach

This paper introduces the development of a new software framework for research, design, and development of wind energy systems which is meant to 1) represent a full wind plant including all physical and nonphysical assets and associated costs up to the point of grid interconnection, 2) allow use of interchangeable models of varying fidelity for different aspects of the system, and 3) support system level multidisciplinary analyses and optimizations. This paper describes the design of the overall software capability and applies it to a global sensitivity analysis of wind turbine and plant performance and cost. The analysis was performed using three different model configurations involving different levels of fidelity, which illustrate how increasing fidelity can preserve important system interactions that build up to overall system performance and cost. Analyses were performed for a reference wind plant based on the National Renewable Energy Laboratory’s 5-MW reference turbine at a mid-Atlantic offshore location within the United States. Three software configurations were used: 1) a previously published wind plant cost model using simplified parametric scaling relationships, 2) an integrated set of wind turbine and plant engineering and cost models that use a “bottom-up” approach to determine overall wind plant performance and cost metrics, and 3) the second set of models plus the addition of a plant layout and flow model for calculation of energy production. Global sensitivity analysis was performed on each analysis set with respect to key wind turbine configuration parameters including rotor diameter, rated power, hub height, and maximum tip speed. The analyses show how the latter approaches capture important coupling throughout the wind plant in a way that has not previously been achieved. In addition, while deficiencies even in the newer model set are readily identifiable, the flexibility of the new framework shows how extension and gradual buildup of model fidelity for various parts of the system provide a powerful tool that enables analysis for an ever-expanding set of wind energy research and design problems.

Understanding the Benefits and Limitations of Increasing Maximum Rotor Tip Speed for Utility-Scale Wind Turbines

For utility-scale wind turbines, the maximum rotor rotation speed is generally constrained by noise considerations. Innovations in acoustics and/or siting in remote locations may enable future wind turbine designs to operate with higher tip speeds. Wind turbines designed to take advantage of higher tip speeds are expected to be able to capture more energy and utilize lighter drivetrains because of their decreased maximum torque loads. However, the magnitude of the potential cost savings is unclear, and the potential trade-offs with rotor and tower sizing are not well understood. A multidisciplinary, system-level framework was developed to facilitate wind turbine and wind plant analysis and optimization. The rotors, nacelles, and towers of wind turbines are optimized for minimum cost of energy subject to a large number of structural, manufacturing, and transportation constraints. These optimization studies suggest that allowing for higher maximum tip speeds could result in a decrease in the cost of energy of up to 5% for land-based sites and 2% for offshore sites when using current technology. Almost all of the cost savings are attributed to the decrease in gearbox mass as a consequence of the reduced maximum rotor torque. Although there is some increased energy capture, it is very minimal (less than 0.5%). Extreme increases in tip speed are unnecessary; benefits for maximum tip speeds greater than 100-110 m/s are small to nonexistent.

Adjoint Optimization of Wind Farm Layouts for Systems Engineering Analysis

Wind is an important renewable energy resource, but in order for it to be competitive with other energy sources, wind farm layouts must be optimized to reduce the levelized cost of energy (LCOE). This requires an analysis that integrates high-fidelity flow models with physical turbine and cost models. We present a new flow model and turbine optimization tool, WindSE, that optimizes wind turbine locations and axial induction factors as part of the National Renewable Energy Laboratory’s open source wind energy systems engineering software tool WISDEM. WindSE enables gradient-based layout optimization by solving the discrete adjoint equations corresponding to the forward flow model. This provides a computationally efficient way to calculate gradients used in the optimization process. We discuss the development of WindSE and provide optimization results based on simulations of single and multiple inflow directions. In the case of strongly directional wind roses the optimal layouts take advantage of flow curvature and speedup effects that are not generated by standard industry linear flow models. When optimizing with respect to a uniform wind rose, local speedup effects are found to be less beneficial and the optimal layouts instead reduce wake losses by maximizing spacing. Sensitivity to wind direction bin sizes and weights is demonstrated with a full layout and axial induction factor optimization using a wind rose from an offshore wind farm.

Assessment of wind turbine component loads under yaw-offset conditions

Renewed interest in yaw control for wind turbine and power plants for wake redirection and load mitigation demands a clear understanding of the effects of running with skewed inflow. In this paper, we investigate the physics of yawed operations, building up the complexity from a simplified analytical treatment to more complex aeroelastic simulations. Results in terms of damage equivalent loads (DELs) and extreme loads under misaligned conditions of operation are compared to data collected from an instrumented, utility-scale wind turbine. The analysis shows that multiple factors are responsible for the DELs of the various components and that airfoil aerodynamics, elastic characteristics of the rotor, and turbulence intensities are the primary drivers. Both fatigue and extreme loads are observed to have relatively complex trends with yaw offsets, which can change depending on the wind-speed regime. Good agreement is found between predicted and measured trends for both fatigue and ultimate loads.

Optimization Under Uncertainty for Wake Steering Strategies

Wind turbines in a wind power plant experience significant power losses because of aerodynamic interactions between turbines. One control strategy to reduce these losses is known as “wake steering,” in which upstream turbines are yawed to direct wakes away from downstream turbines. Previous wake steering research has assumed perfect information, however, there can be significant uncertainty in many aspects of the problem, including wind inflow and various turbine measurements. Uncertainty has significant implications for performance of wake steering strategies. Consequently, the authors formulate and solve an optimization under uncertainty (OUU) problem for finding optimal wake steering strategies in the presence of yaw angle uncertainty. The OUU wake steering strategy is demonstrated on a two-turbine test case and on the utility-scale, offshore Princess Amalia Wind Farm. When we accounted for yaw angle uncertainty in the Princess Amalia Wind Farm case, inflow-direction-specific OUU solutions produced between 0% and 1.4% more power than the deterministically optimized steering strategies, resulting in an overall annual average improvement of 0.2%. More importantly, the deterministic optimization is expected to perform worse and with more downside risk than the OUU result when realistic uncertainty is taken into account. Additionally, the OUU solution produces fewer extreme yaw situations than the deterministic solution.

Roadmap to the multidisciplinary design analysis and optimisation of wind energy systems

A research agenda is described to further encourage the application of Multidisciplinary Design Analysis and Optimisation (MDAO) methodologies to wind energy systems. As a group of researchers closely collaborating within the International Energy Agency (IEA) Wind Task 37 for Wind Energy Systems Engineering: Integrated Research, Design and Development, we have identi_ed challenges that will be encountered by users building an MDAO framework. This roadmap comprises 17 research questions and activities recognised to belong to three research directions: model _delity, system scope and workow architecture. It is foreseen that sensible answers to all these questions will enable to more easily apply MDAO in the wind energy domain. Beyond the agenda, this work also promotes the use of systems engineering to design, analyse and optimise wind turbines and wind farms, to complement existing compartmentalised research and design paradigms.

Optimization Under Uncertainty of Site-Specific Turbine Configurations

Uncertainty affects many aspects of wind energy plant performance and cost. In this study, we explore opportunities for site-specific turbine configuration optimization that accounts for uncertainty in the wind resource. As a demonstration, a simple empirical model for wind plant cost of energy is used in an optimization under uncertainty to examine how different risk appetites affect the optimal selection of a turbine configuration for sites of different wind resource profiles. If there is unusually high uncertainty in the site wind resource, the optimal turbine configuration diverges from the deterministic case and a generally more conservative design is obtained with increasing risk aversion on the part of the designer.

A comparison study of offshore wind support structures with monopiles and jackets for U.S. waters

U.S. experience in offshore wind is limited, and high costs are expected unless innovations are introduced in one or multiple aspects of the project, from the installed technology to the balance of system (BOS). The substructure is the main single component responsible for the BOS capital expenditure (CapEx) and thus one that, if improved, could yield significant levelized cost of energy (LCOE) savings. For projects in U.S. waters, multimember lattice structures (also known as jackets) can render required stiffness for transitional water depths at potentially lower costs than monopiles (MPs). In this study, we used a systems engineering approach to evaluate the LCOE of prototypical wind power plants at six locations along the eastern seaboard and the Gulf of Mexico for both types of support structures. Using a reference wind turbine and actual metocean conditions for the selected sites, we calculated loads for a parked and an operational situation, and we optimized the MP- and jacket-based support structures to minimize their overall mass. Using a suite of cost models, we then computed their associated LCOE. For all water depths, the MP-based configurations were heavier than their jacket counterparts, but the overall costs for the MPs were less than they were for jackets up to depths of slightly less than 30m. When the associated manufacturing and installation costs were included, jackets resulted in lower LCOE for depths greater than 40m. These results can be used by U.S. stakeholders to understand the potential for different technologies at different sites, but the methodology illustrated in this study can be further employed to analyze the effects of innovations and design choices throughout wind power plant systems.

Wind Farm Turbine Type and Placement Optimization

The layout of turbines in a wind farm is already a challenging nonlinear, nonconvex, nonlinearly constrained continuous global optimization problem. Here we begin to address the next generation of wind farm optimization problems by adding the complexity that there is more than one turbine type to choose from. The optimization becomes a nonlinear constrained mixed integer problem, which is a very difficult class of problems to solve. Furthermore, this document briefly summarizes the algorithm and code we have developed, the code validation steps we have performed, and the initial results for multi-turbine type and placement optimization (TTP_OPT) we have run.

Multidisciplinary design analysis and optimisation of a reference offshore wind plant

Motivated by the need to develop reference wind energy systems for optimisation and technology assessment studies, the International Energy Agency Wind Task 37 on Wind Energy Systems Engineering is developing a reference offshore wind power plant at the Dutch offshore wind energy areas Borssele III and IV. This paper presents a comparison between two approaches for developing the preliminary design of an offshore wind plant turbine layout, electrical collection system, and support structures. The first is a sequential approach, where components of the wind farm are optimised sequentially, each with its own objective function, thus neglecting potential interactions between them. The second approach uses Multidisciplinary Design Analysis and Optimisation (MDAO), where all components are jointly optimised with the overall system levelised cost of energy (LCOE) as a global objective function. Studying the cases of regular and irregular layouts, the integrated approach always shows a greater improvement in the LCOE of the final design compared to the design resulting from the traditional sequential approach. The most significant trade-off exploited by the MDAO approach used in this study is between losses in energy production due to turbine wake effects and the costs of electrical cable infrastructure.