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Introduction

In the past decade, the wind industry has witnessed significant levels of innovation, resulting in the development of larger, multimegawatt turbines aimed at achieving lower associated costs of energy. Yet, increasing their competitiveness within the energy sector compared to conventional power sources imposes more requirements on the technology in terms of performance, reliability, and cost. As a result, the industry has been focusing on a variety of goals including trading off installed capital costs for the turbine and plant, costs for operation and maintenance (O&M), energy production, and negative external impacts such as noise emission or habitat disruption [1]. Wind turbine drivetrains serve the fundamental role of converting the aerodynamic torque from the turbine into useful electrical power that can be fed to the power grid. Within the turbine drivetrain, the electrical generator is an important functional element that enables the conversion of energy and is a key determinant of the overall efficiency, reliability, and costs of energy production. In gear-driven systems, the generator is the third most expensive element (after the gearbox and power converters [2]), whereas in direct-driven systems, the generator is the single biggest cost component that challenges their upscaling potential. As part of the National Renewable Energy Laboratory’s (NREL’s) Wind-Plant Integrated System Design and Engineering Model development effort aimed at providing sizing and costing pathways for various subsystems within the wind turbine, GeneratorSE is a new modeling capability developed by NREL specifically intended for optimizing variable-speed wind turbine generators. GeneratorSE provides users with the ability to customize the generator design, thereby satisfying certain design requirements. As a result, users can achieve optimal performance of the entire wind turbine drivetrain by negotiating certain fundamental, interdependent factors such as weight, cost, and efficiency to meet the wind turbine original equipment manufacturer’s objectives. GeneratorSE can be used as an autonomous tool that focuses on generator design or integrated in the system using DriveSE, NREL’s drivetrain sizing tool [3]. Thus, the designer has the option to trade magnet, copper, or lamination properties and weights to achieve the optimal generator design that is also optimal for a given drivetrain system. Two types of generator systems— synchronous and induction machines—are currently being handled by GeneratorSE. The tool includes the following subclasses: permanent-magnet synchronous generators (PMSGs) electrically excited synchronous generators (EESGs), squirrel-cage induction generators (SCIGs), and doubly-fed induction generators (DFIGs). This report documents a set of analytical models employed by the optimization algorithms within the GeneratorSE framework. The initial values and boundary conditions employed for the generation of the various designs and initial estimates for basic design dimensions, masses, and efficiency for the four different models of generators are presented and compared with empirical data collected from previous studies and some existing commercial turbines. These models include designs applicable for variable-speed, high-torque application featuring direct-drive synchronous generators and low-torque application featuring induction generators. In all of the four models presented, the main focus of optimization is electromagnetic design with the exception of permanent-magnet and wire-wound synchronous generators, wherein the structural design is also optimized. Thermal design is accommodated in GeneratorSE as a secondary attribute by limiting the winding current densities to acceptable limits. A preliminary validation of electromagnetic design was carried out by comparing the optimized magnetic loading against those predicted by numerical simulation in FEMM4.2 , a finite-element software for analyzing electromagnetic and thermal physics problems for electrical machines. For direct-drive synchronous generators, the analytical models for the structural design were validated by static structural analysis in ANSYS .