Flywheel energy storage systems (FESS) are devices that are used in short duration grid-scale energy storage applications such as frequency regulation and fault protection. The energy storage component of the FESS is a flywheel rotor, which can store mechanical energy as the inertia of a rotating disk. This article explores the interdependence of key rotor design parameters, i.e., shape, operating speed, rotor radius, standby losses, and choice of material, and their influence on the energy storage characteristics of the FESS. Two commercially manufactured metal flywheels with distinct energy storage characteristics are used as case studies to examine the potential benefit of using shape optimization in combination with operating speed, size, and material selection for rotor design. A sequential hybrid optimization strategy that combines a global genetic algorithm with a gradient-based local method is used to solve the rotor shape optimization problem. The choice of an optimal combination of operating speed and rotor radius, together with shape optimization, is demonstrated to provide 21–46% improvements in the energy capacity of two existing commercial FESS designs. Results show that self discharge losses in the rotor can be reduced by designing optimally shaped rotors with large radii operating at low speeds. It is advantageous, on an “energy-per-cost of material” basis, to use steel as the rotor material for optimally shaped flywheels with large radii operated at low speeds. Conversely, aluminium is a better choice of material for flywheels with smaller radii operated at high speeds.

飞轮储能系统（FESS）是用于短期电网规模储能应用（例如频率调节和故障保护）的设备。FESS的能量存储组件是飞轮转子，它可以将机械能存储为旋转盘的惯性。本文探讨了关键转子设计参数的相互依赖性，即形状，运行速度，转子半径，待机损耗和材料选择，以及它们对FESS储能特性的影响。作为案例研究，使用了两个具有明显储能特性的商业化金属飞轮，以研究将形状优化与运行速度，尺寸和材料选择相结合以进行转子设计的潜在好处。结合全局遗传算法和基于梯度的局部方法的顺序混合优化策略用于解决转子形状优化问题。事实证明，选择运行速度和转子半径的最佳组合以及优化形状，可以使两种现有的商用FESS设计的能效提高21-46％。结果表明，通过设计最佳形状的大半径低速运行的转子，可以减少转子中的自放电损失。以“材料的每单位能量”为基础，有利的是，将钢用作转子材料，用于低速运行时具有大半径的最佳形状的飞轮。相反，铝是用于高速运转的半径较小的飞轮的较好材料选择。