Micro to macro scale modeling of electrical machines

电机的微观到宏观建模

• 批准号: RGPIN-2019-05313
• 负责人: Knight, Andrew
• 金额: $ 3.35万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=752154
• 关键词: Micro; macro; scale; modeling; electrical

My Discovery Research program investigates electrical energy efficiency and the development of low carbon electrical power equipment. This broad scope covers the development of new high-efficiency electric motors, creating tools to understand losses in hydro generators through to the integration of renewable energy and energy storage technologies into systems. These systems may include electric transportation, microgrids or larger power systems. As the world considers how to reduce the carbon footprint of energy use, two key solution paths have developed: 1) electrification of carbon-intensive systems; 2) reducing the carbon intensity of electric systems. A primary application of electrification is transportation. Examples here include decisions by auto manufacturers such as Volvo to move to produce only electric or hybrid-electric vehicles. Less well known are the work to produce more-electric and fully-electric aircraft or the development of electric ship propulsion. Reductions to the carbon intensity of electricity generation are occurring through well-known efforts such as the expansion of wind and solar generation, but also through the deployment of small-scale gas turbines. A key factor in all these developments is the rapid expansion in the use of high efficiency and fault tolerant electrical motors and generators. As a result of this growth, there is a growing need to understand how new electrical machines operate within systems when the equipment is faulted or operating under non-ideal conditions. Transportation systems and energy production must be robust and continue to operate safely in the presence of faults. In order to be able to investigate the potential propagation of faults and non-ideal operation of machinery, it is necessary to develop modelling strategies that scale from the detail of individual component design, through component control strategies to wide area power system analysis. There are currently no practical analysis approaches capable of this. Innovative research in this program will develop these analysis tools. These new models require coupling of multiple physical scales and timescales. Conventionally, this has been accomplished by use of uncoupled consecutive modelling approaches - detailed models of components are developed and parameterized, then reduced scale models are introduced into transient electromagnetic models. Results from these models are in turn used in steady state power system analysis. This approach works well if a system fault is applied to an ideal symmetrical machine. However, it fails when component faults and systems interact. This research program will develop methods to enable concurrent multiscale models of distributed energy resources in electrical energy systems and electric machines in small power systems such as electric transportation.

我的发现研究项目调查电能效率和低碳电力设备的发展。这一广泛的范围涵盖了新型高效电动机的开发，通过将可再生能源和储能技术集成到系统中，创造了了解水轮发电机损失的工具。这些系统可能包括电力运输、微电网或更大的电力系统。当全世界都在考虑如何减少能源使用的碳足迹时，已经形成了两个关键的解决方案：1)碳密集型系统的电气化；2)降低电力系统的碳强度。电气化的一个主要应用是交通运输。这方面的例子包括沃尔沃等汽车制造商决定只生产电动或混合动力汽车。不太为人所知的是生产更电动和全电动飞机或开发电动船舶推进系统的工作。通过众所周知的努力，如扩大风能和太阳能发电，以及通过部署小型燃气涡轮机，正在减少发电的碳强度。所有这些发展的一个关键因素是高效率和容错电动机和发电机的使用迅速扩大。由于这种增长，人们越来越需要了解当设备出现故障或在非理想条件下运行时，新的电机如何在系统内运行。运输系统和能源生产必须是稳健的，并在存在故障的情况下继续安全运行。为了能够研究故障的潜在传播和机械的非理想运行，有必要制定建模策略，从单个组件设计的细节，通过组件控制策略到广域电力系统分析。目前还没有实际的分析方法能够做到这一点。这个项目的创新研究将开发这些分析工具。这些新模型需要多个物理尺度和时间尺度的耦合。通常，这是通过使用非耦合连续建模方法来完成的——首先建立部件的详细模型并进行参数化，然后将缩小比例模型引入瞬变电磁模型中。这些模型的结果又被用于稳态电力系统的分析。如果将系统故障应用于理想的对称机器，则此方法效果良好。但是，当组件故障和系统交互时，它将失败。该研究计划将开发方法，以实现电力能源系统和小型电力系统（如电力运输）中的电机中分布式能源资源的并发多尺度模型。