Electric Power Systems - simulation, operational behaviour, control and protection

电力系统 - 模拟、运行行为、控制和保护

• 批准号: RGPIN-2015-06772
• 负责人: Malik, Om
• 金额: $ 2.19万
• 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: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=614494
• 关键词: Electric; Power; Systems; simulation; operational

Primary thrust of the research is the development of real-time digital control and protection schemes for improved stability of electric power systems. It includes the study of problems relating to electric machine behavior, analysis, design and development of control and protection schemes, generation of electric power from renewable sources, and power system equipment aging assessment for economic maintenance. Power system characteristics are non-linear and change due to changes in network configuration, equipment aging, etc. The fixed parameter controllers, designed for one operating condition, cannot track changes in system parameters. With time they cannot provide optimal performance and system performance degrades. For proper operation, controllers should be retuned. It requires the plant be taken off-line and is expensive due to loss of productivity. A solution is to employ adaptive control algorithms that continuously monitor the dynamic behavior of the system and adjust controller parameters in real-time according to the prevailing system operating conditions. Adaptive self-tuning controllers, that adjust controller parameters automatically to suit actual operating conditions and particularly suitable for application to electric generating units, have been developed. Use of artificial intelligence techniques to design adaptive self-tuning controllers that are robust, effective and universal is being investigated for application to both conventional and renewable electric power generation. Extension of these control algorithms to power electronics devices to improve the stability of interconnected power systems is being explored. A big concern of the power industry is aging assets and lack of techniques to assess the life cycle of power transformers. Algorithms based on intelligent techniques to mine and evaluate the pool of data available with the newly emerging smart grid technologies that the utilities can use to commence effective condition based maintenance actions and prevent unexpected failures are being investigated to provide enormous savings to the utilities. Concerns over environmental degradation have started a major move towards electrical power generation using renewable energy sources. It has resulted in a new direction, including wind farms, distributed generation and micro-grids, with new operational, control and protection problems specific to these technologies. A good part of the research is devoted to various aspects of renewable energy generation, such as safe and reliable protection and control of wind based generation, voltage and frequency control of micro-grids and islanding protection of distributed generation. Making use of the earlier experience with adaptive and artificial intelligence based control, new schemes are being investigated to improve the operation and integration of generation from renewable resources.

这项研究的主要目的是开发实时数字控制和保护方案，以提高电力系统的稳定性。它包括与电机行为有关的问题的研究，控制和保护方案的分析、设计和开发，可再生能源发电，以及用于经济维护的电力系统设备老化评估。 电力系统的特性是非线性的，会随着网络配置的变化、设备的老化等而发生变化。固定参数控制器是为一种运行状态设计的，不能跟踪系统参数的变化。随着时间的推移，它们无法提供最佳性能，系统性能也会下降。为保证正常运行，应重新调整控制器。它要求工厂下线，而且由于生产力损失，成本高昂。一种解决方案是采用自适应控制算法，持续监控系统的动态行为，并根据主要的系统运行条件实时调整控制器参数。自适应自校正控制器已被开发出来，它能自动调整控制器参数以适应实际运行条件，特别适用于发电机组。利用人工智能技术设计稳健、有效和通用的自适应自校正控制器正在研究中，以应用于传统发电和可再生能源发电。正在探索将这些控制算法扩展到电力电子设备中，以提高互联电力系统的稳定性。 电力行业的一大担忧是资产老化，缺乏评估电力变压器生命周期的技术。基于智能技术的算法正在被研究，以利用新出现的智能电网技术来挖掘和评估可用的数据池，公用事业公司可以使用这些数据池来开始有效的基于状态的维护行动，并防止意外故障，以为公用事业公司提供巨大的节省。 对环境退化的担忧已经开始了使用可再生能源发电的重大举措。它导致了一个新的方向，包括风力发电场、分布式发电和微电网，以及这些技术特有的新的操作、控制和保护问题。可再生能源发电的研究主要集中在风力发电的安全可靠保护和控制、微网的电压和频率控制以及分布式发电的孤岛保护等方面。利用早先在自适应和基于人工智能的控制方面的经验，正在研究新的方案，以改善可再生资源发电的运行和整合。