Addressing the complexity of future power system dynamic behaviour

解决未来电力系统动态行为的复杂性

• 批准号: MR/Y00390X/1
• 负责人: Panagiotis Papadopoulos
• 金额: $ 75.88万
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FY00390X%2F1
• 关键词: Addressing; complexity; future; power; system

Electrical power systems are undergoing unprecedented changes that increase the levels of complexity and uncertainty, mainly driven by decarbonisation targets on the way to achieving net zero operation and addressing climate change. As an example, towards this direction the UK government has set a bold target for zero carbon electricity by 2035. Increasing complexity comes from the introduction of a large number of converter-interfaced devices (CID) that exhibit very different dynamic behaviour, governed to a large extent by control. In addition, uncertainty in power system operation is increasing, due to the intermittent behaviour of renewable sources but also increasingly by social behaviour through EVs and potential electrification of heating as well as complex market and power industry structures. This leads to an exploding search space of possible operating conditions and contingencies, which is particularly challenging for computationally intensive stability assessment and dynamic studies. This aspect coupled with the increasing complexity of dynamic behaviour, makes identifying critical operating conditions and contingencies challenging. Consequently, these developments raise the need for improved representation and understanding of dynamic phenomena as well as fast and informative dynamic security and stability assessment. Both aspects are crucial in order to avoid potentially hidden risks of instability that in the worst-case scenario can lead to widespread events and even blackouts. Consequently, the aim of this proposal is to develop methods, tools and models needed to achieve a secure, resilient and cost-effective power system operation.Building on progress made in the initial part of the fellowship, the extension will continue focusing on two main directions. From one hand, it will develop tools, methods and models to represent and investigate the changing dynamic behaviour of power systems in order to capture new arising dynamic phenomena, spanning both transmission and distribution (e.g. offshore/onshore wind, solar PVs, HVDC links, EVs, heat pumps, electrolysers, etc.). On the other hand, it will develop novel machine learning based and data-driven methods for the fast and informative stability assessment as well as the estimation of the stability boundary. This direction will enable unique understanding of the dynamic behaviour that will lead to ancillary services and control to mitigate or alleviate the impact of disturbances and improve system security and resilience. In addition, the fellowship extension will continue and ramp-up engagement with industrial partners to capture practical aspects and fine tune developed methodologies to pave the way for real world applications.In effect, the results of the fellowship will enable more secure, resilient and potentially more cost-effective operation of power systems due to better knowledge of system stability limits. Consequently, much higher integration of renewables and new technologies with various technical and environmental benefits can be achieved in order to meet bold decarbonisation targets in a secure, resilient and cost-efficient manner.

电力系统正在发生前所未有的变化，以增加复杂性和不确定性水平，这主要是由脱碳目标驱动的，以实现净零操作并解决气候变化。例如，朝着这个方向朝着英国政府设定了零碳电力的大胆目标。复杂性的提高来自引入大量转换器相互交流的设备（CID），这些设备（CID）表现出非常不同的动态行为，在很大程度上由控制控制。此外，由于可再生能源的间歇性行为，电力系统操作的不确定性正在增加，但通过电动汽车以及供暖以及复杂的市场和电力行业结构的潜在电气化而越来越多。这导致了可能的操作条件和意外事件的爆炸搜索空间，这对于计算密集型稳定性评估和动态研究尤其具有挑战性。这方面加上动态行为的复杂性日益增加，使确定关键的工作条件和意外事件具有挑战性。因此，这些事态发展提出了对动态现象以及快速而有益的动态安全和稳定评估的改善表示和理解的需求。这两个方面都是至关重要的，以避免潜在地隐藏的不稳定风险，在最坏情况下，这可能会导致广泛的事件甚至停电。因此，该提案的目的是开发实现安全，弹性和成本效益的电力系统操作所需的方法，工具和模型。建立奖学金最初的进度的建设，该扩展将继续集中在两个主要方向上。一方面，它将开发工具，方法和模型来表示和研究动力系统的动态行为不断变化，以捕获新的动态现象，涵盖传输和分配（例如，海上/陆上风，太阳能PVS，HVDC链接，HVDC链接，EVS，EV，热泵，热泵，电源器等）。另一方面，它将开发基于机器学习的新型和数据驱动的方法，以进行快速且内容丰富的稳定性评估以及稳定边界的估计。这个方向将使对动态行为的独特理解，这将导致辅助服务和控制，以减轻或减轻干扰的影响并提高系统安全和弹性。此外，奖学金的扩展将继续并与工业伙伴的互动，以捕获实用方面和微调开发的方法，以为现实世界的应用铺平道路。实际上，由于更好的系统稳定性限制了系统稳定性，该研究金的结果将使奖学金的结果更加安全，有弹性，并具有更高的成本效益运行。因此，可以将可再生能源和新技术与各种技术和环境益处的新技术集成得更高，以便以安全，弹性和成本效益的方式实现大胆的脱碳目标。