Stochastic optimisation for secure dynamic AC-load flow in hybrid multi-modal energy systems under uncertainty

电网资源，在本项目中主要是电力，但也包括天然气和水，将在经济活动增加的世界中发挥关键作用，电网本身也将如此。对于它们的设计和操作，数据不确定性下决策的复杂性日益增加，提出了具有挑战性的优化问题，现有方法的改进是解决这些问题不可或缺的。后者从正确处理风险、非线性和结果模型的大规模销售性质的概念性工作开始。最优潮流（OPF）在交流网络中具有举足轻重的作用，因为它不仅是现实建模的必要条件，而且在数学上也是有益的。另一个至关重要的方面是适当地包括由于可再生能源的不稳定输入而产生的外部不确定性。在计划调查的核心中，有一个新的综合数学模型和定制的“工程价值”方法的适当框架的发展，以支持对那些容易预测错误和不确定性的能源系统的研究。本文特别讨论了以下主题：随机应急管理、网络稳定性、可再生能源输入不确定性下交流网络的拥塞管理以及多模式能源系统的风险规避。

Grid-bound resources, in the present project foremostly electricity, but also gas and water, will have a critical role in a world of increased economic activity, and so will the grids themselves. For their design and operation, the growing complexity of decision making under data uncertainty poses challenging optimisation problems for whose solution the advancement of the existing methodology is indispensable. The latter starts with conceptual work on the proper treatment of risk, nonlinearity, and the large-sale nature of resulting models. Optimal power flow (OPF) in alternate-current (AC) networks has a pivotal role, both since it is indispensable for realistic modeling and also mathematically rewarding. Another crucial aspect is the proper inclusion of external uncertainty due to volatile input from renewablesIn the core of the planned investigations there is the development of an appropriate framework of new integrated mathematical models and tailored methods of ``engineering value'' supporting research into those energy systems prone to forecast errors and uncertainty. In particular, the following topics are addressed:stochastic contingency management, network stability, management of congestions in AC networks under renewable infeed uncertainty, and risk aversion in multimodal energy systems are addressed.