Development of Innovative Technologies and Tools for Flexibility Assessment and Enhancement of Future Power Systems

在电力系统中，运行灵活性对于平衡负荷和不可调度发电之间的长期和短期差异至关重要。由于来自可再生资源的波动发电的份额越来越大，这种对灵活性的需求在未来几年将大幅增加。传统上，这种灵活性差距可以通过安装成本和资源密集型技术来弥合，比如化石发电厂或抽水蓄能系统。为了避免这些大规模投资，人们开发了其他利用电力系统固有灵活性的方法，其中许多方法利用了现有技术单位已经存在的自由度。这种方法也被称为需求侧管理或供应侧管理，包括分布式技术单元的运行，每次都符合电力系统的要求，称为分布式灵活性。从输电系统的角度来看，分布式灵活性选项的建模通常具有高度的抽象性，忽略了对分布级别的潜在影响。相反，配电网中的灵活性通常被建模得非常详细，但灵活性激活的目标通常在于配电网本身。因此，这些分析忽略了对覆盖系统的灵活性或技术限制的额外要求。此外，在实践中，同样的灵活性可以单独用于一个或另一个应用程序，但不能同时用于这两个应用程序。为分布式柔性开发一种统一的建模方法。虽然最近的方法未能对电力系统不同层次的灵活性达成共识，但申请者将开发一个模型框架，允许从面向分布的角度以及从全系统的角度详细量化灵活性潜力。在这种方法中，分布式柔性调度的详细技术优化模型被实施，并在第一步通过广泛的随机模拟来增强。该模型的系统行为在第二步中通过人工智能和机器学习的方法进行分析、学习并最终重现。由此产生的分布式灵活性的多级模型随后允许更准确地量化分布式灵活性，并对对配电和输电系统的交叉影响进行新颖的分析。在实践中，这种建模方法对于欧洲和俄罗斯输电网和配电网的有效规划至关重要。分布式灵活性的改进量化将允许更安全和稳定的电网运行。此外，分布式灵活性的多层次考虑对于最小化总体电网扩展需求以及有效规划发电厂容量和能源市场非常重要。

In electrical power systems, operational flexibility is crucial for the balancing of long- and short-term disparities between load and non-dispatchable generation. Due to the increasing share of fluctuating power generation from renewable resources, this demand for flexibility is going to drastically increase in the oncoming years. Conventionally, this flexibility gap is closed by installation of cost- and recourse-intensive technologies like fossil power plants or pump storage systems. In order to avoid these large-scale investments, other ways of using a power system’s inherent flexibility have been developed, many of them using already existing degrees of freedom of pre-existing technical units. This approach is also known as demand- or supply-side management and comprises the operation of distributed technical units in line with the requirements of the electric power system at a time and is called distributed flexibility. From a transmission system’s perspective, distributed flexibility options are usually modelled with a high degree of abstraction, neglecting potential influences on the distribution level. In contrary, flexibility in distribution grids is often modelled very detailed, but the objective of the flexibility activation lies most often in the distribution grid itself. Thus, these analyses neglect the additional demand for flexibility or technical restrictions in the overlaying system. In addition, the same flexibility can in practice either be used for one application or another individually, but not for both at the same time. velop a unified modelling approach for distributed flexibility. While recent approaches fail at common understanding of flexibility in the different layers of the power system, the applicants will develop a modelling framework that allows the detailed quantification of flexibility potentials with a distribution-oriented perspective as well as on a system-wide view. In this approach, detailed technical optimisation models for the dispatch of distributed flexibility are implemented and enhanced by means of an extensive stochastic simulation in a first step. The systematic behaviour of this model is in a second step analysed, learned and finally reproduced by methods of artificial intelligence and machine learning. The resulting multilevel model of distributed flexibility subsequently allows a much more accurate quantification of the distributed flexibility together and novel analyses of the cross-impact on distribution and transmission systems. In practice, such modelling approaches will be crucial for an efficient planning of European and Russian transmission and distribution grids. The improved quantification of distributed flexibility will allow a more secure and stable grid operation. Additionally, the multilevel consideration of distributed flexibility is important for minimising the overall grid expansion demand and efficient planning of power plant capacity and energy markets.