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发电和不可调度发电之间的长期和短期差异至关重要。由于可再生能源发电的波动性越来越大，这种对灵活性的需求在未来几年将急剧增加。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补，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，已经开发了利用电力系统固有灵活性的其他方法，其中许多方法使用了已有技术单元的现有自由度。这种方法也被称为需求侧或供应侧管理，它包括分布式技术单元在同一时间内按照电力系统的要求运行，称为分布式灵活性。从输电系统的角度来看，分布式灵活性的建模通常是高度抽象的，忽略了对配电层的潜在影响。相反，配电网的灵活性通常被建模得非常详细，但灵活性激活的目标往往在于配电网本身。因此，这些分析忽略了在覆盖系统中对灵活性或技术限制的额外需求。此外，在实践中，相同的灵活性可以单独用于一个应用程序或另一个应用程序，但不能同时用于两个应用程序。为分布式灵活性开发统一的建模方法。虽然最近的方法无法共同理解电力系统不同层的灵活性，但申请人将开发一个建模框架，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。在该方法中，首先通过广泛的随机模拟，实现了分布式灵活性调度的详细技术优化模型，并对其进行了增强。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、学习并最终再现。由此产生的分布式灵活性的多层模型随后可以更准确地量化分布式灵活性，并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配电网络的有效规划至关重要。分布式灵活性的改进量化将使电网运行更加安全和稳定。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电厂容量和能源市场的有效规划非常重要。

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.