Data-Driven and HVDC Control Methods to Enhance Power System Security

Abstract

The development of High-Voltage Direct Current (HVDC) transmission based on Voltage Source Converters (VSCs) and its advantages compared to HVDC based on Line Commutated Converter (LCC), such as black-start capability and the capability to supply weak grids, has increased the interest in HVDC technology in Europe. Moreover, it is seen as enabling technology for Multi-Terminal High-Voltage Direct Current (MT-HVDC) grids. As such a MT-HVDC grid would most likely not be built at once in Europe but be developed by a step-wise integration of already existing on- and o↵shore inter-connectors, this raises potential multi-vendor interoperability issues. Furthermore, new methods are needed which take advantage of (i) the flexibility such a grid can o↵er and (ii) the high-resolution, real-time data available through the increasing deployment of Phasor Measurement Units (PMUs) in order to enhance the system stability of the interconnected AC-HVDC system. This thesis covers five aspects of these developments: we investigate the potential of HVDC transmission lines in Europe; we found that several new HVDC lines are indispensable in the future European transmission network to meet the renewable energy source (RES) integration targets of the European Union. Ideally, these lines must become parts of a MT-HVDC grid to minimize costs and increase reliability. In order to enable an MT-HVDC network consisting of installations from multiple suppliers, we investigate potential multi-vendor interoperability issues and the impact of di↵erent control structures on the power system stability. Further, with the ability to control active and reactive power independently within milliseconds, VSC-HVDC systems do not only introduce new challenges but also new opportunities, such as controllable power flows and corrective control. Considering the increasing availability of measurement data, and the recent advances in data-driven approaches, we develop methods allowing us to enrich and use the available measurement data to increase power system security. As historical data often contain limited number of abnormal situations, simulation data are necessary to accurately determine the security boundary. Therefore, we developed a modular and highly scalable ecient database generation method for data-driven security assessment of power systems. Moreover, using these databases, we take a more holistic view, and we combine the data-driven security assessment with optimization for operations and markets. Thereby, we leverage the advantages of the controlability of VSC-HVDC, the ecient data generation and data-driven methods to minimize power system operation costs. Finally, inspired by the development of the data-driven security assessment, we developed a first proof-of-concept of how such methods can not only assess security, but also predict the criticality of faults based on local measurements only without requiring communication. Ideally, such a method could be developed into a local control support method for HVDC terminals enabling the HVDC terminal potentially not only to react to measurements but act on stability predictions and thereby potentially prevent fast evolving short-term voltage stability problems.