Due to the increasing integration of power electronics-based renewable energy resources, the active quantification and monitoring of the available inertia to opportunely deploy support actions that can keep its value above critical levels is becoming more and more essential in modern power systems. Besides, since emerging operating scenarios are characterized by higher harmonic distortions and faster dynamics, the accurate tracking of the fundamental frequency and the ROCOF has become significantly challenging. Therefore, new measurement procedures and instruments are required to be developed and validated to equip system operators with more reliable measurements. The QUINPORTION project was centred on the development and full characterization of a new PMU prototype that not only meets the standard requirements but that is also designed to cope with the challenges of low-inertia networks. Besides, the other main focus of the project was the development, implementation, and assessment of suitable algorithms for the dynamic quantification of physical and virtual inertia in power systems.
According to this, an enhanced PMU was developed using the industrial controller NI cRIO-9054 and the Taylor-Fourier Multi-Frequency model for the estimation of phasor, frequency, and ROCOF. Among different examinations, the fidelity of the PMU measurements was evaluated within sophisticated Hardware-in- the-Loop testbeds. In this regard, the device was compared against a Schweitzer Engineering Laboratories SEL-421 protection, automation, and control system (which has an integrated PMU functionality conforming to the IEEE C37.118 standard). Based on different validation metrics, it was confirmed that the entire measurement chain (from the physical signals to the final processed metrics) operates with sufficient accuracy and low latency to be effective for real-time stability monitoring. Furthermore, by subjecting the PMU to realistic and severe grid dynamics in a controlled environment, it was verified that the physical hardware can deliver data of sufficient quality and timeliness. Obtained results in this sense represent a critical step in the technology readiness level, effectively de-risking the proposed solution and paving the way for pilot implementations with TSO partners.
Likewise, based on the results related to the estimation of inertia, performed off-line and real-time simulations demonstrated the effectiveness and accuracy of selected, recursive system identification approaches to approximate inertia in power systems. By using ambient frequency and active power measurements along with parametric model structures such as ARMAX, ARX, and OE, the capability of these forms for inertia extraction in a continuous and dynamic way was verified in a real-time simulation platform. The numerical accuracy, computational efficiency, and robustness of these alternatives is demonstrated by estimating the inertia constant of synchronous generators as well as the virtual contributions from an inverter-based resource with Virtual Synchronous Machine control. By this means, valuable insights into the practical aspects and potential of the chosen methods for actual, real-world power system applications, have been achieved.