The integration of power electronics-interconnected generation systems to the grid has fostered a significant number of concerns on power system operations, particularly on the displacement of synchronous generators that leads to a reduction in the grid’s overall inertia and frequency response. These concerns have raised a significant amount of state-of-the-art mathematical proposals on how to estimate system inertia; however, the majority of the proposals do not differentiate generator inertia from load inertia. When inertia prediction for control room applications is required in real-time, the current state-of-the-art proposals use the inertia of generators as a proxy for a minimum, overall inertia estimate, counting the number of units committed in real-time and adding up their inertia. However, as dynamic conditions are becoming challenging with the integration of power electronics-interconnected generation systems, it is important to quantify the amount of inertia from the loads, for which the state-of-the-art proposals present very limited advancement, particularly in applications with real data. This work presents a set of recorded actual events in the Chilean power system to estimate the contribution of loads to inertia and frequency response to assess whether the loads have a significant role in frequency stability. The contribution of this work is as follows: first, reporting real data of a power system from the PMU and SCADA systems that are usually classified as not public; and, second, to derive a conclusion from the data to assess the role of loads in frequency stability in a real case.
The current need for power-system control-room operational tools to increase real-time situational awareness has led to various proposals on data analytics algorithms to obtain operational information from SCADA and PMU power system networks. Most of the proposals are implemented in simulation, with reduced practical significance for system operators. This work proposes a web-based simple algorithm to identify the dynamic parameters of a reduced-order model of power system frequency dynamics that is implemented with industrial hardware on a PMU network in the Chilean power system. To demonstrate the applicability of the proposed tool, the algorithm is implemented in a web page with real-time monitoring of the frequency of the Chilean power system, so that utilities and academic institutions with access to PMU measurements can apply the proposed concepts regardless of the topology of the monitored system.