A Simple Approach to Quantify Accuracy of Power Systems Inertia

Power network stability is a goal that all system operators try to achieve during their daily management. However, the recent spread of renewable energy sources obstacles such a goal. This is mainly due to the replacement of synchronous machines with static-conversion-based ones. Consequently, the grid is now experiencing (i) lower levels of inertia that help during anomalous operations; (ii) lower predictability of the power generation. As for inertia, it is becoming, day after day, a critical parameter used to assess the network's capability to sustain power/frequency variations, due to faults or disturbances. Therefore, system operators are more and more relying on such parameter for implementing their countermeasures. However, the inertia accuracy assessment is still an open issue, and it is seldom associated with the inertia estimates. To this purpose, this paper tries to quantify the uncertainty to be associated with inertia. This is done starting from its definition and the main uncertainty contributions. To achieve this goal, the Monte Carlo method is applied to realistic scenarios. From the results, it clearly emerges the importance of running rigorous uncertainty analysis. This is particularly true for those critical parameters like inertia.