Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
60 tokens/sec
GPT-4o
12 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
5 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Stabilizing Large-Scale Electric Power Grids with Adaptive Inertia (2311.01350v2)

Published 2 Nov 2023 in eess.SY, cs.SY, and physics.soc-ph

Abstract: The stability of AC power grids relies on ancillary services that mitigate frequency fluctuations. The electromechanical inertia of large synchronous generators is currently the only resource to absorb frequency disturbances on sub-second time scales. Replacing standard thermal power plants with inertialess new renewable sources of energy (NRE) therefore jeopardizes grid stability against e.g. sudden power generation losses. To guarantee system stability and compensate the lack of electromechanical inertia in grids with large penetrations of NREs, virtual synchronous generators, that emulate conventional generators, have been proposed. Here, we propose a novel control scheme for virtual synchronous generators, where the provided inertia is large at short times -- thereby absorbing faults as efficiently as conventional generators -- but decreases over a tunable time scale to prevent coherent frequency oscillations from setting in. We evaluate the performance of this adaptive inertia scheme under sudden power losses in large-scale transmission grids. We find that it systematically outperforms conventional, electromechanical inertia and that it is more stable than previously suggested schemes. Numerical simulations show how a quasi-optimal geographical distribution of adaptive inertia devices not only absorbs local faults efficiently, but also significantly increases the damping of inter-area oscillations. Our results show that the proposed adaptive inertia control scheme is an excellent solution to strengthen grid stability in future low-inertia power grids with large penetrations of NREs.

Citations (1)

Summary

We haven't generated a summary for this paper yet.