A Framework for Frequency Stability Assessment of Future Power Systems: An Australian Case Study

TL;DR

This paper presents a comprehensive frequency stability assessment framework for future power systems with high renewable penetration, applying it to the Australian case to identify stability limits and effective mitigation strategies.

Contribution

It introduces a time-series based framework for analyzing numerous future scenarios and proposes a dynamic inertia constraint to ensure frequency stability in high renewable scenarios.

Findings

Identified maximum non-synchronous renewable energy penetration for stability.

Dynamic inertia constraint guarantees stability across contingencies.

De-loaded wind farms' governor-like response is most effective for stability.

Abstract

The increasing penetration of non-synchronous renewable energy sources (NS-RES) alters the dynamic characteristic, and consequently, the frequency behaviour of a power system. To accurately identify these changing trends and address them in a systematic way, it is necessary to assess a large number of scenarios. Given this, we propose a frequency stability assessment framework based on a time-series approach that facilitates the analysis of a large number of future power system scenarios. We use this framework to assess the frequency stability of the Australian future power system by considering a large number of future scenarios and sensitivity of different parameters. By doing this, we identify a maximum non-synchronous instantaneous penetration range from the frequency stability point of view. Further, to reduce the detrimental impacts of high NS-RES penetration on system frequency stability, a dynamic inertia constraint is derived and incorporated in the market dispatch model. The results show that such a constraint guarantees frequency stability of the system for all credible contingencies. Also, we assess and quantify the contribution of synchronous condensers, synthetic inertia of wind farms and a governor-like response from de-loaded wind farms on system frequency stability. The results show that the last option is the most effective one.