Abstract

This paper investigates the impact of network structures on small-disturbance voltage stability of power systems in the long-term. A differential-algebraic model is established in terms of network topology characteristics and the aggregate nonlinear recovery load model. We define the weighted load connectivity (WLC) as an index to indicate the stability of network structures. Then robust stability assessment is used to eliminate the impact of uncertain recovery time of loads. The Monte Carlo method is used to study the relationship between WLC and small-disturbance voltage stability (SDVS) for a broad range of network topologies and parameters. We discover from the simulation results that the network with a larger value of WLC has a stronger ability to maintain SDVS. To further study the impact of renewable energy sources (RESs), we improve the system model by including an inverter-based distributed generator in parallel with each aggregated nonlinear dynamic load. The simulation results of the Hong Kong power grid show that the WLC can still indicate the stability of network structures effectively, and the systems with more stable network structures are less impacted by the penetration of RESs. The proposed WLC appears useful in providing guidance for power network planning and operation.

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