Transient Stability-Driven Planning for the Optimal Sizing of Resilient AC/DC Hybrid Microgrids

TL;DR

This paper introduces a comprehensive planning framework for resilient AC/DC hybrid microgrids, integrating transient stability considerations into optimal sizing and operation to enhance resilience under contingencies.

Contribution

It develops a novel transient stability-driven planning model with a bi-level DAD architecture and an advanced genetic algorithm, incorporating transient stability constraints into microgrid sizing and operation.

Findings

Effective in optimizing resource sizing for resilience

Ensures transient stability under various contingencies

Achieves cost-effective investment decisions

Abstract

This paper proposes a transient stability-driven planning framework for the optimal sizing problem of resilient AC/DC hybrid microgrids (HMGs) under different types of contingencies, capturing frequency and voltage stability requirements as well as the frequency-voltage coupling dynamics of AC/DC interlinking converters (ICs). The planning model is formulated into a defender-attacker-defender (DAD) architecture, which can be further merged into two levels, i.e., upper-level and low-level problems, and then iteratively solved by an enhanced genetic algorithm with sparsity calculation and local search. Regarding the operation stage, a novel transient stability-constrained optimal power flow (TSC-OPF) algorithm is proposed for static and transient operations of HMGs, capturing governor dynamics and automatic voltage regulator of conventional generators as well as the droop control dynamics of inverter-based resources (IBRs) for frequency control and voltage control, respectively. Furthermore, a Lyapunov optimisation approach is developed to capture the time-coupling property of energy storages (ESs) and then allow the TSC-OPF to be solved on an hourly basis with a second-scale resolution, achieving the co-optimisation of static and transient stability requirements. Case studies have been conducted to verify the effectiveness of the proposed planning framework in obtaining cost-effective investment decisions for various resources while respecting transient stability requirements under different contingencies.