Assessing the impact of inertia and reactive power constraints in generation expansion planning

TL;DR

This paper introduces the LEGO model to incorporate inertia and reactive power constraints into power system expansion planning, highlighting their critical impact on system stability, cost, and policy goals in high renewable scenarios.

Contribution

The paper presents a novel optimization model that explicitly includes inertia and reactive power constraints, improving accuracy in future power system planning.

Findings

Ignoring inertia and reactive power constraints can lead to higher costs.

Explicit constraints prevent system infeasibilities and resource misallocation.

Inclusion of these constraints aligns planning with stability and policy objectives.

Abstract

On the path towards power systems with high renewable penetrations and ultimately carbon-neutral, more and more synchronous generation is being displaced by variable renewable generation that does not currently provide system inertia nor reactive power support. This could create serious issues of power system stability in the near future, and countries with high renewable penetrations such as Ireland are already facing these challenges. Therefore, this paper aims at answering the questions of whether and how explicitly including inertia and reactive power constraints in generation expansion planning would affect the optimal capacity mix of the power system of the future. Towards this end, we propose the novel Low-carbon Expansion Generation Optimization (LEGO) model, which explicitly accounts for: unit commitment constraints, Rate of Change of Frequency (RoCoF) inertia requirements and virtual inertia provision, and, a second-order cone programming (SOCP) approximation of the AC power flow, accounting for reactive power constraints. An illustrative case study underlines that disregarding inertia and reactive power constraints in generation expansion planning can result in additional system cost, system infeasibilities, a distortion of optimal resource allocation and inability to reach established policy goals.