Management-oriented decision framework for grid-support technology selection in islanded power systems: a comparative analysis of STATCOMs and synchronous condensers

Purpose This study aims to develop a management-oriented decision framework to guide the selection and deployment of static synchronous compensators (STATCOMs) and synchronous condensers in islanded power systems, addressing the gap between engineering analysis and infrastructure governance in the energy sector. Design/methodology/approach The framework integrates key managerial criteria − system efficiency, capital expenditure, deployment time, maintenance complexity and system strength and resilience − within an analytic hierarchy process (AHP)-based decision architecture. Taiwan’s islanded power system serves as the primary case, with Australia’s National Electricity Market as an international reference. The framework is validated through expert elicitation involving five industry professionals with an average of 28.6 years of experience, using structured AHP questionnaires. A scenario-based sensitivity analysis examines how different managerial priorities shift technology preferences. Findings Under the baseline weighting, system strength and resilience receives the highest priority weight (0.396), followed by operational efficiency (0.264). Expert validation confirms this prioritization, with system strength and resilience receiving the highest group consensus weight (0.472). STATCOMs score higher under cost- and speed-driven scenarios (composite score 0.63 vs 0.37), whereas synchronous condensers are preferred under resilience-priority conditions (0.61 vs 0.39). Practical implications The framework provides utilities, regulators and policymakers with a transparent, replicable decision-support tool that links device-level capabilities to sector-level planning and governance processes in islanded and weak-grid environments. Originality/value This study reframes grid-support technology selection as an infrastructure governance decision rather than a purely technical optimization problem, combining literature-informed analysis with expert validation to bridge engineering analysis and energy sector management practice.