Decentralized Optimal Scheduling for Coordination of Electricity and Gas Systems Considering Frequency and Virtual Inertia Constraints Under Uncertainty

ABSTRACT The transition from traditional bulk generation to renewable energy is reshaping power systems, introducing security challenges due to decreased system inertia. Natural gas (NG)‐fired units, known for their quick response, are often scheduled for operational flexibility, increasing interdependency between electrical and NG networks. However, the decentralized management of these networks by separate operators complicates coordinated system management. This study presents an optimization model that co‐optimizes unit commitment (UC) and virtual inertia (VI) from wind farms (WF) while addressing frequency constraints (FC) and NG network limitations. The model's effectiveness is validated through two case studies: a smaller network with seven gas nodes and an IEEE 5‐bus system, and a larger system with 20 gas nodes and an IEEE 118‐bus system. The results show that incorporating VI constraints reduced costs by 0.8% in Case 1 and 25.8% in Case 2. However, applying FC in Case 2 increased costs by 7.1% while improving frequency stability. These findings underscore the importance of VI in reducing operational costs and enhancing grid stability, especially under variable gas supply conditions. The proposed model demonstrates economic efficiency and grid resilience, making it a useful tool for planning integrated energy systems with increasing renewable energy penetration.This study addresses the scheduling problem in power systems transitioning from traditional to renewable generation, which increases frequency security issues due to reduced system inertia. An optimization model co‐optimizes UC and VI provision from WF, considering FC and operational limitations of the NG system (NGS). Case studies demonstrate the model's effectiveness and computational efficiency.