A Coordinated Active and Reactive Power Optimization Method for Integrated Energy System Based on an XGBoost Surrogate Model for Voltage Stability Margin

Abstract

Conventional integrated energy system (IES) dispatch generally enforces bus-voltage limits but does not quantify proximity to the static voltage-instability boundary, while repeated physics-based stability calculations are computationally expensive for multi-period optimization. This study proposes a coordinated active- and reactive-power dispatch framework for an electricity–heat IES. The minimum singular value of the reduced power-flow Jacobian is used as a physics-based static voltage-stability margin. Monte Carlo operating states are labeled through AC power-flow and Jacobian calculations and used to train an XGBoost surrogate that maps loads, renewable output, electricity–heat coupling-device power, storage states, and reactive-power controls to the margin. SHAP analysis identifies influential buses and operating variables and supports feature reweighting during surrogate training. The predicted margin is converted into a risk penalty and optimized jointly with electricity-purchase, renewable-curtailment, and equipment operating costs. The framework coordinates active-power reshaping by heat pumps, electric boilers, storage, and flexible loads with reactive-power support from SVCs, SVGs, and converter-interfaced resources. The resulting schedule is finally verified by AC power-flow and reduced-Jacobian margin calculations. This approach makes a physics-based stability index practical for preventive, security-aware IES dispatch while retaining model interpretability and physical verification.