Open Access

ARTICLE

An Assessment Method for Static Security Regions in Large-Scale Wind-Integrated Power Systems Based on Probabilistic Power Flow

Hongbo Liu, Jingzhou Zhu, Li Sun^*, Fanjun Zeng
Northeast Electric Power University, Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education, Jilin, China
* Corresponding Author: Li Sun. Email:

Energy Engineering https://doi.org/10.32604/ee.2026.075768

Received 07 November 2025; Accepted 09 January 2026; Published online 03 February 2026

Abstract

This paper tackles the challenge of balancing computational efficiency with analytical rigor in Probabilistic Power Flow (PPF) analysis for power systems with integrated wind power. We propose an enhanced steady-state security region (SSR) assessment method based on PPF theory. The methodology first employs a hybrid Monte Carlo technique that integrates Latin Hypercube Sampling (LHS) with Importance Sampling (IS) to compute and analyze the probabilistic power flow distribution. This hybrid strategy ensures comprehensive global coverage while intensively sampling critical risk regions, thereby improving both computational efficiency and accuracy. Subsequently, a fast-search model for the SSR is constructed. A Static Security Distance (SSD) index is also introduced to quantify the composite impact of renewable generation volatility on steady-state security. The proposed method uniquely integrates the statistical depth of PPF with the holistic visualization of the SSR, offering a comprehensive security assessment tool. Case studies on the IEEE 30-bus system validate the method, examining the influences of wind power penetration rate, the electrical distance of the connection point, and network parameters. Simulation results confirm that the method successfully characterizes the probabilistic nature of system security while providing an intuitive, region-based identification of system vulnerabilities and security margins. Consequently, it provides a holistic analytical tool—integrating statistical and system-wide perspectives—for security evaluation and operational guidance in power systems with high renewable energy penetration.

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Keywords

Wind power integration; probabilistic power flow; steady-state security region; bi-level optimization

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