Probabilistic Modeling of Available Transfer Capability With Dynamic Transmission Reliability Margin for Renewable Energy Export and Integration
Date
Authors
Edeh, Uchenna Emmanuel
Lie, Tek Tjing
Mahmud, Md Apel
Supervisor
Item type
Journal Article
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Publisher
MDPI AG
Abstract
This paper develops a probabilistic Available Transfer Capability (ATC) framework that quantifies export headroom for renewables across transmission-distribution interfaces under time-varying uncertainty. Static transmission reliability margins can unnecessarily curtail exports. A dynamic transmission reliability margin (TRM) is embedded within ATC using rolling window statistics and adaptive confidence factor scheduling to release capacity in calm periods and tighten margins during volatile transitions. Uncertainty is modeled as net nodal power imbalance variability from load and renewable deviations, together with stochastic thermal limit fluctuations. Correlated multivariate scenarios are generated via Latin Hypercube Sampling with Iman-Conover correlation preservation and propagated through full AC power flow analysis. Validation on the IEEE 39-bus system and New Zealand’s HVDC inter-island corridor recovers 93.31 MW of usable transfer capacity on the IEEE system relative to the pooled Monte Carlo P95 constant-margin baseline, with 78.11 MW attributable to rolling window volatility tracking and 15.20 MW to adaptive confidence factor scheduling, and 59.51 MW (+7.6%) on the New Zealand corridor relative to the corresponding pooled Monte Carlo P95 baseline, with the gain arising primarily from rolling window volatility tracking. Relative to a 95% one-sided reliability target, achieved coverage is 93.9% for IEEE and 91.8% for New Zealand, translating into increased export headroom and reduced curtailment.Description
Keywords
02 Physical Sciences, 09 Engineering, 33 Built environment and design, 40 Engineering, 51 Physical sciences, available transfer capability (ATC), transmission reliability margin (TRM), Latin Hypercube Sampling (LHS), rolling window uncertainty estimation, renewable energy integration, probabilistic power flow, distribution-connected renewable export, transmission–distribution interface
Source
Energies, ISSN: 1996-1073 (Print); 1996-1073 (Online), MDPI AG, 19(8), 1864-1864. doi: 10.3390/en19081864
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© 2026 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.