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dc.contributor.authorAnton, Laurenţiu L.
dc.contributor.authorIlić, Marija D.
dc.date.accessioned2025-10-06T20:05:47Z
dc.date.available2025-10-06T20:05:47Z
dc.date.issued2025-09-10
dc.identifier.urihttps://hdl.handle.net/1721.1/163059
dc.description.abstractAs electric grids decarbonize and distributed energy resources (DERs) become increasingly prevalent, interconnection assessments must evolve to reflect operational variability and control flexibility. This paper highlights key modeling limitations observed in practice and reviews approaches for modeling uncertainty. It then introduces a Probabilistic Deliverability Assessment (PDA) framework designed to complement and extend existing procedures. The framework integrates scenario-based AC optimal power flow (AC OPF), corrective dispatch, and optional multi-temporal constraints. Together, these form a structured methodology for quantifying DER utilization, deliverability, and reliability under uncertainty in load, generation, and topology. Outputs include interpretable metrics with confidence intervals that inform siting decisions and evaluate compliance with reliability thresholds across sampled operating conditions. A case study on Puerto Rico’s publicly available bulk power system model demonstrates the framework’s application using minimal input data, consistent with current interconnection practice. Across staged fossil generation retirements, the PDA identifies high-value DER sites and regions requiring additional reactive power support. Results are presented through mean dispatch signals, reliability metrics, and geospatial visualizations, demonstrating how the framework provides transparent, data-driven siting recommendations. The framework’s modular design supports incremental adoption within existing workflows, encouraging broader use of AC OPF in interconnection and planning contexts.en_US
dc.publisherMultidisciplinary Digital Publishing Instituteen_US
dc.relation.isversionofhttp://dx.doi.org/10.3390/en18184832en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceMultidisciplinary Digital Publishing Instituteen_US
dc.titleProbabilistic Deliverability Assessment of Distributed Energy Resources via Scenario-Based AC Optimal Power Flowen_US
dc.typeArticleen_US
dc.identifier.citationAnton, L.L.; Ilić, M.D. Probabilistic Deliverability Assessment of Distributed Energy Resources via Scenario-Based AC Optimal Power Flow. Energies 2025, 18, 4832.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.relation.journalEnergiesen_US
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2025-09-26T14:04:49Z
dspace.date.submission2025-09-26T14:04:49Z
mit.journal.volume18en_US
mit.journal.issue18en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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