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Day-ahead reserve determination in power systems with high renewable penetration.

Authors :
Liu, Xuan
Conejo, Antonio J.
Source :
International Journal of Electrical Power & Energy Systems. Feb2024, Vol. 156, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

We consider the operation of a power system with high renewable penetration and minimal network bottlenecks and provide a technique to determine the appropriate level of reserve to enforce. Within a daily scheduling framework, we model the production uncertainty of renewable units via scenarios and include security constraints per scenario to ensure an uneventful operation in case of failure of key thermal units. The rarely constraining network is modeled via areas with limited capacity at their interfaces. The considered decision-making framework results in a two-stage stochastic programming problem whose first stage decides on the commitment of thermal units and whose second stage reproduces, per scenario, the operation of the system with and without the failure of key thermal units. The optimal unit scheduling obtained from the proposed model implicitly identifies a generating reserve pattern that we compare with common rules used in industry for reserve identification, such as 20% or 30% of the demand. We use the Illinois 200-bus system to illustrate and computationally characterize the methodology proposed. • An economically efficient yet secure reserve determination procedure. • Renewable uncertainty is modeled via scenarios. • Security regarding unit failures is ensured via security constraints. • The resulting optimization model is tractable and does not need decomposition. • The reserve determined is superior to setting a percentage of the load as reserve. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01420615
Volume :
156
Database :
Academic Search Index
Journal :
International Journal of Electrical Power & Energy Systems
Publication Type :
Academic Journal
Accession number :
175107534
Full Text :
https://doi.org/10.1016/j.ijepes.2023.109703