Reserve requirement estimation in renewable-intensive power system

Energy reserve requirements (RRs) provision is crucial for transmission system operators to ensure reliable and safe operation. Moreover, generation company strategies in the energy and service markets are based on expected power and reserve requests in real-time and day-ahead operations. An approach to evaluate three tertiary RRs is proposed in this paper, accounting for load and renewable forecast errors and generation outage. The RRs estimation is carried out by a statistical analysis based on a seasonal classification of load demand and RES production compared with a reference system. Finally, the feasibility of the estimated RRs with available margins is assessed. This approach is applied to the NREL 118-bus test system.

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Published
2024-11-03
DOI
https://doi.org/10.1109/iecon55916.2024.10905276
Citations
1
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
0.21
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article

Reserve requirement estimation in renewable-intensive power system

Giuseppe Forte, Maria Dicorato, Francesca Marasciuolo, Francisco González-Longatt et al.
1 citations
Integrated Energy Systems Optimization
0.21
article

Reserve requirement estimation in renewable-intensive power system

Giuseppe Forte, Maria Dicorato, Francesca Marasciuolo, Francisco González-Longatt, Gioacchino Tricarico
article en
1 citations

Abstract

Energy reserve requirements (RRs) provision is crucial for transmission system operators to ensure reliable and safe operation. Moreover, generation company strategies in the energy and service markets are based on expected power and reserve requests in real-time and day-ahead operations. An approach to evaluate three tertiary RRs is proposed in this paper, accounting for load and renewable forecast errors and generation outage. The RRs estimation is carried out by a statistical analysis based on a seasonal classification of load demand and RES production compared with a reference system. Finally, the feasibility of the estimated RRs with available margins is assessed. This approach is applied to the NREL 118-bus test system.

Loughborough University (GB), Renewable Energy Systems (United Kingdom) (GB), Polytechnic University of Bari (IT)
Affordable and clean energy
Openalex Percentile: Top 43%
Integrated Energy Systems Optimization
0.21
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Reserve requirement estimation in renewable-intensive power system — Giuseppe Forte, Maria Dicorato, et al. · (2024) | TGRS Research Map | TGRS