Reserve Deliverability-Constrained Battery Energy Storage Sizing for Renewable Power Plants Considering Cycling Degradation

High penetration of wind and photovoltaic generation requires renewable power plants to maintain not only energy delivery capability, but also prescribed upward and downward reserve capability. However, many existing battery energy storage system (BESS) sizing models evaluate reserve capability mainly through nominal power headroom or optional ancillary service revenue, which may lead to biased capacity decisions when state-of-charge limits and point of common coupling (PCC) constraints are binding. This paper proposes a reserve deliverability-constrained BESS sizing framework for renewable power plants considering cycling degradation. The proposed model represents reserve requirements explicitly and evaluates deliverable reserve by jointly considering BESS power headroom, dual-endpoint state-of-charge energy margins, and PCC export/import headroom. Real day-mapped typical scenarios and extreme stress test scenarios are integrated into the evaluation, while rainflow degradation is assessed after dispatch and included only in the candidate-level economic comparison. Numerical experiments are conducted on an equivalent large-scale renewable portfolio constructed from the 2023 nationally aggregated Belgian wind and photovoltaic generation profiles. Within the original 15-candidate set, the selected configuration increases from 300 MW/300 MWh to 1000 MW/1000 MWh when the reserve requirement rises from 5% to 15%. Under the base economic assumptions and the cycling-only degradation model, tightening the PCC export limit from 10000 to 4000 MW changes the best-performing configuration from 300 MW/300 MWh/1 h to 1000 MW/4000 MWh/4 h. Ablation results indicate that ignoring reserve requirements or deliverability constraints may lead to smaller selected capacities or overestimated feasible reserve capability. The proposed framework provides an interpretable sizing method for renewable plant-level BESS planning under prescribed reserve requirements, PCC constraints, and cycling degradation costs.