<![CDATA[Background: The integration of utility-scale solar photovoltaic power plants requires attention to short-term power fluctuations because photovoltaic output can change rapidly due to variations in irradiance, temperature, atmospheric conditions, and cloud movement. Objective: This study aims to evaluate a SoDa-based synthetic photovoltaic power profile and optimize Battery Energy Storage System capacity for ramp-rate control of a 100 MW solar photovoltaic power plant. Methods: A quantitative simulation and optimization approach was applied. A one-minute synthetic photovoltaic power profile was generated using SoDa, evaluated for monthly consistency against NASA POWER, and analyzed under multiple ramp-rate limit scenarios. The optimum BESS power and energy capacities were determined using deterministic grid search and benchmarked against Particle Swarm Optimization (PSO). Results: The synthetic profile demonstrated adequate monthly consistency with NASA POWER (Pearson r = 0.860, rRMSE = 5.99%), confirming its suitability for pre-feasibility ramp-rate analysis. Stricter ramp-rate limits produced markedly more violations and required higher BESS capacities, ranging from 10 MW/10 MWh for moderate limits up to 20.5 MW/20.5 MWh for the most stringent scenario, with 100% compliance achieved in all cases. This framework demonstrates the practical value of synthetic data-driven BESS sizing for early-stage solar project planning in data-scarce environments. Conclusion: Stricter ramp-rate limits increase BESS capacity requirements once the minimum capacity constraint is no longer sufficient. This study contributes an auditable, transparent pre-feasibility framework that integrates synthetic data generation, and advancing the literature on data-driven energy storage sizing for utility-scale solar PV projects.]]>
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