Abstract
ABSTRACT This paper provides an in-depth analysis of Battery Energy Storage Systems (BESS) integration within onshore wind farms, focusing on optimal sizing, placement, and techno-economic models to mitigate the intermittent nature of wind energy. It accentuates the intricate balance between the technical and economic aspects of onshore wind farms, emphasizing the pivotal role of metrics like the Levelized Cost of Energy (LCOE) in assessing economic factors and the necessity for more comprehensive and nuanced models and metrics. The discussion encompasses challenges associated with BESS integration, such as reliability, stability, and generation uncertainty, along with exploring advanced methodologies like stochastic, fuzzy, and robust optimization and Machine Learning for load forecasting to optimize energy storage scheduling and enhance operational efficiency. The paper underscores the ongoing need for meticulous refinement in methodologies, storage solutions advancements, and grid management techniques innovations, suggesting the criticality of continuous research and development in these domains to realize sustainable and resilient onshore wind farms.
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