Control strategy to smooth wind power output using battery energy storage system: A review

In recent years, wind energy has increased its participation in the world energy mix. Besides its advantages, wind energy is not constant and presents undesired fluctuations, which can affect the power quality, reliability, and generation dispatch. Energy storage systems (ESS) are used to smooth the wind power output, reducing fluctuations. Within the variety of energy storage systems available, the battery energy storage system (BESS) is the most utilized to smooth wind power output. However, the capacity of BESS to compensate for fluctuations is usually exceptionally large, which will increase the capital cost of the system and reducing its suitability. To solve this problem, some studies focused on implementing control systems to optimize BESS and reduce its required size. This paper presents a literature review of the control strategies that use the battery energy storage systems to smooth the wind power output, which can guide future practical applications. Based on this review we found that most of the studies use PI, Fuzzy, and MPC control strategies but no many studies focusing on deep learning which is an arising control technology in the field of Wind Energy.

Automated summary

In recent years, wind energy has become increasingly important in the global energy structure, but its fluctuations present challenges. Battery energy storage systems are commonly used to smooth wind power output, with research focusing on optimizing control strategies to reduce costs and improve suitability. Current studies primarily utilize PI, Fuzzy, and MPC control strategies, with less emphasis on emerging deep learning technologies in the field of Wind Energy.