Design and Performance Analysis of Bi-Directional DC-DC Buck/Boost Converter for Energy Storage Systems Using Advanced Control Strategies

International Journal of Electronics and Communication Engineering

© 2024 by SSRG - IJECE Journal

Volume 11 Issue 3

Year of Publication : 2024

Authors : E. Kalaiyarasan, S. Singaravelu

10.14445/23488549/IJECE-V11I3P106

How to Cite?

E. Kalaiyarasan, S. Singaravelu, "Design and Performance Analysis of Bi-Directional DC-DC Buck/Boost Converter for Energy Storage Systems Using Advanced Control Strategies," SSRG International Journal of Electronics and Communication Engineering, vol. 11,  no. 3, pp. 53-62, 2024. Crossref, https://doi.org/10.14445/23488549/IJECE-V11I3P106

Abstract:

The growing demand for efficient and reliable energy storage systems has led to increased research and development in the field of advanced control strategies. This research evaluates and compares the effectiveness of advanced control strategies such as Proportional and Integral controller (PI), Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) for energy storage systems employing a DC-DC bi-directional converter. ANFIS control combines the strengths of fuzzy logic and neural networks to provide a hybrid approach, particularly appealing for its adaptability and capacity to handle complex and uncertain operational environments. Energy storage systems have emerged as vital components in modern energy management, and they play a pivotal role in addressing renewable energy intermittency, enhancing grid stability, and efficiently managing energy demands. At the heart of these systems lies the DC-DC bi-directional buck/boost converter, which plays a critical component in enabling bidirectional energy transfer between the storage system (lead acid battery) and the DC source. This research employs a simulation-based methodology for a comprehensive evaluation and comparison of these control strategies. The aim is to provide valuable insights into the accuracy, stability, control complexity and suitability of various control approaches in optimizing the operation of such systems.

Keywords:

Energy Storage Systems, PI, DC-DC Bi-directional converter, Control strategies, Efficiency, Stability, Robustness, Simulation, Artificial Neural Network, Adaptive Neuro-Fuzzy Inference System.

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