International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 04 | Apr 2024
p-ISSN: 2395-0072
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ANFIS-Based Bi-directional Grid Connected EV Charging Station With Battery Storage System: - A Review Mr. Chandra Shekhar Sahu1, Mr. Vishwanath Prasad Kurmi2, Miss. Preeti Sahu3 1Department of Electrical Engineering, Dr. CVRU Kota Bilaspur Chhattisgarh, India
2Asst. Professor, Dept. of Electrical Engineering, Dr. CVRU Kota, Bilaspur, Chhattisgarh, India 3 Asst. Professor, Dept. of Electrical Engineering, Dr. CVRU Kota, Bilaspur, Chhattisgarh, India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - The need for contemporary transportation
challenges and opportunities associated with incorporating energy storage technologies, such as batteries and pumped hydro storage, into solar PV installations, emphasizing the role of storage in enhancing grid stability and maximizing renewable energy utilization. [9]
infrastructure is growing along with concerns about dangerous climatic changes and global warming. To resolve this issue, countries are promoting the use of Electric Vehicles (EVs). However, dependency on fossil fuel-based infrastructure for charging EVs is not efficient. An EV charging station powered by renewable energy has significant potential for EV charging. A solar-powered charging station and a BESS (Battery Energy Storage System) are essential in the present situation. It is also recommended to provide additional grid support to ensure uninterrupted power supply to the charging station without overloading the grid. ANFIS-based MPPT tracks the maximum power from the solar PV array. Generate the power and charge the EV battery and Stationary battery storage system from the PV source and also transfer power to the grid. When the PV array does not generate power and no power in the stationary battery storage system then the Grid charges the stationary battery storage system and the EV battery. The findings of the present research can also help to increase power efficiency and the power factor should be maintained.
Nwaigue et al (2019) conduct a review on the smart grid integration of solar PV systems. The study examines the challenges and potential solutions for integrating solar PV into existing power grids, focusing on aspects like grid stability, power quality, and control strategies, highlighting the need for advanced grid management techniques to optimize solar PV integration [16] Raugei et al (2017) investigate the EROI of photovoltaic as compared to fossil fuel life cycles. The study presents a comprehensive methodology for assessing EROI and provides insightful comparisons, emphasizing the favourable energy payback characteristics of solar PV systems. [21]
1.2 ANFIS-Based MPPT Techniques
1. Literature Review 1.1 Solar PV Power Generation
Kumar et al (2021) described the ANFIS-based MPPT technique for standalone solar PV systems. The proposed method utilizes ANFIS to estimate the optimal operating point, achieving efficient tracking performance and enhancing the energy yield. [10]
Islam et al (2022) provide a comprehensive review of recent advancements in solar PV technologies and applications. The study covers various aspects, including solar cell technologies, module design, integration techniques, and emerging applications, highlighting the rapid progress and potential future trends in the field. [5]
Bendary et al (2021) described the ANFIS (AdaptiveNetwork-Based Fuzzy Inference System) used for MPPT in photovoltaic systems. The proposed ANFIS-based MPPT controller adapts to changing environmental conditions, ensuring accurate tracking and improving the overall system efficiency. [11]
Colasante et al (2022) explore the role of solar PV in global energy transition scenarios. The study emphasizes the significant potential of solar PV to drive de-carbonization efforts and highlights the importance of policy frameworks and market incentives to facilitate the widespread adoption of solar PV technologies. [4]
G. Liu, et al (2020) introduced a comparative study of different ANFIS-based MPPT algorithms for standalone solar PV systems. The study evaluates the algorithms' tracking accuracy, convergence speed, and stability, providing valuable insights for selecting an optimal ANFISbased MPPT approach. [14]
K. M. Tan et al (2021) described a review on energy storage integration in solar PV systems. The study discusses the
U. Yilmaz et al (2019) A MPPT (“Maximum Power Point Tracking”) method was developed. It consists of two main
Key Words: PV source, BES Grid, EV Station, Bidirectional converter, ANFIS, PID,
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