Dragonfly Algorithm Based Global Maximum Power Point Tracker for Photovoltaic Systems

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• 关键词：Dragonfly algorithm ; Global maximum power point tracking ; Photovoltaic systems ; Swarm intelligence
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9712
• 期：1
• 页码：211-219
• 全文大小：501 KB
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• 作者单位：Gururaghav Raman (16)
  Gurupraanesh Raman (16)
  Chakkarapani Manickam (16)
  Saravana Ilango Ganesan (16)
  
  16. Department of Electrical and Electronics Engineering, National Institute of Technology, Tiruchirappalli, 620015, India
  
• 丛书名：Advances in Swarm Intelligence
• ISBN：978-3-319-41000-5
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9712

文摘

This paper presents the application of the Dragonfly Algorithm (DA) for tracking the Global Maximum Power Point (GMPP) of a photovoltaic (PV) system. Optimization techniques employed for GMPP tracking (GMPPT) are required to be fast and efficient in order to reduce the tracking time and energy loss respectively. The DA, being a meta-heuristic algorithm with good exploration and exploitation characteristics, is a suitable candidate for this application. Due to its simplicity, the DA is implemented on a low cost microcontroller, and is proven to track the GMPP effectively under various irradiation conditions. The performance of the proposed DA based GMPPT scheme is compared with that of the conventional PSO based GMPPT scheme, and proves to be superior in terms of tracking time and energy loss during tracking.