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This chapter introduces four newly developed Maximum Power Point Tracking (MPPT) approaches aimed at significantly enhancing the tracking performance of photovoltaic (PV) systems and overcoming the common challenges faced by existing MPPT techniques. The first proposed approach focuses on adapting to temperature variations, improving tracking speed, and minimizing steady-state fluctuations at the maximum power point (MPP). This method integrates seamlessly with existing MPPT algorithms like P&O and INC, offering an average efficiency improvement from 98.8% to around 99.1%, along with reduced response times and negligible power ripples. The second approach optimizes power extraction under varying irradiance and load conditions while minimizing steady-state oscillations. It outperforms traditional methods in terms of convergence speed and tracking efficiency, achieving efficiencies from 99.4 to 99.76% and tracking times significantly faster than P&O and INC methods. The third approach, ASSTA, utilizes a novel tracking mechanism based on the Theta angle, showing superior tracking accuracy and reducing power loss, especially during rapid climatic changes. ASSTA achieves tracking times under 0.017 s and efficiencies between 99.1 and 99.84%. The final approach enhances tracking performance under extreme temperature variations, addressing key limitations of conventional MPPT methods. This strategy decreases tracking time, eliminates steady-state ripples, and improves tracking efficiency by up to 9.04% compared to existing methods like INC and P&O.

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Principle and Simulation Investigation of The Newly Proposed MPPT Approaches

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  • 发表日期：

    2025年

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  • Abdelkhalek Chellakhi,
  • Said El Beid

摘要

This chapter introduces four newly developed Maximum Power Point Tracking (MPPT) approaches aimed at significantly enhancing the tracking performance of photovoltaic (PV) systems and overcoming the common challenges faced by existing MPPT techniques. The first proposed approach focuses on adapting to temperature variations, improving tracking speed, and minimizing steady-state fluctuations at the maximum power point (MPP). This method integrates seamlessly with existing MPPT algorithms like P&O and INC, offering an average efficiency improvement from 98.8% to around 99.1%, along with reduced response times and negligible power ripples. The second approach optimizes power extraction under varying irradiance and load conditions while minimizing steady-state oscillations. It outperforms traditional methods in terms of convergence speed and tracking efficiency, achieving efficiencies from 99.4 to 99.76% and tracking times significantly faster than P&O and INC methods. The third approach, ASSTA, utilizes a novel tracking mechanism based on the Theta angle, showing superior tracking accuracy and reducing power loss, especially during rapid climatic changes. ASSTA achieves tracking times under 0.017 s and efficiencies between 99.1 and 99.84%. The final approach enhances tracking performance under extreme temperature variations, addressing key limitations of conventional MPPT methods. This strategy decreases tracking time, eliminates steady-state ripples, and improves tracking efficiency by up to 9.04% compared to existing methods like INC and P&O.