Abstract
Efficient Maximum Power Point Tracking (MPPT) techniques play a vital role in optimizing energy extraction from photovoltaic (PV) systems, primarily due to the high sensitivity of photovoltaic panel (PVP) characteristics to varying environmental parameters, including ambient temperature and solar irradiance. Conventional MPPT methods generally depend on identifying and following reference points, which are extracted from variables closely related to the Maximum Power Point (MPP) on the external current-voltage characteristics of PVP. In response to the limitations inherent to traditional approaches, this study proposes an advanced lookup table strategy to generate highly accurate reference values explicitly as functions of measured ambient temperature and solar irradiance. Initially, this research employs the two-diodes electrical circuit model to rigorously define the foundational relationships between ambient temperature, irradiance, and photovoltaic panel performance. Subsequently, contemporary advanced extraction methods based on recent academic literature were applied, enabling accurate identification of the MPP coordinates. Creating an effective lookup table requires comprehensive and detailed experimental datasets, which are often insufficient or unevenly distributed in practical scenarios. To address this challenge, the Shepard global interpolation method was integrated into the model development process, effectively mitigating datasets limitations through accurate interpolation of missing data points. This approach significantly elevates the precision and robustness of MPPT models. A comprehensive case study, conducted with real-world experimental datasets, rigorously validated the accuracy and reliability of the proposed interpolation-based lookup table. The results confirm substantial enhancements in MPPT accuracy, facilitating greater energy extraction efficiency and improved overall performance in practical photovoltaic applications.
DOI: 10.61416/ceai.v27i4.9541