A Fast MPPT Method Based on Improved Water Cycle Optimization Algorithm for Photovoltaic Systems Under Partial Shading Conditions and Load Variations

Abstract

Photovoltaic array characteristics with partial shading (PS) have multiple maximum power points (MPPs), and conventional algorithms have difficulties in tracking accurate global maximum power points (GMPPs). This study proposes a MPP tracking (MPPT) method based on improved water cycle optimization for fast-tracking the GMPP under PS conditions, along with a new strategy to enhance the convergence speed of the MPPT method during load variations. The experimental setup included a dc–dc single-ended primary inductance converter (SEPIC) and digital signal processing and control engineering (DSPACE) controller to assess the performance of the proposed method. The proposed method was also compared with the conventional water cycle optimization and six MPPT algorithms. The experimental results showed that the proposed method obtained an average tracking efficiency of 99.92% and a tracking time of 0.475 s for all PS tests. Moreover, it achieved a GMPP in a single perturbation step when the load change occurred, reducing the power loss in the photovoltaic (PV) system. The comparison showed that the proposed method performed better than the other MPPT methods in terms of tracking efficiency, convergence speed, and ease of implementation. This method could be utilized to implement developed PV systems with minimal losses.

Keywords

• Fast convergence speed
• global maximum power point (GMPP)
• load change
• maximum power point tracking (MPPT) method
• photovoltaic (PV) system
• partial shading condition