Enhanced harmony search for MPPT control in solar systems
Haojie Lu, Cheng-En Ye, Hao Yi Tsai, Yu‐Pei Huang
Abstract
• Proposed a novel and efficient algorithm to optimize HSA for MPPT under PSCs. • Normal distribution approach (NDA) can reduce 10 % sampling in both HSA and HSA+SSP. • Simplified sampling process (SSP) increased iterations by 11.78 % and decreased accuracy by 2.19 %, but reduced sampling by 59.35 %. • NHSA+SSP increased iterations by 1.89 % and decreased accuracy by 3.28 %, but reduced sampling by 62.95 %. • Offers high energy efficiency and effective tracking of maximum power under PSCs. This study introduces a novel approach to optimize the Harmony Search Algorithm (HSA) for maximum power point tracking (MPPT) in solar systems under partial shading conditions (PSCs). The enhanced HSA incorporates a Normal Distribution Approach (NDA) to refine the search process and a Simplified Sampling Process (SSP) to efficiently calculate nearby sampling points using interpolation. Experimental results demonstrate that the proposed algorithm significantly reduces the number of sampling points (by approximately 62.95 %) while maintaining comparable accuracy (around 94.5 %). The algorithm offers the benefits of high energy efficiency and effective tracking of maximum power under partial shading conditions. The optimized parameter settings provide valuable insights for future research in this field.