Novel Grass Hopper optimization based MPPT of PV systems for complex partial shading conditions

Abstract

Recently depletion of fossil fuels and environmental concerns triggered the extensive research on alternative energy resources, paricularly solar energy. The power of PV systems may be decreased by the oscillation, random fluctuation, and slow speed of their power tracking. To tackle these issues, a novel grasshopper optimization (GHO) technique is implemented to the MPPT controller under fast varying irradiance and PS conditions. A thorough comparison is made with well-established techniques, such as P&O, ABC, PSO, DFO, PSOGS, and CS optimization techniques under 5 different cases of weather conditions. The shortcomings of existing techniques are exposed under complex partial shading (CPS). An adaptive search and skip method is incorporated into GHO to enhance its robustness. Detailed qualitative and statistical analysis is made and results are presented to solidify the feasibility of GHO. The analysis confirms the effectiveness of the proposed GHO over existing bio-inspired MPPT techniques. Results show that the proposed GHO is highly robust with the tracking efficiency of up to 99.5%. The oscillation reduction of up to 85% is achieved along with 14–60% faster tracking. Experimental validation on low-cost setup further solidifies the practicality of the proposed technique in real-world applications.