Novel initialization strategy: Optimizing conventional algorithms for global maximum power point tracking

Abstract

In this research, a novel initialization strategy for conventional MPPT algorithms is proposed to define the best position for the tracking process to start over the P–V curve. Consequently, the global maximum power point (GMPP) becomes the nearest or first maximum among the existing multiple MPPs under the partial shading condition (PSC). In addition, the step size of the applied conventional algorithm is minimized based on its proximity to the actual GMPP. Therefore, the tracking speed is improved, and the power loss can be reduced by the proposed approach. The major advantages of this approach are eliminating the need to modify the original algorithm, hybridizing with other algorithms, or employing any complex procedures, as in metaheuristic and optimization MPPT algorithms. Hence, it is overcoming the main drawbacks of conventional MPPT. In this work, the proposed initialization approach is applied to the simplest conventional MPPT technique, which is the perturbation and observation (P&O) algorithm, to show the enhancement in performance without the need to introduce any complex processes. MATLAB/Simulink simulation model and hardware implementation based on digital signal processing (DSP) controller TMS320F28335 are two distinct methodologies used to validate the outperformance when applying the proposed initialization technique under PSC and various weather fluctuations. The outcomes show that the proposed initialization technique was successful in extracting the maximum power peak while also improving time response, accuracy, and generating oscillations.

Keywords

• Partial shading condition (PSC)
• Global maximum power point (GMPP)
• Digital signal processing (DSP) controller
• Perturb and observe (P&O)