Research on MPPT control strategy based on CCAOA algorithm

Abstract

ABSTRACT Photovoltaic arrays operating under partial shading conditions (PSCs) may exhibit multiple peaks in the power-voltage curve of the PV system output. The conventional maximum power point tracking (MPPT) algorithm cannot address the multipeak problem and demonstrates slow convergence speed, often falling into a local optimum. Consequently, this study proposes a collaborative and cosine arithmetic optimisation algorithm (CCAOA). First, a cosine factor is introduced into the mathematical optimisation. Circle chaotic mapping and cross-variance strategy were incorporated to boost the diversity and randomness within the algorithm population followed by a cooperative search strategy involving addition and subtraction to enhance the algorithm’s local search capability, thereby accelerating its convergence speed. We assessed the effectiveness of the CCAOA using six IEEE standard test functions. The CCAOA outperforms other algorithms in terms of convergence speed and accuracy. Furthermore, when applied to the MPPT control strategy, the CCAOA’s performance is validated through simulations and experiments. MPPT can be performed within approximately 0.3 to 0.4 s under static conditions, with 99.98% efficiency. Under dynamic conditions, only approximately 0.4 s is required for MPPT, thereby achieving a maximum efficiency of 99.99%. Conversely, the AOA, TSO, and PSO algorithms require over 0.4 s for MPPT and can be trapped in local optima under these two conditions. Experiments were conducted using a PV simulator and DC/DC converter, and the algorithm achieved efficiencies of 99.22%, 99.33%, and 99.54% under uniform irradiation and two PSCs, respectively.