Improving the application of dung beetle algorithm in photovoltaic MPPT

The P-U characteristic curve of photovoltaic (PV) arrays under local shading conditions is multi-peak in nature, and the traditional maximum power point tracking (MPPT) algorithm is prone to fall into local optimality and fails to track the maximum power point. The dung beetle (DBO) optimisation algorithm is suitable for the complex multi-pole optimisation problem, and thus has been widely used in multi-peak MPPT. An improved dung beetle algorithm is proposed to address the problems of the dung beetle algorithm’s tendency to converge prematurely to a local optimum during the optimisation process, the slow convergence speed at the late iteration stage, and the low accuracy of the dung beetle algorithm. The algorithm incorporates the Fuch chaos strategy, adaptive step-size strategy and random difference variation strategy. Simulation results show that the algorithm can track the maximum power point under both static local shading and dynamic local shading conditions, and has faster convergence speed, higher accuracy and better stability, which can be applied to grid PV arrays to improve the efficiency of PV.