A novel PV array reconfiguration strategy with modified discrete slime mould algorithm considering maximizing power output and minimizing switching actions under partial shading

Partial shading condition (PSC) severely impairs the power output of photovoltaic (PV) array, causing power mismatch losses. To balance power supply reliability and economic efficiency, a novel PV array reconfiguration strategy with modified discrete slime mould algorithm (MODSMA) is proposed. Firstly, a PV array reconfiguration model is constructed to maximize power output (alleviating PSC-induced degradation) and minimize switching actions (reducing hardware wear, switching losses, and control complexity). Then, adjustable weight factors are set to adapt for flexible scenarios. Moreover, the discrete slime mould algorithm is improved based on Latin hypercube sampling-based initialization learning, intra-column random disturbance and domain search operation to meet the applicability of discrete optimization. The proposed PV array reconfiguration strategy achieves a maximum energy improvement rate (MEIR) of 35.30% for the 5×5 array. For the 6×10 array, all indicators are superior to the benchmarks with fewer switching actions. It reduces costs and computational complexity, and exhibits stronger adaptability to diverse shading scenarios.