Hybrid Digital Twin-P&O Photovoltaic Controller for Partial Shading Conditions

Photovoltaic (PV) arrays have emerged as a prominent clean and renewable energy source within modern smart grids. However, this transition in energy production brings forth new challenges, one of which is partial shading. Partial shading refers to the uneven shading pattern that occurs on a PV array, leading to multiple peaks on the PV power curve. Traditional Maximum Power Point Tracking (MPPT) methods often struggle to extract the maximum power under such conditions. This paper investigates the potential of utilizing digital twins, an emerging technology, to address this challenge. Digital twins represent virtual counterparts of physical objects—in this case, the PV array. These virtual models are engineered to estimate the maximum power point of a PV array amidst partial shading conditions. A hybrid controller that integrates a neural network-based digital twin with a conventional perturb and observe (P&O) controller is proposed. Through simulations conducted using Simulink and Python under rapidly changing irradiance conditions, the efficacy of the proposed approach is validated. Simulation results demonstrate that the hybrid controller effectively extracts the maximum power from the PV array even under partial shading conditions.