A Sensor-Based Improved MPPT Technique Under Partial Shading Condition

The solar PV generation systems are well established in modern scenario where the problem of partial shading (PS) condition is a major threat on generation efficiency. In partially shaded PV system where multiple cells are arranged in cascaded mode, the output characteristics, e.g., power versus voltage or current versus voltage (P–V or I–V) displays multiple peaks. This results in enhancing the complexity of tracking global maximum using maximum power point tracking (MPPT) algorithms. The existing conventional MPPT algorithms like, hill climbing (HC) method, perturb and observe (P&O) method or modified P&O method, etc., used under such conditions, fail to extract maximum power due to their tendencies to lock at local maxima. Optimization-based MPPT procedures such as artificial bee colony (ABC) method, Cuckoo search (CS) algorithm and particle swarm optimization (PSO), etc., achieve global maxima detection under partial shading condition. These optimization-based algorithms require more computational load, resulting in difficulty while coming to real-time implementation. In this paper, an evolved sensor-based (SB) MPPT is projected under PS condition for detecting maximum power point (MPP) to overcome such disadvantages of optimization-based techniques. The proposed SB MPPT imposes not any computational burden on the working processor besides its simple hardware implementation. The proposed SB MPPT scheme shows comparable accuracy of tracking with excellent dynamic performance showing good tracking efficiency for considered 3S configuration while implementing in MATAB SIMUILINK atmosphere. The comparative results with existing techniques are achieved to justify the suitability of the proposed concept with relatively much easier implementation using existing available drive compatible hardware.