Modified adaptive perturb and observe maximum power point tracking algorithm for higher effiency in photovoltaic system

Abstract

Due to the continuous variation in temperature and solar irradiance, P–V characteristics curve of a photovoltaic (PV) system exhibit a non-linear, time-varying Maximum Power Point (MPP). Furthermore, the tracking becomes more complicated when the PV array is partially shaded due to the presence of multiple peaks. This work proposes a Maximum Power Point Tracking (MPPT) algorithm named Modified Adaptive Perturb and Observe (MA-P&O) to address two main limitations of the conventional Perturb and Observe (P&O), namely the steady state oscillation and the divergence from the MPP. At the same time, it locates the global peak during partial shading. The MA-P&O is equipped with an intelligent mechanism to detect the steady state oscillation, and then deploy an adaptive perturbation procedure to reduce it to the minimum. Furthermore, to avoid operating voltage from diverging from its locus, a dynamic boundary condition is imposed. For partial shading, an effective checking mechanism to precisely detect partial shading occurrence is suggested. In addition, an improved set of equation is developed to detect the exact position of local peaks under partial shading. To assess its feasibility, the proposed ideas are simulated using comprehensive PV simulator. For practical validation, the algorithm is implemented in hardware using a buck-boost converter in conjunction with dSPACE DS1104 DSP board. It is demonstrated that under the dynamic irradiance and partial shading test, the MA-P&O ensures the MPPT efficiency is 99.5%. Furthermore, when evaluated against the European Standard EN 50530 test, the MA-P&O records a 98.6% efficiency; this is up to 18% higher than the conventional and other adaptive P&O. Finally, MA-P&O is tested with a tropical daily irradiance and temperature profile. It is found that MA-P&O successfully ensures 99.2%, which is on average 3% higher than the other P&O based algorithms.