
To meet the increasing demand of energy, photovoltaic (PV) systems are viable solution but weather changing conditions cause PV systems to fall into partial shading (PS) category which makes the maximum power point (MPP) to be non-linear. Conventional MPPT techniques effectively tracks MPP under uniform irradiance level but fails under nonuniform irradiance levels. Many bio-inspired MPPT control techniques are presented in literature but drawbacks observed in these techniques are high tracking time, oscillations at global maxima (GM) and falling in local maxima (LM) trap under PS. A novel sparrow search algorithm (SSA) based MPPT control technique is presented in this paper. Enhancement in performance of PV systems, less convergence time, little or no oscillations around global maxima (GM) are improvements observed in the proposed technique during comparative analysis with other bio inspired techniques. These enhancements are also validated with experimental setup by implementing proposed technique on low cost microcontroller. Comparison also shows the tracking of GM of proposed technique with high efficiency greater than 99.98%, up to 50% less tracking time and zero oscillations at GM under PS conditions. Superiority of proposed technique in terms of sensitivity, solidity and cogency is presented using statistical analysis.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 9 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
