ArticleScientific reports2026
Performance comparison of MPPT controllers in a grid-connected PV system: LCOE and payback period approaches.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The utilization of renewable energy sources significantly increased in response to the growing global energy demand. Rising concerns about the environment, the photovoltaic (PV) systems emerged as prominent and widely adopted among all other renewable energies. The installation cost of PV systems is more however, the recent advancements in PV technology have made them feasible for a wide range of applications. In addition to module and inverter efficiencies, the overall efficiency of a PV system also depends upon the efficiency of the tracking method. The conventional and intelligent methods are experiencing low tracking efficiency under different irradiation and temperature conditions. PV grid integration can be done in two methods. The single stage grid connected systems can experience problems related to power quality and stability of the DC link voltage at low irradiance levels. To limit this problem, two-stage systems are preferable for maintaining a stable DC-link voltage. This research evaluates several MPPT strategies, including conventional approaches (perturbation and observation, incremental conductivity) and intelligent techniques (fuzzy logic controllers, ANFIS), and proposes a hybrid AGORNN controller, that is based on the Adaptive Grasshopper Optimization Recurrent Neural Network strategy. The performance of each method is assessed through parameters such as PV maximum power (Pmpp), DC link voltage (Vdclink), MPPT tracking efficiency η_MPPT (%), Vdc Ripple Vdcr (%), response time (Tres), overshoot Osh (%), utilization efficiency η_ut (%), THD, cost analysis, and payback period (PB). The results of simulations, which were examined using MATLAB/Simulink (R2023b), and compared with existing hybrid MPPT control methods. It exhibits that the proposed AGORNN controller is more effective than the standard and intelligent MPPT. The novel hybrid MPPT controller was examined under the conditions of STC and different irradiance and temperature, which were referred to as PTC. In STC tracking and conversion efficiencies are 99.86 and 96.55, respectively. The efficiencies under PTC are 96% and 91.50%, which ensures a promising solution to high efficiency grid-connected PV systems. The LCOE and Payback Period are also estimated and compared with other methods.
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