Assessment of maximum power point tracking algorithms on energy storage efficiency for photovoltaic power systems with battery and ultracapacitor

Abstract Hybrid energy storage systems (HESS) play an active role in the sustainability and management of energy. The integration of energy storage devices into photovoltaic (PV) systems contributes to cleaner energy generation and energy sustainability. In this study, with the aim of investigating the effects of various MPPT algorithms on the energy storage efficiency of a photovoltaic/battery/ultracapacitor (PV/Battery/UC) system where the power split is achieved via a High-Pass Filter (HPF). The performances of commercialized (Incremental Conductance-INC) and Metaheuristic (Cuckoo Search Algorithm-CSA) algorithms for PV/Battery/UC hybrid power systems were analyzed in seven (7) different cases where the irradiance value and load power changed periodically. The INC algorithm and CSA exhibited MPPT efficiency performances of 99.32% and 99.91%, respectively. The CSA required approximately 2.5% less battery current in the discharge state, while it provided approximately 1% higher current in the charging state. The oscillations in the INC algorithm caused the charging rate to increase continuously by keeping the UC in continuous charging mode. Although both algorithms exhibited fast response during case transitions, CSA outperformed the INC algorithm by providing reference DC bus voltage regulation in 0.1 s with a fluctuation of approximately 1% ( $$\\pm 0.48V$$ ).