Novel hybrid modified krill herd algorithm and fuzzy controller based MPPT to optimally tune the member functions for PV system in the three-phase grid-connected mode

Abstract

For the technical, economic and environmental benefits, using solar energy has increased worldwide, especially with the help of photovoltaic (PV) systems. The amount of energy produced in PV systems is dependent on environmental circumstances such as temperature and solar irradiance. In order to extract the maximum possible power in PV systems and increase the efficiency under various environmental conditions, maximum power point tracking (MPPT) controllers have been proposed. To fine-tune the control parameters of the proposed MPPT approach, the fuzzy controller and modified krill herd (MKH) algorithm are jointly employed. Rule base and membership functions (MFs) are two important parameters for implementing the FLC and need to be fine-tune appropriately. However, in the condition where precise information concerning the system is not available, the fine-tuning of these parameters cannot be accurate. To cope with this problem, the MKH algorithm is used to optimize the scaling factors of MFs. To improve the stability of the system under study, the PV system is used with the storage system at the same time. This hybrid system can deal with the stochastic nature of the PV system and provide more stability in all atmospheric conditions. The proposed MPPT method is confirmed by comparing it with other well-known techniques.

Keywords: Battery; Fuzzy logic control; Krill herd algorithm; MPPT; Photovoltaic (PV).