An effective control approach of hybrid energy storage system based on moth flame optimization

In modern days, renewable sources increase the independence of urban energy infrastructures from remote sources and grids. In renewable energy systems (RES) systems, batteries are frequently used to close the power gap between the power supply and the load demand. Due to the variable behavior of RES and the fluctuating power requirements of the load, batteries frequently experience repeated deep cycles and uneven charging patterns. The battery's lifespan would be shortened by these actions, and increase the replacement cost. This research provides an effective control method for a solar-wind model with a battery-supercapacitor hybrid energy storage system in order to extend battery’s lives expectancy by lowering intermittent strain and high current need. Unlike traditional techniques, the suggested control scheme includes a low-pass filter (LPF) and a fuzzy logic controller (FLC). To begin, LPF reduces the fluctuating aspects of battery consumption. FLC lowers the battery's high current need while continuously monitoring the supercapacitor's level of charge. The moth flame optimization (MFO) optimizes the FLC's membership functions to get the best peak current attenuation in batteries. The proposed model is compared to standard control procedures namely rule based controller and filtration-based controller. When compared to the conventional system, the suggested method significantly reduces peak current and high power of the battery. Furthermore, when compared to standard control procedures, the suggested solution boosts supercapacitor utilization appreciably.