SIMULATION ANALYSIS TO IMPROVED INVERTER CONTROL TECHNIQUES IN TERMS OF HOSTING CAPACITY FOR SOLAR PHOTOVOLTAIC ENERGY WITH BATTERY ENERGY STORAGE SYSTEM

The increasing penetration of solar photovoltaic (PV) systems into low-voltage distribution networks is limited by inverter-related constraints such as voltage rise, power quality degradation, and restricted hosting capacity. This work presents a simulation-based analysis of improved inverter control techniques aimed at enhancing the hosting capacity of grid-connected solar PV systems integrated with a Battery Energy Storage System (BESS). The proposed configuration consists of a PV array subjected to both steady-state and variable irradiance conditions to emulate realistic environmental variations. The variable PV output is processed through a DC–DC boost converter, whose output is stabilized using a DC-link capacitor. A bidirectional DC–DC converter interfaces the battery unit with the DC link, enabling controlled charging and discharging to mitigate PV intermittency. The inverter is connected to a single-phase 230 V grid through an LCL filter while simultaneously supplying local loads. Maximum Power Point Tracking (MPPT) is implemented for the PV-side DC–DC converter to ensure optimal energy extraction under varying irradiance. An Artificial Neural Network (ANN)- based controller is employed for inverter control to enhance dynamic response, voltage regulation, and power quality. Extensive MATLAB/Simulink simulations demonstrate that the proposed control strategy effectively improves power flow management, reduces grid stress, and increases PV hosting capacity under fluctuating generation conditions. The results validate the suitability of ANNcontrolled inverters with BESS for future high-penetration PV-integrated distribution systems.