Voltage control of standalone photovoltaic – electrolyzer- fuel cell-battery energy system

Abstract

Abstract The study investigates the implementation of novel Neuro-Fuzzy controllers to maintain the power quality for standalone Photovoltaic (PV)-Electrolyzer-Fuel Cell- Battery based power generation systems. Standalone solar based power generation systems are widely becoming popular particularly in the remote areas with no connectivity to a grid. There are challenges to maintain the power output to meet the demand in these standalone systems because of the random nature of solar irradiances, variation of load and no irradiance during night time. The battery bank is required to store the excess energy for use later when required. The battery bank is integrated into a standalone system through a bidirectional DC to DC converter. However, large batteries are costly and require maintenance. Hence, electrolyzer and fuel cell are also integrated with respective DC to DC converters to make a cost effective operation. Small size battery bank is used to stabilize dc-link voltage during transients due to slow dynamics of electrolyzer and fuel cells. The maximum power point tracking (MPPT) device and perturbed and observed algorithm is used for the PV system to operate at maximum utilization. In this paper Neuro-Fuzzy controller based novel controllers are implemented to inverter and DC to DC converters for supplying quality power to both three phase and single phase loads at AC load bus. The presented results are examined through hardware-in-loop on the platform of OPAL-RT to investigate the proposed controllers in all the possible scenarios of a 1 MW standalone system. Results show that the proposed controllers improve the power quality and eliminate the frequency oscillations from the system voltage.