The efficiency of renewable energy sources like PV and fuel cells is improving with advancements in technology. However, maximum power point (MPP) tracking remains the most important factor for a PV-based fuel cell power system to perform at its best. The MPP of a PV system mainly depends on irradiance and temperature, while the MPP of a fuel cell depends upon factors such as the temperature of a cell, membrane water content, and oxygen and hydrogen partial pressure. With a change in any of these factors, the output is changed, which is highly undesirable in real-life applications. Thus, an efficient tracking method is required to achieve MPP. In this research, an optimal salp swarm algorithm tuned fractional order PID technique is proposed, which tracks the MPP in both steady and dynamic environments. To put that technique to the test, a system was designed comprised of a grid-connected proton exchange membrane fuel cell together with PV system and a DC-DC boost converter along with the resistive load. The output from the controller was further tuned and PWM was generated which was fed to the switch of the converter. MATLAB/SIMULINK was used to simulate this model to study the results. The response of the system under different steady and dynamic conditions was compared with those of the conventionally used techniques to validate the competency of the proposed approach in terms of fast response with minimum oscillation.