Improving the performance of microgrid-based Power-to-X systems through optimization of renewable hydrogen generation

Abstract

The necessity of employing renewable energy sources within microgrid-based Power-to-X (P2X) systems has been emphasized by the imperatives of reducing global warming and fossil fuel consumption. Due to their numerous advantages, solar and wind energy have acquired prominence in contemporary power systems. However, their intermittent nature presents challenges. To overcome these challenges, energy storage devices are utilized. Batteries, however, are plagued by issues such as high maintenance needs, self-discharge, and diminishing storage capacity with age. Consequently, investigating alternatives such as hydrogen storage has become a financially viable option, especially for high-power applications. However, the intrinsically slow dynamics of hydrogen production from electricity contrast with the rapid responses of contemporary power electronic devices. This paper presents a versatile technique for optimizing hydrogen production in the presence of stochastic fluctuations in solar irradiance and wind speed. The proposed method combines a modified version of the Symbiotic Differential Whale Optimization Algorithm (m-SDWOA) with power converters to maximize production from renewable sources and electrolyzers. Using extensive simulations to demonstrate the efficacy of the proposed method by comparing its performance to that of the Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO). The results demonstrate the superior performance of the m-SDWOA-integrated method and pave the way for improved hydrogen generation in microgrid-based P2X systems.