Adaptive Demand-Side Management Algorithm for Grid-Integrated PV-Wind-Battery-Hydrogen Systems Using Model Predictive Control

Abstract

Systems for producing green hydrogen will be essential in the move away from fossil fuels and towards technology that produces no carbon emissions. In order to undertake PV-Wind-H2 design for various hybrid configurations, this study provides a novel model for an off-grid hydrogen plant coupled with wind power, solar photovoltaic, and a battery energy storage system. This model makes use of meteorological information as well as component electrical variables. The objectives are to size and operate the systems properly in order to reach production targets while reducing H2 expenses. The direct connection of a PV-Wind-Electrolyser optimises component sizes and hydrogen generation, with the Electrolyser curves determined by the area and number of Electrolyser cells linked to photovoltaic modules. The coupling factor is increased when maximum power point (MPP) tracking is used. However, when compared to optimal PV-Wind-Electrolyser coupling, this gain is minimal. The advantage of battery-assisted electrolysis is that it minimises the size of the electrolyzer, illustrating how easy it is to run it at part loads. As a result, the photovoltaic-Wind and Electrolyzer are bigger to allow H2 generation, but the batteries work much better.