Optimal Scheduling of a Multi-Energy Hub With Renewables, Hydrogen Vehicles, and Storage Systems

Abstract

Hydrogen energy is recognized as a prominent option of environmental sustainability, particularly through its production via electrolysis units, which makes it an essential part of the worldwide effort to reduce carbon footprints and confront climate change. The clean energy potential of hydrogen positions it at the forefront of these efforts by utilizing power-to-gas (P2G) technology. Nevertheless, the optimum functioning of multi-hub energy (MHE) systems relies on the complex interaction between different energy carriers and the increasing use of tri-generation (TG) technologies. Within this context, this research study offers a novel configuration of combined cooling, heat, and power systems (CCHPS) with highly penetrated renewable resources in the presence of hydrogen vehicles and storage units. In particular, multi-carrier markets under various uncertainties are considered which are modeled using stochastic programming methods. The main goal of this work is to develop an effective structure of multi-hub energy systems and underscore the potential of integrating hydrogen and renewable resources in achieving sustainable energy goals. The present study employs a multi-objective optimization approach (MOA) to assess the system’s operation in the context of a techno-environmental perspective. Furthermore, P2G technology has been adopted into the system to augment overall performance, reduce carbon dioxide emissions, and supply the cooling and heating demands under various uncertainties. The MOA emphasizes the main aim of decreasing operating costs, with the secondary target being the reduction of carbon dioxide emissions. The effectiveness of the MOA using the epsilon-constrained technique and Pareto solutions is examined, showing a 32.17% reduction in operating costs and a notable 79.21% reduction in CO2 emissions through the integration of Power-to-Gas (P2G) technology and the Demand Response Program (DRP).