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Optimal Scheduling of a Hydrogen-Based Energy Hub Considering a Stochastic Multi-Attribute Decision-Making Approach


Nowadays, the integration of multi-energy carriers is one of the most critical matters in smart energy systems with the aim of meeting sustainable energy development indicators. Hydrogen is referred to as one of the main energy carriers in the future energy industry, but its integration into the energy system faces different open challenges which have not yet been comprehensively studied. In this paper, a novel day-ahead scheduling is presented to reach the optimal operation of a hydrogen-based energy hub, based on a stochastic multi-attribute decision-making approach. In this way, the energy hub model is first developed by providing a detailed model of Power-to-Hydrogen (P2H) facilities. Then, a new multi-objective problem is given by considering the prosumer’s role in the proposed energy hub model as well as the integrated demand response program (IDRP). The proposed model introduces a comprehensive approach from the analysis of the historical data to the final decision-making with the aim of minimizing the system operation cost and carbon emission. Moreover, to deal with system uncertainty, the scenario-based method is applied to model the renewable energy resources fluctuation. The proposed problem is defined as mixed-integer non-linear programming (MINLP), and to solve this problem, a simple augmented e-constrained (SAUGMECON) method is employed. Finally, the simulation of the proposed model is performed on a case study and the obtained results show the effectiveness and benefits of the proposed scheme.

Funding source: This research is partially supported via AAU Bubble Project—A Novel Zero/Negative Emission Energy System Integrating Power-to-X, Allam Cycle, Carbon Capture, Utilization and Storage (CCUS) and CO2-based Energy Storage (AAU Project No.762985).
Related subjects: Applications & Pathways

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