A Multi-Objective Framework for Smart Energy Hubs: Leveraging Compressed Air Storage and Demand Response
Author(s):
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
In this paper, a multi-carrier energy hub that can generate and deliver electricity, heating, and cooling energy from different sources, such as wind, solar, fuel cells, batteries, and compressed air is proposed. The intelligent energy hub can also participate in electrical and thermal demand response, which aims to reduce peak demand and enhance overall system efficiency. The scheduling problem is a mixed-integer linear programming problem that seeks to minimize the system cost and carbon dioxide emissions. To obtain optimal solutions that strike a balance between cost, emissions, and decision maker's preferences, an augmented epsilon-constraint min-max fuzzy method is employed. The proposed strategy's advantages are demonstrated through a case study, where it is compared with other methods. The results show that the proposed approach effectively reduces the cost and emissions of the smart energy hub while improving the load shape and energy hub efficiency. Moreover, the results showed that the integration of compressed air systems and demand response programs enhances the performance of the smart energy hub, making it more flexible and reliable. The GAMS software is employed for the modeling and resolution of the scheduling issue.
Keywords:
Language:
English
Published:
Journal of Green Energy Research and Innovation, Volume:2 Issue: 2, Spring 2025
Pages:
1 to 25
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