Analysis of energy flow based matrix modeling and collaborative optimization considering different energy storage benefits for multi-energy systems

Xue Zhai, Chai Yoon Um, Ran Wang, Zijian He, Shilei Lu, Wei Feng, Yongjun Sun and Zhifu Wu

Energy, 2025, vol. 335, issue C

Abstract: The multi-energy system under optimal and irredundant planning has attracted significant influence for its critical role in improving energy efficiency, reducing emissions, and promoting sustainable development. This paper introduces an innovative matrix modeling approach based on graph theory for energy flow decoupling analysis and optimal system configuration. The benefits of incorporating energy storage devices into multi-energy systems are thoroughly discussed leading to the introduction of three system strategies. Particle swarm algorithm and Quasi-newton algorithm are employed to search the optimal solutions. A case study of multi-energy system with energy storage is presented to validate the effectiveness of the method. The results demonstrate that the novel modeling method effectively describes the energy flows of multi-energy system using dispatch factors across various components including renewable energy, energy storage and end-use demand. Peak shifting benefits of 11.5 % and 29.5 % are achieved with different energy storage configurations, reducing the required installed capacity, and preventing equipment redundancy. Additionally, compared to the base case, the standard deviation of grid power withdrawal decreases by 2.17 % and 6.52 %, respectively, demonstrating enhanced grid-friendly characteristics and sustainability potential.

Keywords: Multi energy system; Latent thermal energy storage; Matrix modeling; Graph theoretical; Optimal configuration; Peak shifting; Sustainability development (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:335:y:2025:i:c:s0360544225037314

DOI: 10.1016/j.energy.2025.138089

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