Optimization framework for multi-vector energy communities with uncertainty-aware energy management

Alaa Selim, Huadong Mo and Hemanshu Pota

Applied Energy, 2025, vol. 395, issue C, No S030626192500875X

Abstract: This paper presents a robust optimization framework for multi-vector energy communities that addresses key limitations of existing models by integrating electrical and thermal energy systems to enhance resource utilization and reduce grid dependency. The framework employs Mixed-Integer Linear Programming (MILP) to optimize energy flows under stochastic uncertainties and dynamic tariff structures, overcoming the scalability and adaptability challenges faced by prior approaches. A novel aspect of this work is the strategic use of Power-Type Batteries (PTBs) for short-term demand fluctuations and Energy-Type Batteries (ETBs) for long-term energy storage, enabling balanced and efficient energy management. Case studies in New South Wales and Tasmania demonstrate the framework’s scalability, effectively managing scenarios with 10, 50, and 100 feeders. Results show PTBs reduce grid reliance by up to 30 % during peak hours, while ETBs meet both electrical and thermal demands, reducing gas usage by up to 20 %. Additionally, capability-index analysis further highlights the framework’s robustness in maintaining operational efficiency across varying uncertainty levels. By integrating tailored incentive mechanisms, the framework achieves up to 30 % cost reductions, establishing a scalable, low-carbon energy management solution that significantly advances the integration and operational robustness of multi-vector energy systems.

Keywords: Multi-vector energy systems; Uncertainty-aware optimization; Energy storage management; Robust energy frameworks; Distributed energy resources; Energy dispatch (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S030626192500875X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:395:y:2025:i:c:s030626192500875x

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic

DOI: 10.1016/j.apenergy.2025.126145

Access Statistics for this article

Applied Energy is currently edited by J. Yan

More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().