Bi-objective operation optimization of regional integrated energy system considering shared energy storage

With the development of the sharing economy, the concept of “sharing” has begun to penetrate into the power grid, and companies have begun to explore service models for shared energy storage. Based on this, this article studies the optimization technology of regional integrated energy system (RIES)...

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Bibliographic Details
Published in:Scientific reports Vol. 15; no. 1; pp. 38737 - 18
Main Authors: Li, Xiaobang, Zhu, Liying, Zhao, Liying, Zhang, Kang
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 05.11.2025
Nature Publishing Group
Nature Portfolio
Subjects:
639/166/987
639/4077/909/4101
639/4077/909/4110
Algorithms
Carbon
Collaboration
Efficiency
Electricity
Energy consumption
Energy storage
Energy utilization
Humanities and Social Sciences
Industrial development
Leasing
Maintenance costs
multidisciplinary
Operating cost
Operating costs
Operational optimization
Optimization
Regional integrated energy system
Renewable resources
Repair & maintenance
Scheduling
Science
Science (multidisciplinary)
Shared energy storage
Sharing economy
Shared energy storage
Operating cost
Regional integrated energy system
Operational optimization
ISSN:2045-2322, 2045-2322
Online Access:Get full text
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Summary:With the development of the sharing economy, the concept of “sharing” has begun to penetrate into the power grid, and companies have begun to explore service models for shared energy storage. Based on this, this article studies the optimization technology of regional integrated energy system (RIES) operation considering shared energy storage, which is conducive to promoting China’s energy strategy transformation, improving energy utilization efficiency and energy system flexibility. Firstly, the RIES fundamental structure integrating shared energy storage is constructed; Secondly, operational optimization objectives are established for both the RIES and the energy storage aggregator (ESA), aiming to minimize their respective operating costs. The constraints of the operational optimization model are analyzed; Based on the traditional sparrow search algorithm, the chaos sparrow search algorithm (COSSA) is constructed by combining Tent chaos and Gaussian mutation. Last, an illustrative case study demonstrates the effectiveness of the proposed model, showcasing a reduction in RIES operating costs of 2.912536 million dollars enabled by shared energy storage participation. As a result, our method facilitates a more efficient operation of RIES.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-025-22502-4