Author
Listed:
- Tang, Bao-Jun
- Cao, Xi-Lin
- Li, Ru
- Zhang, Sen
- Xiang, Zhi-Bo
- Ghias, Amer M.Y.M.
- Shi, Wen
- Yang, Kejia
Abstract
Deploying shared energy storage across multiple microgrids leverages the complementarity of generation and load among microgrids to achieve coordinated resource allocation, thereby improving system economic performance and reducing carbon emissions. Driven by heterogeneity in pricing mechanisms and storage technologies, shared energy storage among microgrids exhibits diverse configurations. However, existing studies lack multi-dimensional comparisons of various shared storage schemes, constraining the commercialization pathways of shared energy storage. Therefore, this paper develops an interaction model applicable to multiple shared storage systems, to identify the most promising scheme. Firstly, a bi-level optimization model considering multiple pricing mechanisms is established. The operator serves as the shared storage price-maker and maximizes profit by jointly optimizing the storage utilization price and investment capacity. Each microgrid acts as the price-taker and determines cost-minimizing charging/discharging and energy scheduling strategies to respond to price signals. The model is solved using the adaptive genetic algorithm. Secondly, a comprehensive benefit assessment framework is designed based on economic, environmental, and technical indicators with the analytic hierarchy process to rank and prioritize six shared energy storage schemes, which are formed by combining three storage types (battery storage, hydrogen storage, and hybrid electricity-hydrogen storage) with two pricing mechanisms (charging/discharging power-based and capacity-based pricing). Finally, representative scenarios for three microgrids in Liaoning province are generated using k-means clustering to perform the case study. The simulation results favor the charging/discharging power-based pricing mode for advancing the shared energy storage business mode and identify hybrid electricity-hydrogen storage as offering superior comprehensive benefits relative to single-storage technologies.
Suggested Citation
Tang, Bao-Jun & Cao, Xi-Lin & Li, Ru & Zhang, Sen & Xiang, Zhi-Bo & Ghias, Amer M.Y.M. & Shi, Wen & Yang, Kejia, 2026.
"Optimal planning and multi-criteria evaluation of shared energy storage in multiple microgrids: interactions of diverse master-slave game pricing mechanisms and storage technologies,"
Energy, Elsevier, vol. 348(C).
Handle:
RePEc:eee:energy:v:348:y:2026:i:c:s0360544226006791
DOI: 10.1016/j.energy.2026.140576
Download full text from publisher
As the access to this document is restricted, you may want to
for a different version of it.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:348:y:2026:i:c:s0360544226006791. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.