TY - JOUR
T1 - Optimal planning and multi-criteria evaluation of shared energy storage in multiple microgrids
T2 - interactions of diverse master-slave game pricing mechanisms and storage technologies
AU - Tang, Bao Jun
AU - Cao, Xi Lin
AU - Li, Ru
AU - Zhang, Sen
AU - Xiang, Zhi Bo
AU - Ghias, Amer M.Y.M.
AU - Shi, Wen
AU - Yang, Kejia
N1 - Publisher Copyright:
© 2026 Published by Elsevier Ltd.
PY - 2026/4/1
Y1 - 2026/4/1
N2 - 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.
AB - 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.
KW - Comprehensive benefit evaluation
KW - Hybrid electricity-hydrogen storage system
KW - Multiple microgrids
KW - Multiple pricing modes
KW - Shared energy storage
UR - https://www.scopus.com/pages/publications/105034469272
U2 - 10.1016/j.energy.2026.140576
DO - 10.1016/j.energy.2026.140576
M3 - Article
AN - SCOPUS:105034469272
SN - 0360-5442
VL - 348
JO - Energy
JF - Energy
M1 - 140576
ER -