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May 6, 2026Energies0 citationsOpen Access

Comparative Lifecycle Economic Assessment of Shared Energy Storage Under Multi-Service Revenue Scenarios

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YLYang LiuQXQishan XuFZFeng Zhang

Key Points

  • To develop a lifecycle economic comparison framework for shared energy storage assets used by multiple users.
  • Established a multi-service revenue structure for evaluation.
  • Conducted case studies for lithium iron phosphate and vanadium redox flow batteries.
  • Analyzed six Chinese electricity markets across standardized revenue combinations.
  • P3 scenario yields the highest net present value (NPV) among current operational practices.
  • P6 serves as a theoretical benchmark with higher NPVs compared to P3 for both battery types.
  • Power-related services demonstrate sensitivity to rated power, while revenues from spot-market and peak shaving depend more on rated capacity.

Abstract

This study develops a lifecycle economic comparison framework for shared energy storage, in which multiple users share a common storage asset through capacity leasing. A multi-service revenue structure, including capacity leasing, spot-market arbitrage, auxiliary frequency regulation, peak shaving, and capacity compensation, is established for comparative evaluation. Case studies are conducted for lithium iron phosphate (LFP) and vanadium redox flow (VRF) batteries across six representative Chinese electricity markets and six standardized revenue-combination scenarios. The results show that, among the scenarios that more closely reflect current operating practices, P3 (capacity compensation + spot market + auxiliary frequency regulation) delivers the highest net present value (NPV). P6 combines all five revenue streams without explicitly modeling service-coupling dispatch constraints, and is therefore treated as a theoretical benchmark rather than an immediately deployable operating mode. Under this benchmark assumption, its calculated NPV is 21.1% and 41.7% higher than that of P3 for the two battery types, respectively. The study also shows that power-related services are more sensitive to rated power, while spot-market and peak-shaving revenues are more dependent on rated capacity.

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Cite This Study

Liu et al. (2026) studied this question.

synapsesocial.com/papers/69fa8e8904f884e66b530ec3https://doi.org/10.3390/en19092177
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