Performance evaluation and optimisation of a multistage wave-driven compressed air energy storage system

The abundant yet intermittent nature of ocean wave energy necessitates efficient storage to ensure a reliable power supply. Wave-driven compressed air energy storage (W-CAES) is a promising solution; however, conventional single-stage W-CAES designs exhibit limited energy capture and low efficiency. To address these limitations, this study proposes a multistage W-CAES system and develops an integrated model for comprehensive performance evaluation. Thermodynamic and energy flow analyses are systematically conducted to optimize the design. Additionally, a comparative evaluation is performed to examine the influence of key parameters, such as storage pressure and number of stages, on overall performance. Results indicate that increasing the number of compression stages significantly improves both capture factor and round-trip efficiency under equivalent storage conditions. In particular, a three-stage W-CAES achieves a capture factor of 9.1% (versus 1.46% for a single-stage) and a round-trip efficiency of 70.01% (up from 64.53%) at the same wave condition and storage pressure, demonstrating the benefits of the multistage approach. A Tasmanian case study demonstrates feasibility: 500 two-stage units could offset up to 20% of Tasmania’s imported energy, depending on seasons. These findings highlight the enhanced performance of multistage W-CAES and its potential to make significant contributions to renewable energy integration.

Authors

Institutions

Publication Details

Journal
Renewable Energy
Published
2025-11-06
DOI
https://doi.org/10.1016/j.renene.2025.124725
Citations
1
Primary Topic
Wave and Wind Energy Systems
Type
article
Field-Weighted Citation Impact
1.15
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Performance evaluation and optimisation of a multistage wave-driven compressed air energy storage system

Evan Franklin, Alexandre Pichard, Michael Negnevitsky, Xiaolin Wang et al.
1 citations
Renewable Energy
Wave and Wind Energy Systems
1.15
article

Performance evaluation and optimisation of a multistage wave-driven compressed air energy storage system

Evan Franklin, Alexandre Pichard, Michael Negnevitsky, Xiaolin Wang, Shujian Ma
article en
1 citations

Abstract

The abundant yet intermittent nature of ocean wave energy necessitates efficient storage to ensure a reliable power supply. Wave-driven compressed air energy storage (W-CAES) is a promising solution; however, conventional single-stage W-CAES designs exhibit limited energy capture and low efficiency. To address these limitations, this study proposes a multistage W-CAES system and develops an integrated model for comprehensive performance evaluation. Thermodynamic and energy flow analyses are systematically conducted to optimize the design. Additionally, a comparative evaluation is performed to examine the influence of key parameters, such as storage pressure and number of stages, on overall performance. Results indicate that increasing the number of compression stages significantly improves both capture factor and round-trip efficiency under equivalent storage conditions. In particular, a three-stage W-CAES achieves a capture factor of 9.1% (versus 1.46% for a single-stage) and a round-trip efficiency of 70.01% (up from 64.53%) at the same wave condition and storage pressure, demonstrating the benefits of the multistage approach. A Tasmanian case study demonstrates feasibility: 500 two-stage units could offset up to 20% of Tasmania’s imported energy, depending on seasons. These findings highlight the enhanced performance of multistage W-CAES and its potential to make significant contributions to renewable energy integration.

Renewable EnergyVol. 256
University of Tasmania (AU), Launceston General Hospital (AU), Clean Energy (United States) (US)
Openalex Percentile: Top 17%
Wave and Wind Energy Systems
1.15
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.