Coordinated Scheduling of EES–CAES Hybrid Energy Storage Under Minimum Inertia Requirements

In response to the reduced system inertia and increased frequency security risks in high-renewable power systems, as well as the limitations of single energy storage technologies, a coordinated optimal scheduling method for electrochemical energy storage (EES) and compressed air energy storage (CAES) considering the minimum inertia requirement (MIR) is proposed. The method constructs a coordination framework, leveraging the fast response of EES and the sustained support and equivalent inertia contribution of CAES. An MIR evaluation model considering RoCoF and frequency nadir constraints is established, and the inertia deficit is converted into fast reserve demand, forming an inertia–reserve coupling mechanism. To address nonlinear frequency constraints, an adaptive piecewise linearization method is adopted to transform the model into a mixed-integer linear programming problem. Case studies show that, compared with the benchmark hybrid energy storage scheduling strategy without inertia–reserve coordination, the proposed method reduces thermal generation cost by 4.5% and renewable curtailment by 74.8%. Moreover, the proposed APWL method improves computational efficiency by 47% compared with the conventional PWL method.

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Publication Details

Journal
Sustainability
Published
2026-04-17
DOI
https://doi.org/10.3390/su18084011
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Coordinated Scheduling of EES–CAES Hybrid Energy Storage Under Minimum Inertia Requirements

Shun Yao, Feng Wu, Linjun Shi, Yiming Zhang
Sustainability
Microgrid Control and Optimization
article

Coordinated Scheduling of EES–CAES Hybrid Energy Storage Under Minimum Inertia Requirements

Shun Yao, Feng Wu, Linjun Shi, Yiming Zhang
article en

Abstract

In response to the reduced system inertia and increased frequency security risks in high-renewable power systems, as well as the limitations of single energy storage technologies, a coordinated optimal scheduling method for electrochemical energy storage (EES) and compressed air energy storage (CAES) considering the minimum inertia requirement (MIR) is proposed. The method constructs a coordination framework, leveraging the fast response of EES and the sustained support and equivalent inertia contribution of CAES. An MIR evaluation model considering RoCoF and frequency nadir constraints is established, and the inertia deficit is converted into fast reserve demand, forming an inertia–reserve coupling mechanism. To address nonlinear frequency constraints, an adaptive piecewise linearization method is adopted to transform the model into a mixed-integer linear programming problem. Case studies show that, compared with the benchmark hybrid energy storage scheduling strategy without inertia–reserve coordination, the proposed method reduces thermal generation cost by 4.5% and renewable curtailment by 74.8%. Moreover, the proposed APWL method improves computational efficiency by 47% compared with the conventional PWL method.

SustainabilityVol. 18(8)
Hohai University (CN), Shanghai Electric (China) (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 6%
Microgrid Control and Optimization
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