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A reliability-aware chance-constrained battery sizing method for island microgrid

Lookup NU author(s): Dr Marcos Santos, Dr Ilias Sarantakos, Dr Neal WadeORCiD, Dr David Greenwood



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


© 2022 The AuthorsIsland Microgrids can coordinate local energy resources, provide post-fault reliability improvements for local customers, and aggregate local power and energy resources to offer services to the wider system. A crucial component of an Island Microgrid is the battery energy storage system, which can manage local imbalances, alleviate constraints, and improve reliability by enabling post-fault islanding. A planning and sizing method is required to quantify and maximize the benefits of battery energy storage while avoiding over-investment and under-utilization. This paper combines comprehensive reliability assessment with chance-constrained convex optimization, via second-order cone programming, to optimally size energy storage within an Island Microgrid. Chance constraints are applied to the battery state-of-charge to avoid sizing the energy storage to accommodate extreme cases of uncertainty, avoiding uneconomic investment. The probability of reaching a state-of-charge constraint also indicates the likelihood that the battery energy storage system will be unable to facilitate island operation in the event of an outage, which affects the Island Microgrid reliability. The method is demonstrated on a real Austrian distribution network as part of the MERLON project. Results illustrate that an optimal trade-off can be identified between system reliability and operating cost when the probability of violating the chance constraints is 4.8%.

Publication metadata

Author(s): Huo D, Santos M, Sarantakos I, Resch M, Wade N, Greenwood D

Publication type: Article

Publication status: Published

Journal: Energy

Year: 2022

Volume: 251

Print publication date: 15/07/2022

Online publication date: 14/04/2022

Acceptance date: 09/04/2022

Date deposited: 23/05/2022

ISSN (electronic): 0360-5442

Publisher: Elsevier Ltd


DOI: 10.1016/


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Funder referenceFunder name
European Union's Horizon 2020 research and innovation programme under grant agreement No 824386