期刊
ENERGY
卷 251, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2022.123978
关键词
Battery sizing; BESS; Chance-constrained programming; Distribution system; Island microgrid; Reliability; Second-order cone programming
资金
- European Union [824386]
- H2020 Societal Challenges Programme [824386] Funding Source: H2020 Societal Challenges Programme
Island Microgrids are a solution that can coordinate energy resources, improve reliability, and provide services to the wider system. The battery energy storage system plays a crucial role in managing imbalances and improving reliability. This paper proposes a planning and sizing method that combines reliability assessment and chance-constrained convex optimization to optimize the size of energy storage within an Island Microgrid.
Island 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%.(c) 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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