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Optimizing Microgrid Energy Management Systems with Variable Renewable Energy Penetration: Analysis of Data Loss Effects

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Proceedings of the Future Technologies Conference (FTC) 2023, Volume 2 (FTC 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 814))

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Abstract

This study presents a multi-layered microgrid system with an optimization-based energy management system, where the impact of renewable energy penetration and data loss in battery command is investigated. Data loss in battery command can cause voltage instability, energy supply loss, and increased operational costs in microgrid systems, especially in electricity markets. The simulation results show that on average, more data loss results in higher operational costs, but there are situations where less data loss can be more detrimental to microgrid operation than higher levels of data loss. This research provides valuable insights into the effects of data loss in battery command and its potential economic impact on microgrid operation.

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Author information

Authors and Affiliations

  1. Virginia Commonwealth University, Richmond, USA

    Saikat Das & Zhifang Wang

Authors
  1. Saikat Das
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  2. Zhifang Wang
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Corresponding author

Correspondence to Saikat Das .

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Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

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Das, S., Wang, Z. (2023). Optimizing Microgrid Energy Management Systems with Variable Renewable Energy Penetration: Analysis of Data Loss Effects. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2023, Volume 2. FTC 2023. Lecture Notes in Networks and Systems, vol 814. Springer, Cham. https://doi.org/10.1007/978-3-031-47451-4_26

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