@inproceedings{0fb287eb62ad42b59223a8a6127db779,
title = "Real-time Operation Model for Energy Management System of Battery Energy Storage System-Case Study: The School of Sinntorp",
abstract = "This paper shows the real-time operation model of Energy Management System (EMS) for control of Battery Energy Storage System (BESS). These models are needed to manage uncertain electricity loads, delivery of peak shaving and frequency regulation services and the BESS financial feasibility. The delivery of these services result in economic return for the resource owner and increased grid flexibility. The Energy Management System implemented in this work uses the electricity load and grid frequency data as inputs to generate BESS control commands that deliver the said services. The validation simulation performed on the School of Sinntorp in Sweden returns an annual return on investment of 22% for the BESS and inverter. Implementation of storage systems was shown to expedite the adoption of renewable energy while also solving the challenges that this adoption on scale poses. This active adoption is pivotal in achieving the UN sustainable developmental goals (SDGs) for energy.",
keywords = "BESS, EMS, Electricity Grid, Peak Shaving, Renewable Integration",
author = "Hamza Shafique and Archer, {Dan Eric} and Robert Eriksson and Tjernberg, {Lina Bertling}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022 ; Conference date: 12-06-2022 Through 15-06-2022",
year = "2022",
doi = "10.1109/PMAPS53380.2022.9810577",
language = "English",
series = "2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022",
}
