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A hierarchical two-level MILP optimization model for the management of grid-connected BESS considering accurate physical model

Author

Listed:
  • Nebuloni, Riccardo
  • Meraldi, Lorenzo
  • Bovo, Cristian
  • Ilea, Valentin
  • Berizzi, Alberto
  • Sinha, Snigdh
  • Tamirisakandala, Raviteja Bharadwaj
  • Raboni, Pietro

Abstract

This work proposes a new Energy Management System (EMS) for Battery Energy Storage Systems (BESS). The goal is to make a BESS profitable in the new environment considering massive use of batteries that can be foreseen in the next future, due to the predictive increase of clean energy resources. The developed EMS considers two levels of optimization. The first level models the participation of the BESS in an Ancillary Service Market and schedules the BESS. The second level, the most innovative, is responsible for optimally distributing the power set-points obtained previously among the various battery banks considering, in addition to the battery aging, also the different efficiencies of battery banks, converters, and transformers. Moreover, this second-level manages both active and reactive power flows, and losses. Both optimization algorithms have been modeled as Mixed Integer Linear Programming (MILP) and implemented in GAMS using CPLEX as a solver. The results are encouraging: compared with the common industrial practice in which the load profile is equally shared among the individual batteries within a BESS, the two new proposed EMS strategies guarantee for a long period of operation (10-years) a consistent reduction in the number of batteries replacement (around 47%), thus ensuring significant cost savings. Moreover, the proposed BESS model accurately approximates the real physical behavior of the system, leading to an average error in State-of Energy (SoE) evaluation below 0.6%, which is almost one order of magnitude lower than the ones obtained by simpler models from literature with degradation only SoE-dependent.

Suggested Citation

  • Nebuloni, Riccardo & Meraldi, Lorenzo & Bovo, Cristian & Ilea, Valentin & Berizzi, Alberto & Sinha, Snigdh & Tamirisakandala, Raviteja Bharadwaj & Raboni, Pietro, 2023. "A hierarchical two-level MILP optimization model for the management of grid-connected BESS considering accurate physical model," Applied Energy, Elsevier, vol. 334(C).
    • Handle: RePEc:eee:appene:v:334:y:2023:i:c:s0306261923000612
    DOI: 10.1016/j.apenergy.2023.120697
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    References listed on IDEAS

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    1. Matteo Spiller & Giuliano Rancilio & Filippo Bovera & Giacomo Gorni & Stefano Mandelli & Federico Bresciani & Marco Merlo, 2023. "A Model-Aware Comprehensive Tool for Battery Energy Storage System Sizing," Energies, MDPI, vol. 16(18), pages 1-24, September.
    2. Wang, Jian & Ilea, Valentin & Bovo, Cristian & Xie, Ning & Wang, Yong, 2023. "Optimal self-scheduling for a multi-energy virtual power plant providing energy and reserve services under a holistic market framework," Energy, Elsevier, vol. 278(PB).
    3. Wu, Haochi & Qiu, Dawei & Zhang, Liyu & Sun, Mingyang, 2024. "Adaptive multi-agent reinforcement learning for flexible resource management in a virtual power plant with dynamic participating multi-energy buildings," Applied Energy, Elsevier, vol. 374(C).
    4. Mehrshad Pakjoo & Luigi Piegari & Giuliano Rancilio & Silvia Colnago & Joseph Epoupa Mengou & Federico Bresciani & Giacomo Gorni & Stefano Mandelli & Marco Merlo, 2023. "A Review on Testing of Electrochemical Cells for Aging Models in BESS," Energies, MDPI, vol. 16(19), pages 1-26, September.
    5. Liu, Feng & Lv, Tao & Meng, Yuan & Li, Cong & Hou, Xiaoran & Xu, Jie & Deng, Xu, 2023. "Potential analysis of BESS and CCUS in the context of China's carbon trading scheme toward the low-carbon electricity system," Renewable Energy, Elsevier, vol. 210(C), pages 462-471.
    6. Irina Picioroaga & Madalina Luca & Andrei Tudose & Dorian Sidea & Mircea Eremia & Constantin Bulac, 2023. "Resilience-Driven Optimal Sizing of Energy Storage Systems in Remote Microgrids," Sustainability, MDPI, vol. 15(22), pages 1-16, November.
    7. Rancilio, Giuliano & Bovera, Filippo & Spiller, Matteo & Merlo, Marco & Delfanti, Maurizio, 2024. "BESS and the ancillary services markets: A symbiosis yet? Impact of market design on performance," Applied Energy, Elsevier, vol. 375(C).
    8. Park, Sung-Won & Yu, Jung-Un & Lee, Jin-Wook & Son, Sung-Yong, 2024. "A comprehensive review of battery-based power service applications considering degradation: Research status and model integration," Applied Energy, Elsevier, vol. 374(C).

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