IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i18p6546-d1237929.html

A Model-Aware Comprehensive Tool for Battery Energy Storage System Sizing

Author

Listed:
  • Matteo Spiller

    (Politecnico di Milano—Department of Energy, Via Lambruschini 4a, 20156 Milano, Italy)

  • Giuliano Rancilio

    (Politecnico di Milano—Department of Energy, Via Lambruschini 4a, 20156 Milano, Italy)

  • Filippo Bovera

    (Politecnico di Milano—Department of Energy, Via Lambruschini 4a, 20156 Milano, Italy)

  • Giacomo Gorni

    (Eni S.p.A., Renewable, New Energies and Material Science Research Center, Via Fauser 4, 28100 Novara, Italy)

  • Stefano Mandelli

    (Plenitude, Via Giuseppe Ripamonti 85, 20141 Milano, Italy)

  • Federico Bresciani

    (Eni S.p.A., Renewable, New Energies and Material Science Research Center, Via Fauser 4, 28100 Novara, Italy)

  • Marco Merlo

    (Politecnico di Milano—Department of Energy, Via Lambruschini 4a, 20156 Milano, Italy)

Abstract

This paper presents a parametric procedure to size a hybrid system consisting of renewable generation (wind turbines and photovoltaic panels) and Battery Energy Storage Systems (BESS). To cope with the increasing installation of grid-scale BESS, an innovative, fast and flexible procedure for evaluating an efficient size for this asset has been developed. The tool exploits a high-fidelity empirical model to assess stand-alone BESS or hybrid power plants under different service stacking configurations. The economic performance has been evaluated considering the revenue stacking that occurs when participating in up to four distinct energy markets and the degradation of the BESS performances due to both cycle- and calendar-aging. The parametric nature of the tool enables the investigation of a wide range of system parameters, including novel BESS control logic, market prices, and energy production. The presented outcomes detail the techno-economic performances of a hybrid system over a 20-year scenario, proposing a sensitivity analysis of both technical and economic parameters. The case study results highlight the necessity of steering BESS investment towards the coupling of RES and accurate planning of the service stacking. Indeed, the implementation of a storage system in an energy district improves the internal rate of return of the project by up to 10% in the best-case scenario. Moreover, accurate service stacking has shown a boost in revenues by up to 44% with the same degradation.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:18:p:6546-:d:1237929
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/18/6546/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/18/6546/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Matteo Moncecchi & Claudio Brivio & Stefano Mandelli & Marco Merlo, 2020. "Battery Energy Storage Systems in Microgrids: Modeling and Design Criteria," Energies, MDPI, vol. 13(8), pages 1-18, April.
    2. Mercier, Thomas & Olivier, Mathieu & De Jaeger, Emmanuel, 2023. "The value of electricity storage arbitrage on day-ahead markets across Europe," Energy Economics, Elsevier, vol. 123(C).
    3. Nicola Campagna & Vincenzo Castiglia & Rosario Miceli & Rosa Anna Mastromauro & Ciro Spataro & Marco Trapanese & Fabio Viola, 2020. "Battery Models for Battery Powered Applications: A Comparative Study," Energies, MDPI, vol. 13(16), pages 1-26, August.
    4. Nataliia Shamarova & Konstantin Suslov & Pavel Ilyushin & Ilia Shushpanov, 2022. "Review of Battery Energy Storage Systems Modeling in Microgrids with Renewables Considering Battery Degradation," Energies, MDPI, vol. 15(19), pages 1-18, September.
    5. 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).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rodriguez, Mauricio & Arcos-Aviles, Diego & Guinjoan, Francesc, 2024. "Simple fuzzy logic-based energy management for power exchange in isolated multi-microgrid systems: A case study in a remote community in the Amazon region of Ecuador," Applied Energy, Elsevier, vol. 357(C).
    2. Li, Hai & Zheng, Peng & Zhang, Tingsheng & Zou, Yingquan & Pan, Yajia & Zhang, Zutao & Azam, Ali, 2021. "A high-efficiency energy regenerative shock absorber for powering auxiliary devices of new energy driverless buses," Applied Energy, Elsevier, vol. 295(C).
    3. Superchi, Francesco & Bianchini, Alessandro, 2026. "Development of a MILP optimization framework to design grid-connected microgrids: enhancing operational synergy among wind, solar, batteries, and hydrogen storage," Renewable Energy, Elsevier, vol. 256(PG).
    4. 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.
    5. Petrelli, Marina & Fioriti, Davide & Berizzi, Alberto & Bovo, Cristian & Poli, Davide, 2021. "A novel multi-objective method with online Pareto pruning for multi-year optimization of rural microgrids," Applied Energy, Elsevier, vol. 299(C).
    6. Veenstra, Arjen T. & Mulder, Machiel, 2025. "Profitability of batteries in day-ahead and intraday electricity markets: Assessment of operation strategies with endogenous prices," Energy Economics, Elsevier, vol. 148(C).
    7. Sergio Pires Pimentel & Marcelo Nogueira Bousquet & Tiago Alves Barros Rosa & Leovir Cardoso Aleluia Junior & Enes Goncalves Marra & Jose Wilson Lima Nerys & Luciano Coutinho Gomes, 2025. "A Systematic Literature Review on Li-Ion BESSs Integrated with Photovoltaic Systems for Power Supply to Auxiliary Services in High-Voltage Power Stations," Energies, MDPI, vol. 18(13), pages 1-38, July.
    8. Yue Zhou & Hussein Obeid & Salah Laghrouche & Mickael Hilairet & Abdesslem Djerdir, 2020. "A Disturbance Rejection Control Strategy of a Single Converter Hybrid Electrical System Integrating Battery Degradation," Energies, MDPI, vol. 13(11), pages 1-19, June.
    9. Kazemi-Robati, Ehsan & Varotto, Sofia & Silva, Bernardo & Temiz, Irina, 2025. "Multiobjective energy management of multi-source offshore parks assisted with hybrid battery and hydrogen/fuel-cell energy storage systems," Applied Energy, Elsevier, vol. 377(PC).
    10. 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).
    11. Mostafa Pasandideh & Jason Kurz & Mark Apperley, 2025. "Energy Management and Edge-Driven Trading in Fractal-Structured Microgrids: A Machine Learning Approach," Energies, MDPI, vol. 18(11), pages 1-19, June.
    12. Pablo Carrasco Ortega & Pablo Durán Gómez & Julio César Mérida Sánchez & Fernando Echevarría Camarero & Ángel Á. Pardiñas, 2023. "Battery Energy Storage Systems for the New Electricity Market Landscape: Modeling, State Diagnostics, Management, and Viability—A Review," Energies, MDPI, vol. 16(17), pages 1-51, August.
    13. Zhang, Liming & Zhan, Juan & Sun, Helin & Lu, Qin, 2025. "The impact of the government's new energy storage policy on carbon emission reduction of enterprises – Evidence from China," Applied Energy, Elsevier, vol. 399(C).
    14. 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).
    15. Vladislav Volnyi & Pavel Ilyushin & Konstantin Suslov & Sergey Filippov, 2023. "Approaches to Building AC and AC–DC Microgrids on Top of Existing Passive Distribution Networks," Energies, MDPI, vol. 16(15), pages 1-26, August.
    16. 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).
    17. Aleksandr Kulikov & Pavel Ilyushin & Aleksandr Sevostyanov & Sergey Filippov & Konstantin Suslov, 2024. "Estimation of an Extent of Sinusoidal Voltage Waveform Distortion Using Parametric and Nonparametric Multiple-Hypothesis Sequential Testing in Devices for Automatic Control of Power Quality Indices," Energies, MDPI, vol. 17(5), pages 1-24, February.
    18. Ahmed Mohamed & Rémy Rigo-Mariani & Vincent Debusschere & Lionel Pin, 2024. "Operational Planning Strategies to Mitigate Price Uncertainty in Day-Ahead Market for a Battery Energy System," Post-Print hal-04628352, HAL.
    19. Selim, Alaa & Mo, Huadong & Pota, Hemanshu & Dong, Daoyi, 2026. "Adaptive optimization of BESS and grid set points: A model-free framework for energy management under dynamic tariff pricing," Energy, Elsevier, vol. 346(C).
    20. Tobias Kull & Bernd Zeilmann & Gerhard Fischerauer, 2021. "Field-Ready Implementation of Linear Economic Model Predictive Control for Microgrid Dispatch in Small and Medium Enterprises," Energies, MDPI, vol. 14(13), pages 1-23, June.

    More about this item

    Keywords

    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:18:p:6546-:d:1237929. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.