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A Simulation Framework for Optimal Energy Storage Sizing

Author

Listed:
  • Carlos Suazo-Martínez

    (SPEC Energy Consulting, Rosario Norte 400/51, 7561156 Las Condes, Santiago, Chile)

  • Eduardo Pereira-Bonvallet

    (Energy Centre FCFM, Universidad de Chile, Avenida Tupper 2007, 8370451 Santiago, Chile)

  • Rodrigo Palma-Behnke

    (Energy Centre FCFM, Universidad de Chile, Avenida Tupper 2007, 8370451 Santiago, Chile)

Abstract

Despite the increasing interest in Energy Storage Systems (ESS), quantification of their technical and economical benefits remains a challenge. To assess the use of ESS, a simulation approach for ESS optimal sizing is presented. The algorithm is based on an adapted Unit Commitment, including ESS operational constraints, and the use of high performance computing (HPC). Multiple short-term simulations are carried out within a multiple year horizon. Evaluation is performed for Chile's Northern Interconnected Power System (SING). The authors show that a single year evaluation could lead to sub-optimal results when evaluating optimal ESS size. Hence, it is advisable to perform long-term evaluations of ESS. Additionally, the importance of detailed simulation for adequate assessment of ESS contributions and to fully capture storage value is also discussed. Furthermore, the robustness of the optimal sizing approach is evaluated by means of a sensitivity analyses. The results suggest that regulatory frameworks should recognize multiple value streams from storage in order to encourage greater ESS integration.

Suggested Citation

  • Carlos Suazo-Martínez & Eduardo Pereira-Bonvallet & Rodrigo Palma-Behnke, 2014. "A Simulation Framework for Optimal Energy Storage Sizing," Energies, MDPI, vol. 7(5), pages 1-23, May.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:5:p:3033-3055:d:35705
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    References listed on IDEAS

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    Cited by:

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    3. Yang, Yuqing & Bremner, Stephen & Menictas, Chris & Kay, Merlinde, 2018. "Battery energy storage system size determination in renewable energy systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 109-125.
    4. Serguey A. Maximov & Gareth P. Harrison & Daniel Friedrich, 2019. "Long Term Impact of Grid Level Energy Storage on Renewable Energy Penetration and Emissions in the Chilean Electric System," Energies, MDPI, vol. 12(6), pages 1-19, March.
    5. Haas, J. & Cebulla, F. & Cao, K. & Nowak, W. & Palma-Behnke, R. & Rahmann, C. & Mancarella, P., 2017. "Challenges and trends of energy storage expansion planning for flexibility provision in low-carbon power systems – a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 603-619.
    6. Jeppesen, M. & Brear, M.J. & Chattopadhyay, D. & Manzie, C. & Dargaville, R. & Alpcan, T., 2016. "Least cost, utility scale abatement from Australia's NEM (National Electricity Market). Part 1: Problem formulation and modelling," Energy, Elsevier, vol. 101(C), pages 606-620.
    7. Han, Seungyun & Kobla Tagayi, Roland & Kim, Jaewon & Kim, Jonghoon, 2022. "Adaptive deterministic approach for optimized sizing of high-energy battery system applied in electric-powered application," Applied Energy, Elsevier, vol. 309(C).
    8. Oh, Eunsung & Son, Sung-Yong, 2018. "Energy-storage system sizing and operation strategies based on discrete Fourier transform for reliable wind-power generation," Renewable Energy, Elsevier, vol. 116(PA), pages 786-794.
    9. Abebe Tilahun Tadie & Zhizhong Guo, 2019. "Optimal Planning of Grid Scale PHES Through Characteristics-Based Large Scale Data Clustering and Emission Constrained Optimization," Energies, MDPI, vol. 12(11), pages 1-19, June.
    10. David Olave-Rojas & Eduardo Álvarez-Miranda & Alejandro Rodríguez & Claudio Tenreiro, 2017. "An Optimization Framework for Investment Evaluation of Complex Renewable Energy Systems," Energies, MDPI, vol. 10(7), pages 1-26, July.

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