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Comparison of optimization frameworks for the design of a multi-energy microgrid

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  • Rigo-Mariani, Rémy
  • Chea Wae, Sean Ooi
  • Mazzoni, Stefano
  • Romagnoli, Alessandro

Abstract

The scope of the paper is to investigate different strategies for the design of a multi-energy system considered as a systemic optimization problem. The objective is to determine the best sizes of the energy assets such as electrochemical and thermal storages, cogeneration units, solar generators and chillers. In these cases, the techno-economic optimization is a tradeoff between the operating costs and the capital expenditures in the form of integrated management and design of the system. The paper addresses the challenges of these optimization problems in two steps. The former implements generic piecewise linearization techniques based on non-linear models. That approach allows a significant reduction of the computational time for the management loop of the assets (i.e. optimal power dispatch). The latter takes into consideration the integration of that management loop in different architectures for optimal system planning. The main contribution of the paper toward filling the gap in the literature is to investigate a wide range of optimization frameworks - with bi-level optimizations (using both deterministic and evolutionary methods), Monte-Carlo simulations as well as a performant ‘all-in-one’ approach in which both sizes and controls are variables of a single mathematical problem formulation. Finally, a thorough results analysis highlights that the best solution tends to be the same whether the objective to optimize is the traditional net present value at the end of the system lifespan or the total yearly cost of ownership.

Suggested Citation

  • Rigo-Mariani, Rémy & Chea Wae, Sean Ooi & Mazzoni, Stefano & Romagnoli, Alessandro, 2020. "Comparison of optimization frameworks for the design of a multi-energy microgrid," Applied Energy, Elsevier, vol. 257(C).
  • Handle: RePEc:eee:appene:v:257:y:2020:i:c:s0306261919316691
    DOI: 10.1016/j.apenergy.2019.113982
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    Cited by:

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    4. Wang, Wenting & Yang, Dazhi & Huang, Nantian & Lyu, Chao & Zhang, Gang & Han, Xueying, 2022. "Irradiance-to-power conversion based on physical model chain: An application on the optimal configuration of multi-energy microgrid in cold climate," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
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    6. Rigo-Mariani, Rémy, 2022. "Optimized time reduction models applied to power and energy systems planning – Comparison with existing methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    7. Xia, Tian & Huang, Wujing & Lu, Xi & Zhang, Ning & Kang, Chongqing, 2020. "Planning district multiple energy systems considering year-round operation," Energy, Elsevier, vol. 213(C).
    8. Tiago P. Abud & Andre A. Augusto & Marcio Z. Fortes & Renan S. Maciel & Bruno S. M. C. Borba, 2022. "State of the Art Monte Carlo Method Applied to Power System Analysis with Distributed Generation," Energies, MDPI, vol. 16(1), pages 1-24, December.
    9. Alyssa Diva Mustika & Rémy Rigo-Mariani & Vincent Debusschere & Amaury Pachurka, 2022. "New Members Selection for the Expansion of Energy Communities," Sustainability, MDPI, vol. 14(18), pages 1-15, September.
    10. Wakui, Tetsuya & Hashiguchi, Moe & Yokoyama, Ryohei, 2021. "Structural design of distributed energy networks by a hierarchical combination of variable- and constraint-based decomposition methods," Energy, Elsevier, vol. 224(C).
    11. Zwickl-Bernhard, Sebastian & Auer, Hans, 2021. "Open-source modeling of a low-carbon urban neighborhood with high shares of local renewable generation," Applied Energy, Elsevier, vol. 282(PA).
    12. Seger, Pedro V.H. & Rigo-Mariani, Rémy & Thivel, Pierre-Xavier & Riu, Delphine, 2023. "A storage degradation model of Li-ion batteries to integrate ageing effects in the optimal management and design of an isolated microgrid," Applied Energy, Elsevier, vol. 333(C).
    13. Nastasi, Benedetto & Mazzoni, Stefano & Groppi, Daniele & Romagnoli, Alessandro & Astiaso Garcia, Davide, 2021. "Optimized integration of Hydrogen technologies in Island energy systems," Renewable Energy, Elsevier, vol. 174(C), pages 850-864.
    14. Bartolini, Andrea & Mazzoni, Stefano & Comodi, Gabriele & Romagnoli, Alessandro, 2021. "Impact of carbon pricing on distributed energy systems planning," Applied Energy, Elsevier, vol. 301(C).
    15. Eugenio Borghini & Cinzia Giannetti & James Flynn & Grazia Todeschini, 2021. "Data-Driven Energy Storage Scheduling to Minimise Peak Demand on Distribution Systems with PV Generation," Energies, MDPI, vol. 14(12), pages 1-22, June.
    16. Mo, Qiu & Liu, Fang, 2020. "Modeling and optimization for distributed microgrid based on Modelica language," Applied Energy, Elsevier, vol. 279(C).
    17. La Fata, Alice & Brignone, Massimo & Procopio, Renato & Bracco, Stefano & Delfino, Federico & Barilli, Riccardo & Ravasi, Martina & Zanellini, Fabio, 2022. "An efficient Energy Management System for long term planning and real time scheduling of flexible polygeneration systems," Renewable Energy, Elsevier, vol. 200(C), pages 1180-1201.
    18. Juan José Cartelle Barros & Manuel Lara Coira & María Pilar de la Cruz López & Alfredo del Caño Gochi & Isabel Soares, 2020. "Optimisation Techniques for Managing the Project Sustainability Objective: Application to a Shell and Tube Heat Exchanger," Sustainability, MDPI, vol. 12(11), pages 1-22, June.

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