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A design and dispatch optimization algorithm based on mixed integer linear programming for rural electrification

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  • Moretti, Luca
  • Astolfi, Marco
  • Vergara, Claudio
  • Macchi, Ennio
  • Pérez-Arriaga, Josè Ignacio
  • Manzolini, Giampaolo

Abstract

Off-grid microgrids constitute an increasingly viable alternative to grid extension for rural electrification. Thanks to significant reductions in hardware cost, energy cost for off-grid users in areas sparsely covered by the national grid has become competitive with grid-connection once infrastructural costs are accounted for. Microgrids offer advantages also from an environmental and social point of view, featuring generation systems with high renewable penetration and facilitating the involvement of local communities in development projects. To further enhance microgrids economic competitiveness, it is necessary to devise innovative control strategies and design algorithms, that can ensure an optimal operating performance at the lowest overall cost. In this paper we present a new predictive design and dispatch optimization algorithm based on Mixed Integer Linear Programming (MILP). The new method is compared to a previously developed heuristic methodology, applying both to the design and yearly performance estimation of local microgrids, characterized on the basis of real data relative to a sub-Saharan African region. The potential advantages of including the proposed microgrid design method in a regional electrification planning model are illustrated in a realistic case example.

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  • Moretti, Luca & Astolfi, Marco & Vergara, Claudio & Macchi, Ennio & Pérez-Arriaga, Josè Ignacio & Manzolini, Giampaolo, 2019. "A design and dispatch optimization algorithm based on mixed integer linear programming for rural electrification," Applied Energy, Elsevier, vol. 233, pages 1104-1121.
    • Handle: RePEc:eee:appene:v:233-234:y:2019:i::p:1104-1121
    DOI: 10.1016/j.apenergy.2018.09.194
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    14. Akbas, Beste & Kocaman, Ayse Selin & Nock, Destenie & Trotter, Philipp A., 2022. "Rural electrification: An overview of optimization methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    15. Eduardo Sánchez-Jacob & Andrés González-García & Javier Mazorra & Pedro Ciller & Julio Lumbreras & José Ignacio Pérez-Arriaga, 2021. "Joint Optimal Planning of Electricity and Modern Energy Cooking Services Access in Nyagatare," Energies, MDPI, vol. 14(14), pages 1-24, July.
    16. Asad Ali & Muhammad Salman Fakhar & Syed Abdul Rahman Kashif & Ghulam Abbas & Irfan Ahmad Khan & Akhtar Rasool & Nasim Ullah, 2022. "Optimal Scheduling of Neural Network-Based Estimated Renewable Energy Nanogrid," Energies, MDPI, vol. 15(23), pages 1-31, November.
    17. 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).
    18. Andrea Micangeli & Davide Fioriti & Paolo Cherubini & Pablo Duenas-Martinez, 2020. "Optimal Design of Isolated Mini-Grids with Deterministic Methods: Matching Predictive Operating Strategies with Low Computational Requirements," Energies, MDPI, vol. 13(16), pages 1-19, August.
    19. Ji, Ling & Liang, Xiaolin & Xie, Yulei & Huang, Guohe & Wang, Bing, 2021. "Optimal design and sensitivity analysis of the stand-alone hybrid energy system with PV and biomass-CHP for remote villages," Energy, Elsevier, vol. 225(C).
    20. Mo, Qiu & Liu, Fang, 2020. "Modeling and optimization for distributed microgrid based on Modelica language," Applied Energy, Elsevier, vol. 279(C).
    21. García-Villoria, Alberto & Domenech, Bruno & Ferrer-Martí, Laia & Juanpera, Marc & Pastor, Rafael, 2020. "Ad-hoc heuristic for design of wind-photovoltaic electrification systems, including management constraints," Energy, Elsevier, vol. 212(C).
    22. Comodi, Gabriele & Bartolini, Andrea & Carducci, Francesco & Nagaranjan, Balamurugan & Romagnoli, Alessandro, 2019. "Achieving low carbon local energy communities in hot climates by exploiting networks synergies in multi energy systems," Applied Energy, Elsevier, vol. 256(C).
    23. Azimian, Mahdi & Amir, Vahid & Mohseni, Soheil & Brent, Alan C. & Bazmohammadi, Najmeh & Guerrero, Josep M., 2022. "Optimal Investment Planning of Bankable Multi-Carrier Microgrid Networks," Applied Energy, Elsevier, vol. 328(C).
    24. Moretti, L. & Polimeni, S. & Meraldi, L. & Raboni, P. & Leva, S. & Manzolini, G., 2019. "Assessing the impact of a two-layer predictive dispatch algorithm on design and operation of off-grid hybrid microgrids," Renewable Energy, Elsevier, vol. 143(C), pages 1439-1453.

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