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A meta-heuristic method to design off-grid community electrification projects with renewable energies

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  • Ranaboldo, Matteo
  • García-Villoria, Alberto
  • Ferrer-Martí, Laia
  • Pastor Moreno, Rafael

Abstract

The design of off-grid electrification projects considering hybrid systems and distribution microgrids is a complex task that requires the use of decision support tools. Most of existing tools focus on the design of hybrid systems without defining generator locations and microgrids configuration. Recently a deterministic heuristic was developed to solve the problem. In this study we present an enhanced deterministic heuristic and then a meta-heuristic procedure for designing community off-grid electrification projects based on renewable energies considering micro-scale resource variations and a combination of independent generation points and microgrids. Both new algorithms improve performance of the previous existing procedure. The new deterministic heuristic can rapidly (in a computational time lower than 1 min) obtain a good solution. On the other hand, the proposed meta-heuristic method considerably enhances solutions obtained by the deterministic heuristic with a computational time of 1 h on a standard PC. The improvement tends to raise as the complexity of the analyzed instance increases. The proposed algorithm is a complete design tool that can efficiently support the design of stand-alone community electrification projects requiring of low computational resources.

Suggested Citation

  • Ranaboldo, Matteo & García-Villoria, Alberto & Ferrer-Martí, Laia & Pastor Moreno, Rafael, 2015. "A meta-heuristic method to design off-grid community electrification projects with renewable energies," Energy, Elsevier, vol. 93(P2), pages 2467-2482.
    • Handle: RePEc:eee:energy:v:93:y:2015:i:p2:p:2467-2482
    DOI: 10.1016/j.energy.2015.10.111
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    Cited by:

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    2. Rajanna, S. & Saini, R.P., 2016. "Development of optimal integrated renewable energy model with battery storage for a remote Indian area," Energy, Elsevier, vol. 111(C), pages 803-817.
    3. Leduchowicz-Municio, A. & López-Gozález, A. & Domenech, B. & Ferrer-Martí, L. & Udaeta, M.E.M. & Gimenes, A.L.V., 2022. "Last-mile rural electrification: Lessons learned from universalization programs in Brazil and Venezuela," Energy Policy, Elsevier, vol. 167(C).
    4. Sanajaoba Singh, Sarangthem & Fernandez, Eugene, 2018. "Modeling, size optimization and sensitivity analysis of a remote hybrid renewable energy system," Energy, Elsevier, vol. 143(C), pages 719-731.
    5. Oviedo-Cepeda, J.C. & Serna-Suárez, Ivan & Osma-Pinto, German & Duarte, Cesar & Solano, Javier & Gabbar, Hossam A., 2020. "Design of tariff schemes as demand response mechanisms for stand-alone microgrids planning," Energy, Elsevier, vol. 211(C).
    6. 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).

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