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A multi-objective and robust optimization approach for sizing and placement of PV and batteries in off-grid systems fully operated by diesel generators: An Indonesian case study

  • Carlos D. Rodríguez-Gallegos*
  • , Dazhi Yang
  • , Oktoviano Gandhi
  • , Monika Bieri
  • , Thomas Reindl
  • , S. K. Panda
  • *Corresponding author for this work
  • National University of Singapore
  • Agency for Science, Technology and Research, Singapore

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes an approach to optimize sizing and placement of photovoltaic solar panels (PV) and batteries in systems which employ diesel generators (DGs) as their only source of electrical energy, forming a PV hybrid system. Three objectives have been defined: reduction of the levelized cost of electricity (economic objective); levelized CO2 equivalent life cycle emissions (environmental objective); and accumulated grid voltage deviation (grid quality objective). As this is a multi-objective optimization problem, the current state-of-the-art meta-heuristic algorithm is applied, namely non-dominated sorting genetic algorithm III. Furthermore, a robust design has been developed by considering the worst case scenarios regarding weather conditions. Subsequently, its outcome is compared with non-robust designs. Optimal pareto fronts composed of many combinations are generated with a lot of freedom to choose for a desired design. The results show the advantages of PV hybrid system in remote locations ranging from being cost effective, reducing the accumulated emissions and even to improving the grid quality.

Original languageEnglish
Pages (from-to)410-429
Number of pages20
JournalEnergy
Volume160
DOIs
StatePublished - 1 Oct 2018
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Multi-objective optimization
  • PV hybrid systems
  • Robust optimization
  • Sizing and placement optimization

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