Multi-Objective Particle Swarm optimal sizing of a renewable hybrid power plant with storage

Jean-Laurent Duchaud, Gilles Notton, Christophe Darras and Cyril Voyant

Renewable Energy, 2019, vol. 131, issue C, 1156-1167

Abstract: This paper features a Multi-Objective Particle Swarm Optimization for a power plant integrated in a micro grid. The plant modeling is flexible and can be set up for a wide range of sources, storages and loads. The model contains 12 parameters representing the size of each component which are modeled with power dependent efficiencies. The optimization goals are to reduce the annualized cost of system and the imported energy without failing to supply the load. The study is carried out in two locations (Tilos and Ajaccio) to show the problem dependence on the meteorological conditions. As a result, a pattern stands out for each site with a preferred source and a plant configuration according to the energetic autonomy wanted.

Keywords: Hybrid power-plant; Optimal sizing; Techno-economic study; Particle swarm optimization (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:131:y:2019:i:c:p:1156-1167

DOI: 10.1016/j.renene.2018.08.058

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