Journal article Open Access

Accelerated Particle Swarm Optimization for Photovoltaic Maximum Power Point Tracking under Partial Shading Conditions

Alshareef, Muhannad; Lin, Zhengyu; Ma, Mingyao; Cao, Wenping


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{
  "DOI": "10.3390/en12040623", 
  "container_title": "Energies", 
  "language": "eng", 
  "title": "Accelerated Particle Swarm Optimization for Photovoltaic Maximum Power Point Tracking under Partial Shading Conditions", 
  "issued": {
    "date-parts": [
      [
        2019, 
        2, 
        15
      ]
    ]
  }, 
  "abstract": "<p>This paper presents an accelerated particle swarm optimization (PSO)-based maximum power point tracking (MPPT) algorithm to track global maximum power point (MPP) of photovoltaic (PV) generation under partial shading conditions. Conventional PSO-based MPPT algorithms have common weaknesses of a long convergence time to reach the global MPP and oscillations during the searching. The proposed algorithm includes a standard PSO and a perturb-and-observe algorithm as the accelerator. It has been experimentally tested and compared with conventional MPPT algorithms. Experimental results show that the proposed MPPT method is effective in terms of high reliability, fast dynamic response, and high accuracy in tracking the global MPP.</p>", 
  "author": [
    {
      "family": "Alshareef, Muhannad"
    }, 
    {
      "family": "Lin, Zhengyu"
    }, 
    {
      "family": "Ma, Mingyao"
    }, 
    {
      "family": "Cao, Wenping"
    }
  ], 
  "volume": "2019, 12, 623.", 
  "type": "article-journal", 
  "id": "2573981"
}
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