A Maximum Power Point Tracking Method Based on Perturb-and-Observe Combined With Particle Swarm Optimization
By Kuo-Lung Lian, J. Jhang, I. S. Tian. IEEE Journal of Photovoltaics, 2014
389 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/963c78e0027172f2341148d214c8db548137294c
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In Artificial Intelligence
- Adel El-Shahat
- Susovon Samanta
- Jinhu Lu
- Muralidhar Killi
- Ramdan B. A. Koad
- Ahmed Faheem Zobaa
- Xinghuo Yu
- Her-Terng Yau
In Electrical and Electronic Engineering
In Renewable Energy, Sustainability and the Environment
Citations in the corpus
- Modified Perturb and Observe MPPT Algorithm for Drift Avoidance in Photovoltaic Systems (2015, background): “MPPT algorithms such as fractional open-circuit voltage [4], fractional short-circuit current [4], hill-climbing [5], perturb and observe (P&O) [6]–[13], incremental conductance (IncCond) [14]–[18],”
- An Overall Distribution Particle Swarm Optimization MPPT Algorithm for Photovoltaic System Under Partial Shading (2019, methodology): “Several strategies in finding this region are documented in [24], [28], and [29], where however the detailed information of each PV panel, such”
- Simulation and Hardware Implementation of New Maximum Power Point Tracking Technique for Partially Shaded PV System Using Hybrid DEPSO Method (2015, neutral): “In [34], Lian et al.”
- A Novel MPPT Algorithm Based on Particle Swarm Optimization for Photovoltaic Systems (2017, methodology): “The PSO algorithm is an optimization technique that can be applied using multivariable function optimization with many local optimal points, as presented by Kennedy and Eberhart in 1995 [9] and [14].”