Parameter estimation of photovoltaic modules using a hybrid flower pollination algorithm

2017 ◽  
Vol 144 ◽  
pp. 53-68 ◽  
Author(s):  
Shuhui Xu ◽  
Yong Wang
Keyword(s):  
Parameter Estimation ◽  
Flower Pollination Algorithm ◽  
Photovoltaic Modules ◽  
Flower Pollination

Flower Pollination Algorithm based solar PV parameter estimation

2015 ◽  
Vol 101 ◽  
pp. 410-422 ◽  
Author(s):  
D.F. Alam ◽  
D.A. Yousri ◽  
M.B. Eteiba
Keyword(s):  
Parameter Estimation ◽  
Flower Pollination Algorithm ◽  
Solar Pv ◽  
Flower Pollination

A new hybrid bee pollinator flower pollination algorithm for solar PV parameter estimation

2017 ◽  
Vol 135 ◽  
pp. 463-476 ◽  
Author(s):  
J. Prasanth Ram ◽  
T. Sudhakar Babu ◽  
Tomislav Dragicevic ◽  
N. Rajasekar
Keyword(s):  
Parameter Estimation ◽  
Flower Pollination Algorithm ◽  
Solar Pv ◽  
Flower Pollination

Maiden application of flower pollination algorithm based tilt integral derivative controller with filter for control of electric machines

2021 ◽  
Author(s):  
Tirumalasetty Chiranjeevi ◽  
N.Ram Babu ◽  
S.K. Pandey ◽  
Raj Kumar Patel ◽  
Umesh Kumar Gupta ◽  
...  
Keyword(s):  
Electric Machines ◽  
Flower Pollination Algorithm ◽  
Flower Pollination

scholarly journals Modified Flower Pollination Algorithm for Global Optimization

Mathematics ◽  
2021 ◽  
Vol 9 (14) ◽  
pp. 1661
Author(s):  
Mohamed Abdel-Basset ◽  
Reda Mohamed ◽  
Safaa Saber ◽  
S. S. Askar ◽  
Mohamed Abouhawwash
Keyword(s):  
Global Optimization ◽  
Nonlinear Equation ◽  
Differential Evolution ◽  
Flower Pollination Algorithm ◽  
Test Cases ◽  
Test Functions ◽  
Flower Pollination ◽  
New Variant ◽  
Experimental Findings ◽  
Nonlinear Equation Systems

In this paper, a modified flower pollination algorithm (MFPA) is proposed to improve the performance of the classical algorithm and to tackle the nonlinear equation systems widely used in engineering and science fields. In addition, the differential evolution (DE) is integrated with MFPA to strengthen its exploration operator in a new variant called HFPA. Those two algorithms were assessed using 23 well-known mathematical unimodal and multimodal test functions and 27 well-known nonlinear equation systems, and the obtained outcomes were extensively compared with those of eight well-known metaheuristic algorithms under various statistical analyses and the convergence curve. The experimental findings show that both MFPA and HFPA are competitive together and, compared to the others, they could be superior and competitive for most test cases.

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