AUTHOR=Daqaq Fatima , Ouassaid Mohammed , Kamel Salah , Ellaia Rachid , El-Naggar Mohamed F. 

TITLE=A novel chaotic flower pollination algorithm for function optimization and constrained optimal power flow considering renewable energy sources

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2022.941705

DOI=10.3389/fenrg.2022.941705

ISSN=2296-598X

ABSTRACT=This paper presents an improved chaotic flower pollination algorithm (CFPA) with a view to handle the optimal power
flow (OPF) problem integrating a hybrid wind and solar power and generate the optimal settings of generator power,
bus voltages, shunt reactive power, and tap setting transformers. In spite of the benefits of FPA, it encounters two
problems like other evolutionary algorithms: entrapment in local optima and slow convergence speed. Thus, to deal
with these drawbacks and enhance the FPA searching accuracy, a hybrid optimization approach CFPA which combines
the stochastic algorithm FPA that simulates the flowering plants process, with the chaos methodology is applied in this
manuscript. Therefore, owing to the various non-linear constraints in OPF issue, a constraint handling technique named
superiority of feasible solutions (SF) is embedded into CFPA. To confirm the performance of the chaotic FPA, a set
of different well-known benchmark functions were employed for ten diverse chaotic maps, then the best map is tested
on IEEE 30-bus and IEEE 57-bus test systems. The obtained results are analyzed statistically using Non-parametric
Wilcoxon rank-sum test in view of evaluating their significance compared to the outcomes of the state-of-the-art metaheuristic
algorithms such ant bee colony (ABC), grasshopper optimization algorithm (GOA), and dragonfly algorithm
(DA). Additionally, experimental results illustrate that combining FPA with chaotic sequences is able to accelerate the
convergence, provide better accuracy to find optimal solutions, and prove that CFPA (especially with the Sinusoidal
map) is challenging in solving complex real-world problem.