This study presents a reply on a reply to comments on “Important notes on parameter estimation of the solar photovoltaic cell”, by Gnetchejo et al. [Energy Conversion and Management,https://doi.org/10.1016/j.enconman.2019.111870] introduced by Gnetchejo et al. It is noteworthy that, Gnetchejo et al. proposed their criteria in computing RMSE to prove their results in Algorithm 2 and flowchart in their reply. By inspecting the listed calculation in Algorithm 2 and flowchart, as described in this comment, one can note that their explanations are wrong. © 2019 Elsevier Ltd

Rajasekar N

Department of Energy and Power Electronics

School of Electrical Engineering

Vellore Campus

Yousri D

Elaziz M.A

Merchaoui M

Rana K.P.S

Babu T.S

Oliva D

Ram P

Alama D.F

Eteiba M.B

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Energy Conversion and Management

The inaccurate I-V curve generation in solar PV modeling introduces less efficiency and on the other hand, accurate simulation of PV characteristics becomes a mandatory obligation before experimental validation. Although many optimization methods in literature have attempted to extract accurate PV parameters, all of these methods do not guarantee their convergence to the global optimum. Hence, the authors of this paper have proposed a new hybrid Bee pollinator Flower Pollination Algorithm (BPFPA) for the PV parameter extraction problem. The PV parameters for both single diode and double diode are extracted and tested under different environmental conditions. For brevity, the I01, I02, Ipvfor double diode and I0,Ipvfor single diode models are calculated analytically where the remaining parameters ‘Rs, Rp, a1, a2’ are optimized using BPFPA method. It is found that, the proposed Bee Pollinator method has all the scope to create exploration and exploitation in the control variable to yield a less RMSE value even under lower irradiated conditions. Further for performance validation, the parameters arrived via BPFPA method is compared with Genetic Algorithm (GA), Pattern Search (PS), Harmony Search (HS), Flower Pollination Algorithm (FPA) and Artificial Bee Swarm Optimization (ABSO). In addition, various outcomes of PV modeling and different parameters influencing the accurate PV modeling are critically analyzed. © 2016 Elsevier Ltd

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

Important notes on parameter estimation of solar photovoltaic cell

A novel approach to parameter estimation of photovoltaic systems using hybridized optimizer

Static and dynamic photovoltaic models’ parameters identification using Chaotic Heterogeneous Comprehensive Learning Particle Swarm Optimizer variants

An efficient salp swarm-inspired algorithm for parameters identification of photovoltaic cell models

Reply on “Reply to comment on Important notes on parameter estimation of solar photovoltaic cell”, by Gnetchejo et al. [Energy Conversion and Management, https://doi.org/10.1016/ j.enconman.2019.111870]

Journal	Data powered by TypesetEnergy Conversion and Management
Publisher	Data powered by TypesetElsevier BV
ISSN	0196-8904
Open Access	0