Rani C

Department of Electrical Engineering

School of Electrical Engineering

Vellore Campus

Derick M

Farrag M.E

Wang Y

Busawon K.

Fulltext

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

Solar Energy

IEEE Journal of Photovoltaics

Wind-Driven Optimization Technique for Estimation of Solar Photovoltaic Parameters

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

Energy Conversion and Management

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

Emerging Trends in Electrical, Electronic and Communications Engineering Lecture Notes in Electrical Engineering

Estimation of Solar Photovoltaic Parameters Using Pattern Search Algorithm

Solar PV cells usually operate at efficiency less than 20%, never generates maximum power due to change in environmental conditions such as irradiation, temperature, partial shading etc. Maximum power can be generated from PV cell with suitable tracking techniques. A modified Particle Swarm Optimization (MPSO) technique is proposed in this paper for tracking maximum power. This proposed evolutionary computation technique assures nearly zero steady state oscillation and faster convergence while tracking maximum power. The proposed PSO algorithm is tested on a CUK converter due to its higher efficiency and ripple free output. Simulations are carried out in MATLAB/SIMULINK and the computed results are validated in an experimental setup. © 2014 Published by Elsevier Ltd.

Energy Procedia

Application of Modified Particle Swarm Optimization for Maximum Power Point Tracking under Partial Shading Condition

The abundance and non-polluting nature of solar energy has aroused the interest of many researchers. This worldwide attention of photovoltaic panels has led to the need of generating accurate model for solar photovoltaic (PV) module before proceeding to the installation part. However, accurate modeling of solar PV characteristics is difficult; since the manufacturer's datasheet provides only four values such as Vmp, Imp, Voc, and Isc. Further, for accurate modeling precise estimation of model parameters at different environmental conditions are very essential. On the other hand, optimization technique is a very powerful tool to obtain solutions to complex non-linear problems. Hence, in this paper, Bacterial Foraging Algorithm is proposed to model the solar PV characteristics accurately. A new equation has been evolved to determine the values of Voc, Vmp accurately; since these values decides the closeness of the simulated characteristics. Model parameters are extracted for three different types of solar PV panels. A systematic evaluation and performance comparison of Bacterial Foraging Algorithm with other optimization techniques such as Genetic Algorithm and Artificial Immune System has been done and the best computational technique is derived based on performance criteria such as accuracy, consistency, speed of convergence and absolute error. Extensive computations are carried out for the proposed method, as well as for Genetic Algorithm and Artificial Immune System to substantiate the findings. © 2013 Elsevier Ltd.

Bacterial Foraging Algorithm based solar PV parameter estimation

Renewable and Sustainable Energy Reviews

Parameter estimation of solar photovoltaic (PV) cells: A review

An improved optimization technique for estimation of solar photovoltaic parameters

Journal	Data powered by TypesetSolar Energy
Publisher	Data powered by TypesetElsevier BV
ISSN	0038-092X
Open Access	Yes