Rani C

Department of Electrical Engineering

School of Electrical Engineering

Vellore Campus

Rajesh Kumar M

Department of Communication Engineering

School of Electronics Engineering

Mathew D

Wang Y

Binns R

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

Wind-Driven Optimization Technique for Estimation of Solar Photovoltaic Parameters

IEEE Journal of Photovoltaics

Solar Energy

An improved 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

The double diode model for photovoltaic (PV) modules is currently less adopted than one-diode model because of the difficulty in the extraction of its seven unknown parameters IPV,I01,I02, Rs, Rp, a1 and a2, which is a serious inverse problem. This paper proposes application of the Fireworks Algorithm (FWA) for the accurate identification of these unknown parameters in such a way to solve effectively this modeling problem. In particular, firstly, the FWA has been comprehensively tested with two different technologies of Mono-Crystalline (SM55 &amp; SP70) and Multi-Crystalline (Kyocera200GT) PV modules. In addition, further statistical and error analysis for three different panels are exclusively carried out to validate the suitability of proposed methodology. The results of proposed algorithm are benchmarked with popular Genetic Algorithm and Particle Swarm Optimization (PSO) methods. Fitness convergence curves or FWA method for SM55, SP70 and Kyocera200GT produce very less objective function as 2.2498E−07, 2.85765E−08 and 4.0075E−08 respectively. This illustrates the wise and accurate validation of FWA method. Calculated curve-fit via FWA in agreement to datasheet curve strongly suggest the FWA can constitute the core of suitable optimization code for two diode PV parameter extraction. © 2016 Elsevier Ltd

Parameter extraction of two diode solar PV model using Fireworks algorithm

In this paper, a meta-heuristics algorithm Artificial Immune System (AIS) is used for solar PV parameter estimation. Solar PV Double diode model parameter estimation is carried out by applying the new method. Estimated parameter values are substituted in developed MATLAB model and characteristics are obtained. For performance analysis, the results obtained using AIS are compared with Genetic algorithm (GA) and Particle Swarm Optimization (PSO). For further validation of the proposed method, error graphs are plotted for two panels using AIS, GA and PSO. The results confirm that the proposed method employing AIS outperforms GA and PSO in terms of convergence characteristics and absolute error. © 2015 The Authors. Published by Elsevier Ltd.

Energy Procedia

Solar PV Modelling and Parameter Extraction Using Artificial Immune System

Journal	Data powered by TypesetIEEE Journal of Photovoltaics
Publisher	Data powered by TypesetInstitute of Electrical and Electronics Engineers (IEEE)
ISSN	2156-3381
Open Access	Yes