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

Rajasekar N

Department of Energy and Power Electronics

School of Electrical Engineering

Vellore Campus

Sudhakar Babu T

Prasanth Ram J

Sangeetha K

Laudani A

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

Fulltext

IEEE Journal of Photovoltaics

Wind-Driven Optimization Technique for Estimation of Solar Photovoltaic Parameters

In recent years, continuous depletion of conventional energy resources and the fluctuating fuel cost have motivated research on alternative source for power generation. To effectively harvest power from the green energy resources, extensive research have been carried out in literature. Solar energy being the foremost among all other renewable energy resources has evolved as a reliable substitute for the conventional power generation. Unlike other sources, real time research on Photovoltaic (PV) Systems is a difficult assignment as it necessitates an accurate PV emulator that can precisely replicate the nonlinear characteristics of a PV cell. PV Researchers have developed emulators of different type utilizing various configurations. This paper attempts to present a comprehensive review on different PV emulator topologies so as to gather all the research activities that are scattered in this arena under a common umbrella. Further this paper provides a detailed analysis of each technique emphasizing on its (i) Realization cost (ii) Accuracy (iii) Level of complexity (iv) Sensitiveness to varying environmental conditions (v) Hardware implementation and (vi) Efficiency. © 2017 Elsevier Ltd

Renewable and Sustainable Energy Reviews

Analysis on solar PV emulators: A review

Shade conditions in PV array invoke multiple power peaks in power-voltage characteristics and as a consequence, mismatch and power loss occur. To attenuate the shade effect, various researches worldwide have been actively engaged to dynamically reconfigure the PV array via different interconnection schemes. In this paper, a new puzzle based reconfiguration scheme is proposed and tested with 5 × 5 PV array. Following physical relocation scheme, the proposed dominance square method configures the PV modules of conventional Total Cross Tied (TCT) interconnection. Thus, row and column wise rearrangement helps to attain uniform row current difference with the method. To test the validity of the proposed scheme, seven shade patterns are critically evaluated. Response for every shade pattern is analyzed with the help of I-V, P-V characteristics and their corresponding losses are evaluated. Moreover, income generated and energy saving analysis for the method is also carried out. © 2017 Elsevier Ltd

Energy Conversion and Management

Dominance square based array reconfiguration scheme for power loss reduction in solar PhotoVoltaic (PV) systems

The concept of co-power generation from the excess heat is a rapidly developing technology due to different material innovations in the field of Thermoelectric Generators (TEGs). The photovoltaic (PV) module subjected to solar irradiation utilizes photon energy but also absorbs the heat energy. The module heat is utilized to generate power by the co-generation devices such as TEG. In this paper, theoretical analysis of hybrid PV-TEG system is analyzed using different analytical methods. The performance of PV-TEG system is estimated using mathematical models of PV and TEG using MATLAB/SIMULINK environment. In this work, a novel non-concentrated flat plate PV-TEG configuration is proposed by using the multi crystalline PV connected in rear side with the Bismuth Telluride TEG. The proposed configuration results in production of 5% additional energy with an increase in overall efficiency of 6% at STC conditions. The TEG in the configuration provides cooling for the PV system and also contributes energy of 1–3% of PV rating. The efficiency of proposed PV-TEG configuration is compared with that of standalone PV by making changes in irradiation and ambient temperature. © 2018 Elsevier Ltd

The theoretical performance evaluation of hybrid PV-TEG system

Increased penetration of wind and solar PV system in Distributed Generation (DG) and isolated micro grid environment necessitates the use of maximum power point tracking method for wind and solar PV resources. Considering the change in environmental conditions and non-linearity, a variety of publications reporting various MPPT algorithms for solar and wind energy systems are put forward in recent times. But the review reports on common MPPT techniques used for solar and wind applications for hybrid power generation have not yet been reported. Hence, in this paper, conventional techniques and artificial intelligent techniques found extensively used in the power generation platform are peerly reviewed and compared. Historical MPPT methods like Perturb &amp; Observe (P&amp;O) / Hill Climbing, Incremental Conductance (INC), Fuzzy and Neural Network methods benchmarked in MPPT province are comprehensively compared in a common platform. In addition to the common existing techniques, recent swarm intelligence and bio-inspired techniques in solar PV and sensor less adaptive techniques in wind MPPT are also been reviewed provided for quality assessment. Finally an economic analysis is arrived for MPPT methods based on (i) Capacity utilization factor (ii) Cost (iii) Energy Savings (iv) payback period (v) Income generated and (vi) stability. © 2017 Elsevier Ltd

Design and overview of maximum power point tracking techniques in wind and solar photovoltaic systems: A review

Harnessing of maximum power from solar PV with the aid of maximum power point tracking (MPPT) methods is of significant importance as it contributes to better utilization of the system. Amidst the conventional MPPT methods, hill climbing (HC) and incremental conductance methods are widely recognized but they yield maximum power only under constant irradiation and utterly fail when exposed to conditions of varying irradiation levels. Besides these, they exhibit wide power fluctuations even under steady state along with poor transient characteristics under partial shading conditions which is quite probable. Therefore, a recently developed optimization technique namely, fireworks algorithm is utilized for global MPPT. Extensive simulations are performed for constant irradiation as well as partial shading condition. The obtained results are compared with existing methods to highlight the superiority of the method used in this work. © Springer India 2016.

Advances in Intelligent Systems and Computing Artificial Intelligence and Evolutionary Computations in Engineering Systems

Fireworks Algorithm-Based Maximum Power Point Tracking for Uniform Irradiation as Well as Under Partial Shading Condition

Generation of electricity from solar energy has gained worldwide acceptance due to its abundant availability and eco-friendly nature. Even though the power generated from solar looks to be attractive; its availability is subjected to variation owing to many factors such as change in irradiation, temperature, shadow etc. Hence, extraction of maximum power from solar PV using Maximum Power Point Tracking (MPPT) method was the subject of study in the recent past. Among many methods proposed, Hill Climbing and Incremental Conductance MPPT methods were popular in reaching Maximum Power under constant irradiation. However, these methods show large steady state oscillations around MPP and poor dynamic performance when subjected to change in environmental conditions. On the other hand, bio-inspired algorithms showed excellent characteristics when dealing with non-linear, non-differentiable and stochastic optimization problems without involving excessive mathematical computations. Hence, in this paper an attempt is made by applying modifications to Particle Swarm Optimization technique, with emphasis on initial value selection, for Maximum Power Point Tracking. The key features of this method include ability to track the global peak power accurately under change in environmental condition with almost zero steady state oscillations, faster dynamic response and easy implementation. Systematic evaluation has been carried out for different partial shading conditions and finally the results obtained are compared with existing methods. In addition, simulations results are validated via built-in hardware prototype. © 2015 Elsevier B.V.

Applied Soft Computing

Modified Particle Swarm Optimization technique based Maximum Power Point Tracking for uniform and under partial shading condition

This paper proposes a near accurate Solar PV Emulator using DC-DC Buck converter. A mathematical model serving as a reference is built using MATLAB/SIMULINK for emulating Solar PV characteristics. In the proposed Emulator by changing model parameter values it is possible to emulate any Solar PV characteristics. Hardware implementation is done using dSPACE ds1104 controller board and a closed loop control system is built using PI controller. The proposed Emulator has the following characteristics: 1. Fast and accurate Solar PV Emulator with easy interfacing and real-T ime control 2. Features to extend the system for other Solar PV panels 3. DC-DC Buck converter having high bandwidth. 4. Faster dynamic response and highly stable output with lower response time. 5. Lower output voltage and current ripple. Experimentations are done under different operating conditions and the results obtained are compared with the existing Emulators. © 2014 Published by Elsevier Ltd.

Energy Procedia

A Near Accurate Solar PV Emulator Using dSPACE Controller for Real-time Control

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.

Journal	Data powered by TypesetSolar Energy
Publisher	Data powered by TypesetElsevier BV
ISSN	0038-092X
Open Access	0