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.

Balasubramanian V

Department of Information Security

School of Computer Science and Engineering

Vellore Campus

Rajasekar N

Department of Energy and Power Electronics

School of Electrical Engineering

Azharuddin S.M

Vysakh M

Thakur H.V

Babu T.S

Muralidhar K

Paul D

Jacob B

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.

&nbsp;

&nbsp;

VIT University

Energy Procedia

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

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

Solar Energy

Parameter extraction of two diode solar PV model using Fireworks algorithm

An alternative method of testing maximum power point tracking and solar Photo Voltaic (PV) system performance with a solar PV emulator is presented in this paper. Solar PV emulators are Hardware-in-Loop setup, which mimics the characteristics of a PV panel. Further, these emulators are supplementary to strenuous field testing and commercial solar PV training systems available for research prototyping. In this paper, a solar PV emulator built using a DC-DC Buck Converter and dSPACE ds1104 controller is proposed. In addition, MATLAB/SIMULINK Environment is used to construct the Mathematical Model of Solar PV Module. The proposed Solar PV Emulator has the following features: (1) ease in interfacing with faster dynamic response, (2) ability to monitor and control in real-time using a control desk, (3) higher bandwidth DC-DC buck converter, (4) stable output with lower response time, (5) lower output voltage and current ripple, and (6) capability to reproduce near accurate static and dynamic characteristics of any solar PV module. To illustrate the performance of the proposed emulator, the I-V characteristics of a shell SP70 PV panel are obtained. To further understand the dynamic and steady state behaviour of the system, experimentations are done at different operating conditions. Finally, to know the suitability of the proposed emulator for maximum power point tracking, the Perturb &amp; Observe algorithm is tested for uniform and partial shading conditions. © 2016 AIP Publishing LLC.

Journal of Renewable and Sustainable Energy

A dynamic photo voltaic emulator using dSPACE controller with high accuracy solar photo voltaic characteristics

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

International Journal of Electrical Power & Energy Systems

Design and development of a model-based hardware simulator for photovoltaic array

A photovoltaic panel emulator using a buck-boost DC/DC converter and a low cost micro-controller

Journal	Data powered by TypesetEnergy Procedia
Publisher	Data powered by TypesetElsevier BV
ISSN	1876-6102
Open Access	Yes