Development of arduino assisted data acquisition system for solar photovoltaic array characterization under partial shading conditions

https://doi.org/10.1016/j.compeleceng.2021.107175Get rights and content

Abstract

This research proposed the data acquisition system (DAS), which has a capability to collect real-time voltage and current at variable load resistance during an experimental characterization analysis of 3 × 3 size, photo voltaic (PV) system, under partial shading conditions (PSCs). In addition, the system is economical and minimizes the testing period for PV system characterization relative to traditional approaches. Analogue voltage and current sensors are integrated with the open-source Arduino platform to quantify and store real-time performance data in the SD card assembly. Performance parameters such as voltage and power at global maximum power point (GMPP), with minimized power loss (PL) and improved fill factor (FF) shows the effectiveness of the proposed system under the PSCs. Real-time hardware is developed and its performance is compared with the MATLAB/Simulink performance, with percentage errors as low as 0.48%, 1.95% and 1.37% under different shading case.

Introduction

Owing to the exponential growth of the world's population, energy demand is rapidly increasing regularly. Most of the electricity production leads to over-consumption of fossil fuel energy resources such as coal, gas, oil, etc. Indeed, meeting the energy needs of today's society is difficult due to technological development and the human need for electricity by 24 × 7. Fossil fuel shortages and low storage capacity are forced to seek more viable, reliable and clean energy options for the climate. amongst renewable energy sources, solar energy is deemed the most fascinating source of energy capable of balancing this difference between demand and electricity generation [1]. In addition, researchers have done impressive work to reduce its costs and have stepped up their efforts to advance PV technology in the current scenario. PV systems provide users with a safe, quiet and efficient way to produce electricity.

Apart from the various advantageous features of PV technology, maintenance costs are negligible, particularly for PV systems based on household power applications [2]. In addition, there is no need of high skills for testing and installation of up to a few kW PV systems for domestic applications. Best utilization of PV technology is anticipated in the form of users harvesting maximum energy, but there are few challenges due to climatic conditions and regular maintenance. In this context, real-time monitoring of PV system is necessary for the cost effective solution at the power plant site or remotely [3].

PV systems operate over long periods and produce performance data in terms of voltage and current during the availability of sunlight. The traditional data collection technique uses a manual method with conventional tools such as digital multi-metre and other analogue measurement devices, which is a time-consuming process. Due to rapid changes in environmental conditions, accurate measurement of performance data is difficult to record over a long time-period. Automatic-sensor-enabled data acquisition systems (DAS) thus become mandatory and provide a quick response with accuracy in real-time instead of manual measurement of the PV system performance. Monitoring of PV system parameters helps ensure system stability, to provide information on energy potential, and energy harvested for extensive analysis under climatic conditions [4].

The framework of the paper is set out as follows: The second section contained descriptions of the experimental setup. Modelling of the PV system, design of the series parallel (SP) configurations and performance indices are explained in section third. Furthermore, the results and discussions are presented in the fourth section. Conclusion, limitations and future research direction of this work are outlined at the end of the manuscript.

In the current scenario, the requirements of advanced and economic measurement tools are in high demand with real-time performance monitoring features, especially for remote location PV power plants. An embedded system based various tools/systems are available in the literature for performance parameters monitoring and recording worldwide, but economic tools attract the users and gain popularity. Details of various developed data logger systems are reported in the available literature in the aspect of their applications and the role of major associated components.

In [5], two solar PV modules of 2 × 106 Wpcapacity are tested under four halogen lamps of different power 10 W, 20 W, 50 W, and 75 W with and without MPPT system. The real-time performance parameters are recorded such as output voltage and current of PV array, battery, load, respectively, using Lab-VIEW-based graphical user interface (GUI). During the study, the installed system is used only for the transient behaviour of performance parameters. In [6], a study on transient behaviour of real-time performance data of a Hybrid Wind/PV/battery system is conducted. For extensive transient analysis is shown for PV system (2 × 130 Wp) voltage and current are recorded during peak irradiation levels from 200- 800W/m2 along with wind speed (7 m/s at 05:00 PM) and output power (500 Wp) for 24 h. The power flow analysis between PV/WT/Battery system is investigated efficiently. The authors have designed an open-source Arduino based low-cost data logger and utilized it smartly for measurement of input-output side real-time transient response of PV system and DC load parameters such as voltage, current, and power, respectively, under environmental temperature [7]. In [8], the Lab-VIEW-based GUI is used for live monitoring of electrical output (P-V and I-V curves) of the PV module (20.78 V and 1.81A). The proposed system is validated for one day during the measurement of short circuit current (Isc) under clear and cloudy weather from 8:00 AM- 18:00 PM. Recorded data are validated with the industrial data logger DT80 and found satisfactory performance with percentage error in the range from 0- 1.4%. The hardware system is developed for solar PV tracking and the real-time recorded data is stored in the micro SD card for transient analysis concerning time during the climatic changes [9]. Two ATmega328 microcontrollers are utilized for real-time monitoring of PV system's performance data and voltage, current acquisition under climatic conditions (variable sunlight and temperature). The parameters of the PV module are explicitly imported into the excel sheet from the Lab-VIEW applications for transient analysis of temperature, water flow rate, solar irradiance, etc. [10].

In [11], the authors have developed an I-V curve tracer for 5 W PV modules and tested at different irradiation (640 W/m2, 700 W/m2, 820 W/m2, and 900 W/m2) and temperature (30 °C, 35 °C, 43 °C, and 49 °C) levels. The robustness of the developed system is tested by monitoring experimental data during six months of study under climatic conditions. Real-time electrical and climatic parameters such as voltage, current, temperature, humidity, etc. are recorded through micro SD card with ten minutes sample time interval rate [12]. In [13], a comprehensive study on the effect of dust accumulation on PV system performance is conducted. Dust and cleaned PV modules are taken to investigate the power loss, FF, efficiency under variable irradiance: 560 W/m2, 590 W/m2, 620 W/m2, and 800 W/m2 through developed I-V curve tracer. Implemented data logger to monitor real-time PV system performance parameters in terms of Isc and open circuit voltage(Voc). The measured data are stored in the SD card for critical analysis based on weather scenarios [14]. Open source Arduino-UNO based data logger system is developed for solar PV system characterization in [15]. The real-time data such as voltage, current, and power are plotted to describe the behaviour of the I-V and P-V curves at 1100 W/m2, 72 °C and identified maximum voltage, current 15 V, 1.3A, respectively. The obtained results are validated using DMM and found closely agreed.

In [16], authors have developed a dual-axis solar tracker system for performance enhancement and compared with conventional systems. Real-time voltage and current transient responses are shown using analogue sensors and ATMega328 microcontroller for extensive analysis. Moreover, the efficiency of the proposed model is found to be higher (36.26%) than the conventional system. Another research approach in [17], the authors have developed Zig-Bee based wireless network to transmit real-time performance data (power: 8 W) of H-bridge motor control-assisted DC motor systems are used to change the tilt angle of the solar PV module for continuous monitoring of the sun tracking from 09:00 AM- 03:00 PM on 29–30 April 2017. In [18], the authors implemented a wireless PV module-monitoring system based on IEC 61,724 standard specifications. The implemented module is effective for measuring electrical and meteorological data for real-time analysis. Raspberry-Pi is used as a server for wirelessly transmitting the data frequently at 433 MHz. Low power consumption and high transmission costs make the system reasonable and effective at the industrial level. The experimental results show the uncertainty in the measurement of less than 1% for all parameters.

In [19], wireless data transmission system is established for real-time monitoring of PV system. In addition, a self-developed data logger is incorporated to store the electrical output of the PV system along with illumination and temperature. In [20], built open source Arduino platform dual axis solar tracker framework. The proposed technique increased the power output by 35.15% compared to the static PV panels. Electrical performance is observed in terms of short-circuit current and open-circuit voltage for detailed comparison studies. However, the research is not based on the characterization of the PV system. In [21,22], A real-time PV system monitoring device based on the Internet of Things (IoT) is being created. In addition, solar PV output in terms of voltage and current is reported to plot I-V curve under static conditions. Important environmental parameters, e.g., wind speed, temperature and sunlight, are assessed for considerable interest. For the literature review, various related research manuscripts are considered and salient points of the study are highlighted in Table 1 as,

Following are the major contributions of the proposed work:

  • The proposed device is economical and implemented with easy-to-use, user-friendly resources such as ATmega 328 micro-controller, sensors and external micro SD card assembly to characterize real-time P-V and I-V curves of a 3 × 3 PV system (manufacturer Spark Solar Pvt. Ltd.) under different PSCs.

  • The system is found to be reliable, sensitive and time-efficient compared to the manual process during the analysis. The MATLAB/Simulink analysis is performed to verify the performance and robustness of the method.

  • The established system is accomplished to provide the current-voltage (I-V) and power-voltage (P-V) curves with fewer transients compared to the study conducted in [22].

Output parameters such as FF, GMPP and PL can be calculated and displayed based on real-time data monitoring. As a challenge, this research direction is available to new learners.

Section snippets

Experimental setup: specifications and use of supportive components

The developed experimental setup consists mainly of three sections for measuring the performance of the solar PV array system. In the first section: the solar PV array consisting of 3 × 3 PV modules is arranged in SP connections for performance analysis. In the second section: data logger with micro SD card-shield for measuring and storing output parameters comprised voltage, current sensors, and pairing of the Arduino performance measurement system. In the third section: Variable resistance

Modelling of PV module

The efficiency of the PV system depends on its modelling and it is challenging task due to non-linear behaviour. In literature, various PV modules are availably based on single and double diode approaches. But, single diode PV model is gaining popularity due to easy implementation with less parameters involvement [23]. The single diode based electrical equivalent circuit of PV model is shown in Fig. 5(a), which constitutes a current source Iirr connected anti-parallel to the diode, D1is series

Results and discussion

Extensive MATLAB/Simulation and experimental studies are conducted and shown to represent shadowing cases-6(a)-(c) on the SP configured PV array system. During the analysis, the irradiation levels are deemed 810 W/m2and 435 W/m2 for the experimental and simulation studies. The low level/non-uniform irradiation value (435 W/m2) is believed to be a shading condition for 3 × 3 size SP configured PV array. The performance outcomes of this extensive study as follows,

  • Characterization of PV system

Conclusion, limitations and future research direction

The developed DAS is compatible with an open-source Arduino platform with real-time PV system voltage and current storage capacity during the experimental analysis. The system performance in terms of accuracy and reliability is validated comprehensively with MATLAB/Simulink study. Following key points are observed,

Real-time 3 × 3 size PV performance data are calculated and analysed using the ATmega-328 microcontroller and stored in an external micro SD card to characterize the P-V and I-V

CRediT authorship contribution statement

Rupendra Kumar Pachauri: Conceptualization, Methodology, Software, Data curtion, Writing – original draft preparation, Visualization, Investigation, Supervision, Validation, Writing – review & editing. Om Prakash Mahela: Conceptualization, Methodology, Software, Writing – review & editing. Baseem Khan: Conceptualization, Methodology, Software, Writing – review & editing. Ashok Kumar: Visualization, Investigation. Sunil Agarwal: Software, Validation. Hassan Haes Alhelou: Writing – review &

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

In this paper, the research work done by Hassan Haes Alhelou was supported in part by Science Foundation Ireland (SFI) under the SFI Strategic Partnership Programme Grant Number SFI/15/SPP/E3125 and additional funding provided by the UCD Energy Institute. The opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the Science Foundation Ireland. In addition, research work done by Jianbo Bai was

Rupendra Kumar Pachauri is currently associated with UPES, Dehradun, India. He has received his B. Tech from UPTU, India in 2006. He has received his M. Tech degree from Aligarh Muslim University, India in 2009 and pH. D degree in Renewable Energy from G. B. University, India in 2016. His-fields of research are Solar Energy and Smart grid operations.

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    Rupendra Kumar Pachauri is currently associated with UPES, Dehradun, India. He has received his B. Tech from UPTU, India in 2006. He has received his M. Tech degree from Aligarh Muslim University, India in 2009 and pH. D degree in Renewable Energy from G. B. University, India in 2016. His-fields of research are Solar Energy and Smart grid operations.

    Om Prakash Mahela (Senior Member, IEEE) received B.E. degree from the COTE, Udaipur, India, in 2002. M. Tech. degree from Jagannath University, Jaipur in 2013 and the Ph.D. degree from IIT Jodhpur, India in 2018. He is associated with Rajasthan Rajya Vidhyut Prasaran Nigam Ltd. His-research interests include power quality, power system planning and PV system-grid integration.

    Baseem Khan (Member, IEEE) received the Bachelor of Engineering degree in electrical engineering from RGPV, Bhopal, India, in 2008, and the M. Tech and pH. D degrees in electrical engineering from the MANIT, Bhopal, in 2010 and 2014, respectively. He is currently associated with Hawassa University, Ethiopia. His-research interests include power system restructuring, meta-heuristic optimization techniques, renewable energy integration.

    Ashok Kumar was born in Bikaner rajasthan india in 1990. He received the B. Tech degree from the Marudhar Engineering college, Bikaner Rajasthan, India in 2012 and M. Tech degree from Apex institute of technology Jaipur Rajasthan India in 2020. He is working as assistant professor with the Engineering College Bikaner. His-research includes power quality and renewable energy integration.

    Sunil Agarwal is presently working as an Assistant Professor in Apex Institute of Engineering and Technology. I have completed my Engineering in Electrical stream and Postgraduate in Power System. Current research interests include power quality problems, fault analysis, power electronics, Flexible AC transmission systems and many research papers have been published in national and international journal and conferences in these areas.

    Hassan Haes Alhelou (Senior Member, IEEE) is with the School of Electrical and Electronic Engineering, University College Dublin, Ireland. Also, He is a faculty member at Tishreen University, Lattakia, Syria. He has published more than 120 research papers in the high quality peer-reviewed journals and international conferences. His-major research interests are Power system dynamics, Power system operation and control.

    Jianbo Bai got his Ph.D. degree from Southeast University in 2006. Now he is associated with Hohai University, China since 2016. His-current research interests include comprehensive and highly efficient use of solar energy, simulation and optimizing of PV power stations, etc. He has hosted many projects supported by NNS Foundation of China and Jiangsu Province in China.

    Reviews processed and recommended for publication by Associate Editor Dr. S. Smys

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