Assessing the Energy Production Potential of a 2.6 Kw Solar PV System Using PV Syst

Abstract

This work focuses on designing a 2.6 Kw Solar PV system operating in Grid-Connected mode. A 3-Step method of efficiency evaluation is done in order to assess the energy production potential of the designed PV system. This method of assessment covers all the technical, economic and annual performance aspects of the designed PV system. Assessment is done and the results are demonstrated that forecast the energy production potential of this 2.6 Kw Solar PV system. The results will be verified using PV Syst software.

Introduction

I. INTRODUCTION

In today's world of technological developments, electricity plays a crucial role for a nation's development, for both developing and developed nations the challenge is being able to meet the growing demand for energy. According to a report from the Central Electricity Authority in 2018, it is observed that there is 8629 million units in energy supply but simultaneously 3314 megawatts in peak power demand. [1] To satisfy such demand, production needs to increase. Considering the limitations of conventional power sources, we go for alternative energy sources like solar and wind. This paper discusses on solar energy generation by designing a Grid Connected solar PV setup of 2.6 Kw power capacity in the location of Mangalpalli, Telangana. These systems are capable of feeding electricity directly into the connected grid, operating alongside conventional sources of energy. These produce clean electricity near where it's used, reducing losses and eliminating the need for batteries. [2] Their performance depends on local factors such as climate, PV Array orientation, and inverter efficiency.[3] Hence there is a need of a method to determine efficiency of such PV installations in a way where all technical, economic and annual performance aspects gets covered. For such designing and analyzing of PV systems, there are various tools available. These tools are  implemented by engineers and scientists for optimization and analysis. Such tool is PV Syst, a PC software that was developed by the University of Geneva, it offers pre-feasibility analysis, simulation and forecasting for PV systems.[4] This research paper aims to design and simulate a 2.6 Kw solar PV system to implement 3-step method for efficiency evaluation in order to assess the energy production potential of this PV system.

II. METHODOLOGY

This paper proposes a 3-Step methodology where the complete evaluation of  a PV system is divided into three important steps. They are-

A. Parameter Analysis

The Primary Block that extracts electricity out of solar irradiation is a solar cell. A solar cell produces output power according to its characteristics under different conditions. These characteristics examine Voltage, Current and Power parameters of solar cell under normal under constant and varying temperature. These characteristics help us in understanding the stability, compatibility with the power grid, efficiency and performance under different levels of irradiation. Overall, this analysis covers aspects related to solar cell and its efficiency in generating a stable efficient power.

B. Performance Analysis

Performance analysis is studying the performance of the PV system by considering power production, losses, efficiency, balance, irradiation in order to achieve valuable information about power production and estimate forecasting of aspects that enable us to gain understanding about the efficiency of the technical aspects of a PV system. All the technical aspects of this PV system like power production, performance, efficiency are covered under performance analysis.

C. Financial Analysis

Financial analysis is the study in which installation costs and operating costs of the PV setup are considered to gain calculated analysis on income variation, yearly net profit which are necessary for the planning and organizing of a solar PV system. This also gives a proper estimate on return on investment and cumulative cash flow to the user which aids in pre-feasibility of the system. Overall, this analysis covers all the monetary aspects behind establishing a solar PV system. Fig I illustrates proper understanding of this methodology below.

Hence, the above analysis clearly shows that we saved 64.238 tons of CO2 emissions this proves the feasibility of this system. So, we can say that this PV system improves air quality, supports bio diversity and ecosystem.[6]

From Financial Analysis, we can say that this system efficiently produces energy of 4121 kWh/year spent installation cost of 133,500/-INR and operating cost of 6,253.40 INR/year. Considering Project lifetime to be 20 years with start year to be 2020. According to the forecasting results of this analysis, payback period is to be 6.1 years with Return of investment rate of 569.6%. This shows that financial analysis was successful for this PV system.

Conclusion

In this paper, a 2.6 Kw Solar PV system integrated with Grid is designed and evaluated successfully using PV Syst software. It can be observed from all the analysis we have performed it proves this PV system to be stable, compatible with power grid, performs efficiently under different levels of irradiation and temperatures. Also, despite of minor losses the system is experiencing still persists to perform well and is potent in producing power for long term scale of time which makes this system financially secure and provides return on investment support and more profitability within 6.1 years of installation.

References

[1] Ministry of Power, Government of India, “Load Generation Balance Report 2018-19”, Central Electricity Authority, July 2018, pp 1-3. [2] B.S Kumar and K. Sudhakar, “ Performance evaluation of 10 MW grid connected solar photovoltaic power plant in India, “Energy Reports, Vol 1, pp. 184-192, 2015. [3] T.M.Iftakhar Uddin, Md. Abrar Saad, Husnain-Al-Bustam, Md. Zakaria Mahbub, “Computational Modeling of a GRID Connected System Using PVSYST Software”, International Journal of Scientific & Engineering Research, Vol.3, 2012. [4] C.P. Kandaswamy, P. Prabu, K. Niruba, “Solar Potential Assessment Using PVSYST Software”, International Conference on Green Computing, Communication and Conservation of Energy (ICGCE), 2013. [5] P. Yadav, N. Kumar and S.S. Chandel, “Simulation and Performance analysis of a 1 KWP Photovoltaic System using PVSyst”, 2015 International Conference on Computations of Power, Energy, Information and Communication (ICCPEIC), Chennai 2015, pp.0358-0363. [6] R. Rawat, V. Chaudhary, H.M. Dubey, “Performance Evaluation of 30.5 KWP On-Grid Solar System Using PVsyst”, Springer International Publishing 2020, Cham, https://doi.org/10.1007/978-3-030-44758-8_35 [7] Surabh sharma, C.P. Kurian, L.S. Paragond, “Solar PV System Design Using PVSyst: A Case Study of an Academic Institute”, 2018 International Conference on Control, Power, Communication and Computing Technologies (ICCPCCT), Kannur, India, 2018, pp.123-128, DOI: 10.1109/ICCPCCT.2018.8574334 [8] Davide Baschierl, Carlo Alberto Magni, Andrea Marchioni, “Comprehensive Financial modelling of Solar PV Systems”, EUPVSEC2020- 37th European Photovoltaic Solar Energy Conference and Exhibition. DOI: 10.4229/EUPVSEC20202020-7D0.8.5 [9] Kazi Abdul Kader, Florina Rahman, Islam Nahid, Zahid Abedin, “Design and Analysis of an On-Grid Solar System Using PVSyst Software for Commercial Application”, January 2022, Research gate [10] PV Syst Software https://www.pvsyst.com/ [11] Azam Khan, Bilal Alam, Wajid Ali, “Comparative Study, Design and Performance Analysis of Grid-connected Solar PV System of Two Different Places Using PVsyst Software”, Advances in Sustainability Science and Technology, Springer, July 2022. [12] Duan, S., et al. (2020). Assessment of Optimal Battery Sizing for Grid-Connected Residential Photovoltaic Systems Using PVsyst and Genetic Algorithm. IEEE Access, 8, 177656-177671. [13] Kaldellis, J. K., et al. (2019). Comprehensive Analysis of PV Performance Ratios for Optimal Module Tilt and Orientation. Sustainability, 11(22), 6353. [14] International Energy Agency (IEA). (2021). Renewables 2021: Analysis and Forecasts to 2026. IEA Publications. [15] Taherian, H., et al. (2022). Forecasting of Solar Photovoltaic Energy Generation Using Machine Learning Techniques: A Comprehensive Review. IEEE Transactions on Sustainable Energy, 13(1), 21-39.

Copyright

Copyright © 2023 Vivek Kumar Shaw, K. Srinivasa Rao. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.