Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology (Deemed to be University), Kattankulathur, Tamil Nadu, India.
National Institute of Wind Energy, Chennai, India.
F1000Res. 2023 Aug 31;12:1068. doi: 10.12688/f1000research.134731.1. eCollection 2023.
Developing countries like India are rapidly transitioning from traditional energy sources to sustainable energy sources, due to the increase in demand and the depletion of fossil fuels. Grid-connected photovoltaic (PV) systems attract many investors, organizations, and institutions for deployment. This article studies and compares the performance evaluations of three 52-kW PV plants installed at an educational institution, SRMIST (SRM Institute of Science and Technology), in Tamil Nadu, India. This site receives an annual average temperature of 28.5°C and an average global horizontal irradiation of 160 kWh/m2/m. The prediction model for the 52-kW power plant is obtained using solar radiation, temperature, and wind speed. Linear regression model-based prediction equations are derived using the Minitab 16.2.1 software, and the results are compared with the real-time AC energy yield acquired from the three 52-kW plants for the year 2020. Furthermore, this 52-kW plant is designed using PVsyst V7.1.8 version software. The simulation results are compared with the energy yield from the plants in 2020 to identify the shortfall in the plant performance. The loss analysis for the plant is performed by obtaining the loss diagram from the PVsyst software. This study also proposes a methodology to study the commissioned PV plant's performance and determine the interaction between variables such as direct and diffused solar radiations, air temperature, and wind speed for forecasting hourly produced power. This article will motivate researchers to analyze installed power plants using modern technical tools.
发展中国家,如印度,由于需求的增加和化石燃料的枯竭,正在迅速从传统能源向可持续能源转变。并网光伏 (PV) 系统吸引了许多投资者、组织和机构进行部署。本文研究并比较了安装在印度泰米尔纳德邦的一所教育机构——SRMIST(SRM 科技学院)的三个 52kW PV 电站的性能评估。该地点的年平均温度为 28.5°C,平均全球水平辐照度为 160 kWh/m2/m。使用太阳辐射、温度和风速获得了 52kW 功率电站的预测模型。使用 Minitab 16.2.1 软件得出了基于线性回归模型的预测方程,并将结果与 2020 年从三个 52kW 电站获得的实时交流能量产量进行了比较。此外,该 52kW 电站是使用 PVsyst V7.1.8 版软件设计的。将模拟结果与 2020 年的电站能量产量进行比较,以确定电站性能的不足。通过从 PVsyst 软件中获取损耗图,对电站进行了损耗分析。本研究还提出了一种研究已安装的光伏电站性能的方法,并确定了直接和漫射太阳辐射、空气温度和风速等变量之间的相互作用,以预测每小时的发电量。本文将激励研究人员使用现代技术工具分析已安装的电站。