Solar Photovoltaic (PV) systems are gaining popularity as a form of alternative energy with increased environmental awareness, renewable energy usage and concern for energy security. Lack of area-specific forecasts for the power output of gridconnected photovoltaic system hinders tapping solar power on a large scale. The objective of this paper is to estimate the profile of produced power of a grid-connected 20 kWp solar power plant in a reputed manufacturing industry located in Tiruchirappalli, India [10° 44' 42.3816'' N, 78° 47' 9.4524'' E]. An Artificial Neural Network (ANN)-based model is proposed in this paper. An experimental database of solar power output (from 7 th January 2014 to 10 th February 2014) has been used for training the ANN. Simulations were carried out with the Neural Network Fitting Toolbox of MATLAB software. Day-Ahead Forecasting results indicate that the proposed model performs well with great accuracy and efficiency.Statistical error analysis in terms of Mean Absolute Percentage Error (MAPE) was conducted and the best result was found to be 0.2887%. Reliable area-specific solar power production map can provide better utilization of solar energy resource and help in power system management.
Operational requirements of photovoltaic (PV) modules result in their inherent exposure to harsh environmental conditions. The performance of solar cells decreases with increasing temperature, with both efficiency and power output getting affected. High ambient temperature coupled with irradiance absorption leads to an elevated photovoltaic cell operating temperature, adversely affecting the panels' lifespan. Superhydrophobic nanocoatings are the preferred solution to reduce the accumulation of dust (soiling) over the surface of the panels. This article aims to study the effects of nanocoatings on module operating temperature and temperature-dependent cell parameters, such as open-circuit voltage (
), short-circuit current (
) and power generation. The application of nanocoating over the surface of solar panels reduces the operating temperatures while improving power generation in a temperate location with high annual atmospheric temperatures.
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