Impact of Aerosol and Cloud on the Solar Energy Potential over the Central Gangetic Himalayan Region

Abstract

We examine the impact of atmospheric aerosols and clouds on the surface solar radiation and solar energy at Nainital, a high-altitude remote location in the central Gangetic Himalayan region (CGHR). For this purpose, we exploited the synergy of remote-sensed data in terms of ground-based AERONET Sun Photometer and satellite observations from the MODerate Resolution Imaging Spectroradiometer (MODIS) and the Meteosat Second Generation (MSG), with radiative transfer model (RTM) simulations and 1 day forecasts from the Copernicus Atmosphere Monitoring Service (CAMS). Clouds and aerosols are one of the most common sources of solar irradiance attenuation and hence causing performance issues in the photovoltaic (PV) and concentrated solar power (CSP) plant installations. The outputs of RTM results presented with high accuracy under clear, cloudy sky and dust conditions for global horizontal (GHI) and beam horizontal irradiance (BHI). On an annual basis the total aerosol attenuation was found to be up to 105 kWh m−2 for the GHI and 266 kWh m−2 for BHI, respectively, while the cloud effect is much stronger with an attenuation of 245 and 271 kWh m−2 on GHI and BHI. The results of this study will support the Indian solar energy producers and electricity handling entities in order to quantify the energy and financial losses due to cloud and aerosol presence.

Can Forest Fires Be an Important Factor in the Reduction in Solar Power Production in India?

“…The variation was found to be from 0 to 25% for AMF and 55% for CMF. It can be observed that the AMF values were dominated by values ranging between 0.5 to 0.8 [36], which indicate heavy aerosol content during these months. The frequency of occurrence of AMF was highest in the range of 0.5 to 0.8, and was within 5% for other values.…”

“…The spatial resolution of the aerosol optical depth at a 550 nm forecast used in the present study was 0.4 • × 0.4 • (spatial resolution of the CAMS forecasts), whereas the temporal resolution of CAMS reanalysis is 3 hourly. The use of the CAMS AOD and other details are described in several earlier papers, and are hence not repeated here [36,42,[46][47][48][49].…”

“…In the current work, the financial analysis was performed for the 40 GW of solar power installed in the Indian subcontinent. The PV energy simulation was performed by assuming a realistic efficiency of 16% based on PV material (i.e., silicon polycrystalline) and shadowing effects of 4% from the surrounding region [36,39,65]. To perform the financial analysis of solar energy production, the price of electricity generation in INR per kWh is needed (1 INR = 0.013 USD).…”

“…To perform the financial analysis of solar energy production, the price of electricity generation in INR per kWh is needed (1 INR = 0.013 USD). The PV output energy is converted into the price of electricity by following earlier studies [36,37,39,66] and using the following equation:…”

“…This was later revised and increased to 100 GW of off grid-connected solar PV power, including 40 GW of off grid-connected rooftop solar projects, by 2022. Progress details and an overview of renewable energy development in the Indian subcontinent are presented in several earlier papers [35][36][37][38][39].…”