Publications

Masoom, A; Kosmopoulos, P; Bansal, A; Gkikas, A; Proestakis, E; Kazadzis, S; Amiridis, V (2021). Forecasting dust impact on solar energy using remote sensing and modeling techniques. SOLAR ENERGY, 228, 317-332.

Abstract
The present study focuses on assessment of dust impact on forecasting solar irradiance and energy, during an extreme dust event. We utilize surface-based Aeronet measurements, satellite observations (MODIS and CALIPSO), and Modls Dust AeroSol (MIDAS) dust database in conjunction with Weather Research and Forecasting (WRF) model simulations, based on inputs from Indian Solar Irradiance Operational System (INSIOS) and Copernicus Atmosphere Monitoring Service (CAMS) forecast. This work presents a novel approach of CAMS aerosol optical depth (AOD) ingestion into WRF model for analyzing dust impact on solar irradiance. The study region is the northwestern part of Indian subcontinent, an area with some of the largest solar power projects in India. A set of three consecutive and deadly dust storms occurred in May 2018 with one having high intensity and values of AOD and dust optical depth reaching up to 2. Dust events of this extent leads to a significant reduction in solar irradiance and affect the capacity of energy exploitation through Photovoltaic installations and Concentrating Solar Power plants due to the solar aerosol-related extinction. The dust plume resulted in an average decrease of 76 W/m(2) and 275 W/m(2) for global horizontal irradiance (GHI) and direct normal irradiance (DNI), respectively, and a maximum reduction of 100 W/m(2) (10%) and 400 W/m(2) (40%) in GHI and DNI, respectively. The proposed methodology can support solar energy producers, for optimum energy production forecasting, management, and maintenance (e.g. soiling) as well as transmission and distribution system operators, taking into account the effect of dust aerosols into their day-to-day market operations.

DOI:
10.1016/j.solener.2021.09.033

ISSN:
0038-092X