Photovoltaic (PV) power system performance can vary from nominal specifications when put in application, making it difficult to accurately estimate real power generation at a localized level. As the usage and efficiency of PV systems has increased in recent years, the amount of power contributed to the national power grid from solar irradiation has also increased significantly. However, solar power installations are subject to variances in efficiency and output, driven by differences in system size, local weather, and atmospheric condition changes. With a significant install base in today's world, combined with extensive solar irradiance and meteorological data, the variables exist to explore the viability of a power generation forecasting model to predict PV power system performance across the United States at a localized level.
Chang, Kevin; Siddiqui, Afreen; and Slater, Robert
"Forecasting Localized Weather-Based Photovoltaic Energy Production,"
SMU Data Science Review: Vol. 2
, Article 2.
Available at: https://scholar.smu.edu/datasciencereview/vol2/iss2/2
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