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Solar Energy Forecasting and Resource Assessment by Jan Kleissl

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Index

Note: Page numbers followed by “f” denote figures; “t” tables.

A

Aerosol optical depth (AOD), 25–26, 26f
American Society of Testing and Materials (ASTM), 14, 16f
Artificial neural networks (ANNs)-based forecast model, 389–390, 392f
data-rich scenario, 390
decision parameters, 390–391
survival-of-the-fittest scheme, 390–391

B

Baseline Surface Radiation Network (BSRN), 114

C

California Independent System Operators (CAISO) organization, 172
Canadian Weather Energy and Engineering Datasets (CWEEDS)
diffuse fraction vs. clearness index, 106–107, 107f
MAC3 model, 106
solar-irradiance measurements, 106
solar-radiation values, 106
RMSE, 106
Cloud index (CI), 29, 31
Cloud-motion vectors (CMVs)
cloud-motion detection, 273–275, 274f
error characterization ...

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