Recent developments in the weather research and forecasting (WRF) model have made it possible to accurately estimate incident solar radiation. This study couples the WRF-solar modifications with a multilayer urban canopy and building energy model (BEM) to create a unified WRF forecasting system called urban WRF–solar (uWRF-solar). This paper tests the integrated approach in the New York City (NYC) metro region as a sample case. Hourly forecasts are validated against ground station data collected at ten different sites in and around the city. Validation is carried out independently for clear, cloudy, and overcast sky conditions. Results indicate that the uWRF-solar model can forecast solar irradiance considerably well for the global horizontal irradiance (GHI) with an R2 value of 0.93 for clear sky conditions, 0.61 for cloudy sky conditions, and finally, 0.39 for overcast conditions. Results are further used to directly forecast solar power production in the region of interest, where evaluations of generation potential are done at the city scale. Outputs show a gradient of power generation produced by the potential available solar energy on the entire uWRF-solar grid. In total, the city has a city photovoltaic (PV) potential of 118 kWh/day/m2 and 3.65 MWh/month/m2.
On the Assessment of a Numerical Weather Prediction Model for Solar Photovoltaic Power Forecasts in Cities
Contributed by the Advanced Energy Systems Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received October 7, 2018; final manuscript received February 14, 2019; published online March 29, 2019. Assoc. Editor: Reza Baghaei Lakeh.
- Views Icon Views
- Share Icon Share
- Cite Icon Cite
- Search Site
Gamarro, H., Gonzalez, J. E., and Ortiz, L. E. (March 29, 2019). "On the Assessment of a Numerical Weather Prediction Model for Solar Photovoltaic Power Forecasts in Cities." ASME. J. Energy Resour. Technol. June 2019; 141(6): 061203. https://doi.org/10.1115/1.4042972
Download citation file:
- Ris (Zotero)
- Reference Manager