Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Antonio T. Lorenzo"'
Publikováno v:
Frontiers in Energy Research, Vol 12 (2024)
The Expected Solar Performance and Ramp Rate tool (ESPRR) is an open-source interactive web-based application that reliably calculates ramp rate (RR) statistics and an expected power generation time series for prospective photovoltaic (PV) systems. U
Externí odkaz:
https://doaj.org/article/568d81e11ea94755b7d41bc9b2620002
Publikováno v:
Solar Energy. 144:466-474
We use a Bayesian method, optimal interpolation, to improve satellite derived irradiance estimates at city-scales using ground sensor data. Optimal interpolation requires error covariances in the satellite estimates and ground data, which define how
Autor:
Anastasios Golnas, William F. Holmgren, Leland Boeman, Antonio T. Lorenzo, Clifford W. Hansen, Justin Sharp, Aidan Tuohy
Publikováno v:
2019 IEEE 46th Photovoltaic Specialists Conference (PVSC).
We describe an open source evaluation framework for solar forecasting to support the DOE Solar Forecasting 2 program and the broader solar forecast community. The framework enables evaluations of solar irradiance, solar power, and net-load forecasts
This paper has been submitted to Solar Energy. Abstract: We introduce a computational framework to forecast cloud index (CI) fields for up to one hour on a spatial domain that covers a city. Such intra-hour CI forecasts are important to produce solar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::370c5d767fd623e957a201573a8f2f67
Publikováno v:
Solar Energy. 122:1158-1169
We describe and evaluate forecasts of solar irradiance using real-time measurements from a network of irradiance sensors. A forecast method using cloud motion vectors obtained from a numerical weather model shows significant skill over a standard per
We used the open-source PVLib-Python library to create PV power forecasts for a fleet of utility scale power plants and assessed their accuracies. PVLib-Python allows users to easily retrieve standardized weather forecast data relevant to PV power mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8df09a52d9e647177d1882093cf87a1b
Publikováno v:
2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC).
We describe how Bayesian data assimilation can be used to improve nowcasts of irradiance over small, city-scale, spatial areas. Specifically, we use optimal interpolation (OI) to improve satellite derived estimates of global horizontal irradiance (GH
Publikováno v:
2015 IEEE 42nd Photovoltaic Specialist Conference (PVSC).
We describe improvements to the open source PVLIB-Python modeling package. PVLIB-Python provides most of the functionality of its parent PVLIB-MATLAB package and now follows standard Python design patterns and conventions, has improved unit test cove
Publikováno v:
2014 IEEE 40th Photovoltaic Specialist Conference (PVSC).
We present a method to calculate the economic value of forecasts, based on the use of forecasts to optimize curtailment strategies in scenarios with a ramp rate rule. We consider how and when to limit PV power output in order to comply with a ramp ra
Autor:
Michael Leuthold, Antonio T. Lorenzo, Chang Ki Kim, William F. Holmgren, Alexander D. Cronin, Eric A. Betterton
Publikováno v:
2014 IEEE 40th Photovoltaic Specialist Conference (PVSC).
We developed a real-time PV power forecasting system for Tucson Electric Power using a combination of high-resolution numerical weather prediction, satellite imagery, distributed generation (DG) production data, and irradiance sensors. The system pro