Skip to main content
OSTI.GOVU.S. Department of Energy Office of Scientific and Technical Information
U.S. Department of Energy
Office of Scientific and Technical Information
 

A Reproducible Validation of Algorithms for Estimating Array Tilt and Azimuth from Photovoltaic Power Time Series

Conference ·
; ; ;

In this research, we assess the viability of four different, publicly available algorithms for estimating the azimuth and tilt parameters of solar photovoltaic systems using only the associated AC power time series data and site latitude-longitude coordinates. In this work, we curated a benchmarking data set of 44 fixed-tilt systems, comprising 275 measured AC power inverter data streams, with known azimuth and tilt parameters. Additionally, we isolated test cases in the data set with real- world issues, including shading and clipping, to determine how algorithm performance varies based on the presence of these phenomena. Using this data set for benchmarking, we evaluated the estimated vs. actual system characteristics for each algorithm, as well as the associated algorithm execution time using a standardized benchmarking process. The two highest performing algorithms were the Solar Data Tools and the PVWatts 5- based methods, which both achieved a median absolute error of approximately 5 and 1 degrees for azimuth and tilt, respectively. During run time analysis, the SDT method was approximately 5 times faster than the PVWatts 5-based method, with the median execution time for a stream varying between 6 and 8 seconds vs. a median run time of 31 seconds for the PVWatts 5-based method.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office
DOE Contract Number:
AC36-08GO28308
OSTI ID:
2310351
Report Number(s):
NREL/CP-5K00-88895; MainId:89674; UUID:d1e35ab0-d438-477f-a8b2-0ebafe31fd04; MainAdminId:71885
Resource Relation:
Conference: Presented at the 2023 IEEE 50th Photovoltaic Specialists Conference (PVSC), 11-16 June 2023, San Juan, Puerto Rico
Country of Publication:
United States
Language:
English

References (12)

Estimation of Photovoltaic System Location and Orientation from Power Signals June 2021
Solar Engineering of Thermal Processes April 2013
Signal Decomposition Using Masked Proximal Operators January 2023
A deep neural network approach for behind-the-meter residential PV size, tilt and azimuth estimation January 2020
Solar Data Tools: Automatic Solar Data Processing Pipeline June 2020
pvlib python: a python package for modeling solar energy systems September 2018
PVWatts Version 5 Manual September 2014
Automated Shift Detection in Sensor-Based PV Power and Irradiance Time Series June 2022
Performance Comparison of Clipping Detection Techniques in AC Power Time Series June 2021
PVInsight (Final Technical Report) September 2021
The National Solar Radiation Data Base (NSRDB) June 2018
Photovoltaic fleet degradation insights April 2022

Similar Records

Related Subjects

SOLAR ENERGY
azimuth
photovoltaic
system parameters
tilt
time series