Abstract
Heliostat Aimpoint and Layout Optimization Software (HALOS) is an open-source software package that allows users to explore solar field layout optimization, aimpoint strategy optimization, and performance characterization of concentrating solar power tower plants. Users interface with the tool through python, and results are reported in time series tables, plots, runtime logs, and flat-file outputs. Users choose from a list of variables such as tower height, receiver capacity, flux limits, design-point irradiance, etc., and specify information about the system using a small collection of flat files. The software can then optimize the specified variables (e.g., aimpoints for each heliostat) to maximize the thermal energy delivered to the receiver while adhering to flux limits. HALOS is implemented to be flexible with respect to flux characterization methods, but includes a direct connection to NREL's SolarPILOT™ software via its python API so that users can utilize high-fidelity flux simulation methods that have already been developed.
- Developers:
-
Zolan, Alexander [1] ; Hamilton, William [1] ; Liaqat, Kashif [1] ; Wagner, Michael [1]
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Release Date:
- 2021-06-15
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Programming Languages:
-
Python
- Licenses:
-
BSD 3-clause "New" or "Revised" License
- Sponsoring Org.:
-
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies OfficePrimary Award/Contract Number:AC36-08GO28308
- Code ID:
- 59329
- Site Accession Number:
- SWR-21-41
- Research Org.:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Country of Origin:
- United States
Citation Formats
Zolan, Alexander, Hamilton, William, Liaqat, Kashif, and Wagner, Michael.
HALOS (Heliostat Aimpoint and Layout Optimization Software).
Computer Software.
https://github.com/NREL/HALOS.
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office.
15 Jun. 2021.
Web.
doi:10.11578/dc.20210616.1.
Zolan, Alexander, Hamilton, William, Liaqat, Kashif, & Wagner, Michael.
(2021, June 15).
HALOS (Heliostat Aimpoint and Layout Optimization Software).
[Computer software].
https://github.com/NREL/HALOS.
https://doi.org/10.11578/dc.20210616.1.
Zolan, Alexander, Hamilton, William, Liaqat, Kashif, and Wagner, Michael.
"HALOS (Heliostat Aimpoint and Layout Optimization Software)." Computer software.
June 15, 2021.
https://github.com/NREL/HALOS.
https://doi.org/10.11578/dc.20210616.1.
@misc{
doecode_59329,
title = {HALOS (Heliostat Aimpoint and Layout Optimization Software)},
author = {Zolan, Alexander and Hamilton, William and Liaqat, Kashif and Wagner, Michael},
abstractNote = {Heliostat Aimpoint and Layout Optimization Software (HALOS) is an open-source software package that allows users to explore solar field layout optimization, aimpoint strategy optimization, and performance characterization of concentrating solar power tower plants. Users interface with the tool through python, and results are reported in time series tables, plots, runtime logs, and flat-file outputs. Users choose from a list of variables such as tower height, receiver capacity, flux limits, design-point irradiance, etc., and specify information about the system using a small collection of flat files. The software can then optimize the specified variables (e.g., aimpoints for each heliostat) to maximize the thermal energy delivered to the receiver while adhering to flux limits. HALOS is implemented to be flexible with respect to flux characterization methods, but includes a direct connection to NREL's SolarPILOT™ software via its python API so that users can utilize high-fidelity flux simulation methods that have already been developed.},
doi = {10.11578/dc.20210616.1},
url = {https://doi.org/10.11578/dc.20210616.1},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20210616.1}},
year = {2021},
month = {jun}
}