wiki.openmod-initiative.org - User contributions [en]

SIREN

2024-11-07T11:23:31Z

Angus King:

{{Model
|Full_Model_Name=SEN Integrated Renewable Energy Network Toolkit
|author_institution=Sustainable Energy Now Inc
|authors=Angus King
|contact_persons=Angus King
|contact_email=angusking53@gmail.com
|website=http://www.sen.asn.au/modelling_overview
|source_download=https://github.com/ozsolarwind/siren
|logo=Sen48x48.png
|text_description=SIREN uses external datasets to model the potential for renewable energy generation for a geographic region. The approach is to model the data on an hourly basis for a desired year (ignoring leap days, that is, 8,760 hours). Users explore potential location and scale of renewable energy sources (stations, storage, transmission) to meet electricity demand. It is possible to model any geographic area and uses a number of open or publicly available data sources:
<ul>
<li>Maps can be created from OpenStreet Map (MapQuest) tiles
<li>Weather data files can be created from NASA (MERRA2) or ECMWF (ERA5) satellite data
<li>It uses US NREL SAM models to calculate energy generation
</ul>
SIREN is available, packaged for Windows, on Sourceforge (https://sourceforge.net/projects/sensiren/). There's a help file (https://rawgit.com/ozsolarwind/siren/master/help.html) which describes "how it works".
The program source is available on github (https://github.com/ozsolarwind/siren)
|User documentation=https://rawgit.com/ozsolarwind/siren/master/help.html
|Number of developers=1
|open_source_licensed=Yes
|license=Affero General Public License v3 (AGPL-3.0)
|model_source_public=Yes
|Link to source=https://github.com/ozsolarwind/siren
|data_availability=some
|open_future=No
|modelling_software=Python, NREL SAM
|processing_software=Python
|GUI=No
|model_class=Electricity System Model,
|sectors=Electricity,
|technologies=Renewables
|Storage (Gas)=No
|Storage (Heat)=No
|decisions=dispatch, investment
|georesolution=Individual power stations
|timeresolution=Hour
|math_modeltype=Simulation, Other
|math_modeltype_shortdesc=Uses NREL SAM models to estimate hourly renewable generation for a range/number of renewable energy stations
|math_objective=Match generation to demand and minimise cost
|is_suited_for_many_scenarios=Yes
|montecarlo=No
|report_references=https://sen.asn.au/modelling/
|Model input file format=No
|Model file format=No
|Model output file format=No
}}

SIREN

2024-11-07T11:21:47Z

Angus King:

{{Model
|Full_Model_Name=SEN Integrated Renewable Energy Network Toolkit
|author_institution=Sustainable Energy Now Inc
|authors=Angus King
|contact_persons=Angus King
|contact_email=angusking53@gmail.com
|website=http://www.sen.asn.au/modelling_overview
|source_download=https://github.com/ozsolarwind/siren
|logo=Sen48x48.png
|text_description=SIREN uses external datasets to model the potential for renewable energy generation for a geographic region. The approach is to model the data on an hourly basis for a desired year (ignoring leap days, that is, 8,760 hours). Users explore potential location and scale of renewable energy sources (stations, storage, transmission) to meet electricity demand. It is possible to model any geographic area and uses a number of open or publicly available data sources:
<ul>
<li>Maps can be created from OpenStreet Map (MapQuest) tiles
<li>Weather data files can be created from NASA (MERRA2) or ECMWF (ERA5) satellite data
<li>It uses US NREL SAM models to calculate energy generation
</ul>
SIREN is available, packaged for Windows, on Sourceforge (https://sourceforge.net/projects/sensiren/). There's a help file (https://rawgit.com/ozsolarwind/siren/master/help.html) which describes "how it works".
The program source is available on github (https://github.com/ozsolarwind/siren)
|User documentation=https://rawgit.com/ozsolarwind/siren/master/help.html
|Number of developers=1
|open_source_licensed=Yes
|license=Affero General Public License v3 (AGPL-3.0)
|model_source_public=Yes
|Link to source=https://github.com/ozsolarwind/siren
|data_availability=some
|open_future=No
|modelling_software=Python, NREL SAM
|processing_software=Python
|GUI=No
|model_class=Electricity System Model,
|sectors=Electricity,
|technologies=Renewables
|Storage (Gas)=No
|Storage (Heat)=No
|decisions=dispatch, investment
|georegions=WA
|georesolution=Individual power stations
|timeresolution=Hour
|math_modeltype=Simulation, Other
|math_modeltype_shortdesc=Uses NREL SAM models to estimate hourly renewable generation for a range/number of renewable energy stations
|math_objective=Match generation to demand and minimise cost
|is_suited_for_many_scenarios=Yes
|montecarlo=No
|report_references=https://sen.asn.au/modelling/
|Model input file format=No
|Model file format=No
|Model output file format=No
}}

SIREN

2024-11-07T11:21:15Z

Angus King:

{{Model
|Full_Model_Name=SEN Integrated Renewable Energy Network Toolkit
|author_institution=Sustainable Energy Now Inc
|authors=Angus King
|contact_persons=Angus King
|contact_email=angusking53@gmail.com
|website=http://www.sen.asn.au/modelling_overview
|source_download=https://github.com/ozsolarwind/siren
|logo=Sen48x48.png
|text_description=SIREN uses external datasets to model the potential for renewable energy generation for a geographic region. The approach is to model the data on an hourly basis for a desired year (ignoring leap days, that is, 8,760 hours). Users explore potential location and scale of renewable energy sources (stations, storage, transmission) to meet electricity demand. It is possible to model any geographic area and uses a number of open or publicly available data sources:
<ul>
<li>Maps can be created from OpenStreet Map (MapQuest) tiles
<li>Weather data files can be created from NASA (MERRA2) or ECMWF (ERA5) satellite data
<li>It uses US NREL SAM models to calculate energy generation
</ul>
SIREN is available, packaged for Windows, on Sourceforge (https://sourceforge.net/projects/sensiren/). There's a help file (https://rawgit.com/ozsolarwind/siren/master/help.html) which describes "how it works"
The program source is available on github (https://github.com/ozsolarwind/siren)
|User documentation=https://rawgit.com/ozsolarwind/siren/master/help.html
|Number of developers=1
|open_source_licensed=Yes
|license=Affero General Public License v3 (AGPL-3.0)
|model_source_public=Yes
|Link to source=https://github.com/ozsolarwind/siren
|data_availability=some
|open_future=No
|modelling_software=Python, NREL SAM
|processing_software=Python
|GUI=No
|model_class=Electricity System Model,
|sectors=Electricity,
|technologies=Renewables
|Storage (Gas)=No
|Storage (Heat)=No
|decisions=dispatch, investment
|georegions=WA
|georesolution=Individual power stations
|timeresolution=Hour
|math_modeltype=Simulation, Other
|math_modeltype_shortdesc=Uses NREL SAM models to estimate hourly renewable generation for a range/number of renewable energy stations
|math_objective=Match generation to demand and minimise cost
|is_suited_for_many_scenarios=Yes
|montecarlo=No
|report_references=https://sen.asn.au/modelling/
|Model input file format=No
|Model file format=No
|Model output file format=No
}}

SIREN

2024-11-07T07:51:22Z

Angus King:

{{Model
|Full_Model_Name=SEN Integrated Renewable Energy Network Toolkit
|author_institution=Sustainable Energy Now Inc
|authors=Angus King
|contact_persons=Angus King
|contact_email=angusking53@gmail.com
|website=http://www.sen.asn.au/modelling_overview
|source_download=https://github.com/ozsolarwind/siren
|logo=Sen48x48.png
|text_description=SIREN uses external datasets to model the potential for renewable energy generation for a geographic region. The approach is to model the data on an hourly basis for a desired year (ignoring leap days, that is, 8,760 hours). Users explore potential location and scale of renewable energy sources (stations, storage, transmission) to meet electricity demand. It is possible to model any geographic area and uses a number of open or publicly available data sources:
<ul>
<li>Maps can be created from OpenStreet Map (MapQuest) tiles
<li>Weather data files can be created from NASA (MERRA2) or ECMWF (ERA5) satellite data
<li>It uses US NREL SAM models to calculate energy generation
</ul>
SIREN is available, packaged for Windows, on Sourceforge (https://sourceforge.net/projects/sensiren/). There's a help file (https://rawgit.com/ozsolarwind/siren/master/help.html) which describes "how it works"
|User documentation=https://rawgit.com/ozsolarwind/siren/master/help.html
|Number of developers=1
|open_source_licensed=Yes
|license=Affero General Public License v3 (AGPL-3.0)
|model_source_public=Yes
|Link to source=https://github.com/ozsolarwind/siren
|data_availability=some
|open_future=No
|modelling_software=Python, NREL SAM
|processing_software=Python
|GUI=No
|model_class=Electricity System Model,
|sectors=Electricity,
|technologies=Renewables
|Storage (Gas)=No
|Storage (Heat)=No
|decisions=dispatch, investment
|georegions=WA
|georesolution=Individual power stations
|timeresolution=Hour
|math_modeltype=Simulation, Other
|math_modeltype_shortdesc=Uses NREL SAM models to estimate hourly renewable generation for a range/number of renewable energy stations
|math_objective=Match generation to demand and minimise cost
|is_suited_for_many_scenarios=Yes
|montecarlo=No
|report_references=https://sen.asn.au/modelling/
|Model input file format=No
|Model file format=No
|Model output file format=No
}}

SIREN

2023-08-08T05:05:33Z

Angus King:

{{Model
|Full_Model_Name=SEN Integrated Renewable Energy Network Toolkit
|author_institution=Sustainable Energy Now Inc
|authors=Angus King
|contact_persons=Angus King
|contact_email=angus@ozsolarwind.com
|website=http://www.sen.asn.au/modelling_overview
|source_download=https://github.com/ozsolarwind/siren
|logo=Sen48x48.png
|text_description=SIREN uses external datasets to model the potential for renewable energy generation for a geographic region. The approach is to model the data on an hourly basis for a desired year (ignoring leap days, that is, 8,760 hours). Users explore potential location and scale of renewable energy sources (stations, storage, transmission) to meet electricity demand. It is possible to model any geographic area and uses a number of open or publicly available data sources:
<ul>
<li>Maps can be created from OpenStreet Map (MapQuest) tiles
<li>Weather data files can be created from NASA (MERRA2) or ECMWF (ERA5) satellite data
<li>It uses US NREL SAM models to calculate energy generation
</ul>
SIREN is available, packaged for Windows, on Sourceforge (https://sourceforge.net/projects/sensiren/). There's a help file (https://rawgit.com/ozsolarwind/siren/master/help.html) which describes "how it works"
|User documentation=https://rawgit.com/ozsolarwind/siren/master/help.html
|Number of developers=1
|open_source_licensed=Yes
|license=Affero General Public License v3 (AGPL-3.0)
|model_source_public=Yes
|Link to source=https://github.com/ozsolarwind/siren
|data_availability=some
|open_future=No
|modelling_software=Python, NREL SAM
|processing_software=Python
|GUI=No
|model_class=Electricity System Model,
|sectors=Electricity,
|technologies=Renewables
|Storage (Gas)=No
|Storage (Heat)=No
|decisions=dispatch, investment
|georesolution=Individual power stations
|timeresolution=Hour
|math_modeltype=Simulation, Other
|math_modeltype_shortdesc=Uses NREL SAM models to estimate hourly renewable generation for a range/number of renewable energy stations
|math_objective=Match generation to demand and minimise cost
|is_suited_for_many_scenarios=Yes
|montecarlo=No
|report_references=https://sen.asn.au/modelling/
|Model input file format=No
|Model file format=No
|Model output file format=No
}}

SIREN

2023-07-07T10:10:38Z

Angus King:

{{Model
|Full_Model_Name=SEN Integrated Renewable Energy Network Toolkit
|author_institution=Sustainable Energy Now Inc
|authors=Angus King
|contact_persons=Angus King
|contact_email=angus@ozsolarwind.com
|website=http://www.sen.asn.au/modelling_overview
|source_download=https://github.com/ozsolarwind/siren
|logo=Sen48x48.png
|text_description=SIREN uses external datasets to model the potential for renewable energy generation for a geographic region. The approach is to model the data on an hourly basis for a desired year (ignoring leap days, that is, 8,760 hours). Users explore potential location and scale of renewable energy sources (stations, storage, transmission) to meet electricity demand. It is possible to model any geographic area and uses a number of open or publicly available data sources:
<ul>
<li>Maps can be created from OpenStreet Map (MapQuest) tiles
<li>Weather data files can be created from NASA (MERRA2) or ECMWF (ERA5) satellite data
<li>It uses US NREL SAM models to calculate energy generation
</ul>
SIREN is available, packaged for Windows, on Sourceforge (https://sourceforge.net/projects/sensiren/). There's a help file (https://rawgit.com/ozsolarwind/siren/master/help.html) which describes "how it works"
|User documentation=https://rawgit.com/ozsolarwind/siren/master/help.html
|Number of developers=1
|open_source_licensed=Yes
|license=Affero General Public License v3 (AGPL-3.0)
|model_source_public=Yes
|Link to source=https://github.com/ozsolarwind/siren
|data_availability=some
|open_future=No
|modelling_software=Python, NREL SAM
|processing_software=Python
|GUI=No
|model_class=Electricity System Model,
|sectors=Electricity,
|technologies=Renewables
|Storage (Gas)=No
|Storage (Heat)=No
|decisions=dispatch, investment
|georesolution=Individual power stations
|timeresolution=Hour
|math_modeltype=Simulation, Other
|math_modeltype_shortdesc=Uses NREL SAM models to estimate hourly renewable generation for a range/number of renewable energy stations
|math_objective=Match generation to demand and minimise cost
|is_suited_for_many_scenarios=No
|montecarlo=No
|report_references=https://sen.asn.au/modelling/
|Model input file format=No
|Model file format=No
|Model output file format=No
}}

SIREN

2023-07-07T02:49:30Z

Angus King:

{{Model
|Full_Model_Name=SEN Integrated Renewable Energy Network Toolkit
|author_institution=Sustainable Energy Now Inc
|authors=Angus King
|contact_persons=Angus King
|contact_email=angus@ozsolarwind.com
|website=http://www.sen.asn.au/modelling_overview
|source_download=https://github.com/ozsolarwind/siren
|logo=Sen48x48.png
|text_description=SIREN uses external datasets to model the potential for renewable energy generation for a geographic region. The approach is to model the data on an hourly basis for a desired year (ignoring leap days, that is, 8,760 hours). Users explore potential location and scale of renewable energy sources (stations, storage, transmission) to meet electricity demand. It is possible to model any geographic area and uses a number of open or publicly available data sources:
<ul>
<li>Maps can be created from OpenStreet Map (MapQuest) tiles
<li>Weather data files can be created from NASA (MERRA2) or ECMWF (ERA5) satellite data
<li>It uses US NREL SAM models to calculate energy generation
</ul>
SIREN is available, packaged for Windows, on Sourceforge (https://sourceforge.net/projects/sensiren/). There's a help file (https://rawgit.com/ozsolarwind/siren/master/help.html) which describes "how it works"
|User documentation=https://rawgit.com/ozsolarwind/siren/master/help.html
|Number of developers=1
|open_source_licensed=Yes
|license=Affero General Public License v3 (AGPL-3.0)
|model_source_public=Yes
|Link to source=https://github.com/ozsolarwind/siren
|data_availability=some
|open_future=No
|modelling_software=Python, NREL SAM
|processing_software=Python
|GUI=No
|model_class=Electricity System Model,
|sectors=Electricity,
|technologies=Renewables
|Storage (Gas)=No
|Storage (Heat)=No
|decisions=dispatch, investment
|timeresolution=Hour
|math_modeltype=Simulation, Other
|math_modeltype_shortdesc=Uses NREL SAM models to estimate hourly renewable generation for a range/number of renewable energy stations
|math_objective=Match generation to demand and minimise cost
|is_suited_for_many_scenarios=No
|montecarlo=No
|report_references=https://sen.asn.au/modelling/
|Model input file format=No
|Model file format=No
|Model output file format=No
}}

File:Sen48x48.png

2023-07-07T02:42:53Z

Angus King:

Sustainable Energy Now Inc

2023-07-07T02:36:21Z

Angus King:

{{Institution
|Full Name=Sustainable Energy Now Inc
|Abbreviation=SEN
|Website=https://sen.asn.au/
|Address=Perth, Western Australia
|Email=contact@sen.asn.au
}}
<br/>

SIREN

2016-06-28T07:34:05Z

Angus King:

{{Model
|Full_Model_Name=SEN Integrated Renewable Energy Network Toolkit
|author_institution=Sustainable Energy Now Inc
|authors=Angus King
|contact_persons=Angus King
|contact_email=angus@ozsolarwind.com
|website=http://www.sen.asn.au/modelling_overview
|source_download=https://github.com/ozsolarwind/siren
|logo=Sen logo 99.png
|text_description=SIREN uses external datasets to model the potential for renewable energy generation for a geographic region. The approach is to model the data on an hourly basis for a desired year (ignoring leap days, that is, 8,760 hours). Users explore potential location and scale of renewable energy sources (stations, storage, transmission) to meet electricity demand. It is possible to model any geographic area and uses a number of open or publicly available data sources:
o Maps can be created from OpenStreet Map (MapQuest) tiles
o Weather data files can be created from NASA (MERRA2) satellite data
o It uses US NREL SAM models to calculate energy generation
SIREN is available, packaged for Windows, on Sourceforge (https://sourceforge.net/projects/sensiren/). There's a help file (https://rawgit.com/ozsolarwind/siren/master/help.html) which describes "how it works"
|open_source_licensed=Yes
|license=Affero General Public License v3 (AGPL-3.0)
|model_source_public=Yes
|data_availability=some
|open_future=No
|modelling_software=Python, NREL SAM
|processing_software=Python
|model_class=Electricity System Model,
|sectors=Electricity,
|technologies=Renewables
|decisions=dispatch, investment
|timeresolution=Hour
|math_modeltype=Simulation, Other
|math_modeltype_shortdesc=User NREL SAM models to estimate hourly renewable generation for a range/number of renewable energy stations
|math_objective=Match generation to demand and minimise cost
|is_suited_for_many_scenarios=No
|report_references=http://www.sen.asn.au/modelling_findings
}}

SIREN

2016-06-06T10:01:01Z

Angus King:

{{Model
|Full_Model_Name=SEN Integrated Renewable Energy Network Toolkit
|author_institution=Sustainable Energy Now Inc
|authors=Angus King
|contact_persons=Angus King
|contact_email=angus@ozsolarwind.com
|website=http://www.sen.asn.au/modelling_overview
|source_download=https://github.com/ozsolarwind/siren
|logo=Sen logo 99.png
|text_description=SIREN uses external datasets to model the potential for renewable energy generation for a geographic region. The approach is to model the data on an hourly basis for a desired year (ignoring leap days, that is, 8,760 hours). Users explore potential location and scale of renewable energy sources (stations, storage, transmission) to meet electricity demand. It is possible to model any geographic area and uses a number of open or publicaly available data sources:
o Maps can be created from OpenStreet Map (MapQuest) tiles
o Weather data files can be created from NASA (MERRA2) satellite data
o It uses US NREL SAM models to calculate energy generation
SIREN is available, packaged for Windows, on Sourceforge (https://sourceforge.net/projects/sensiren/). There's a help file (https://rawgit.com/ozsolarwind/siren/master/help.html) which describes "how it works"
|open_source_licensed=Yes
|license=Affero General Public License v3 (AGPL-3.0)
|model_source_public=Yes
|data_availability=some
|open_future=No
|modelling_software=Python, NREL SAM
|processing_software=Python
|model_class=Electricity System Model,
|sectors=Electricity,
|technologies=Renewables
|decisions=dispatch, investment
|timeresolution=Hour
|math_modeltype=Simulation, Other
|math_modeltype_shortdesc=User NREL SAM models to estimate hourly renewable generation for a range/number of renewable energy stations
|math_objective=Match generation to demand and minimise cost
|is_suited_for_many_scenarios=No
|report_references=http://www.sen.asn.au/modelling_findings
}}

SIREN

2016-06-06T09:58:09Z

Angus King: Created page with "{{Model |Full_Model_Name=SEN Integrated Renewable Energy Network Toolkit |author_institution=Sustainable Energy Now Inc |authors=Angus King |contact_persons=Angus King |contac..."

{{Model
|Full_Model_Name=SEN Integrated Renewable Energy Network Toolkit
|author_institution=Sustainable Energy Now Inc
|authors=Angus King
|contact_persons=Angus King
|contact_email=angus@ozsolarwind.com
|website=http://www.sen.asn.au/modelling_overview
|source_download=https://github.com/ozsolarwind/siren
|logo=Sen logo 99.png
|text_description=SIREN uses external datasets to model the potential for renewable energy generation for a geographic region. The approach is to model the data on an hourly basis for a desired year (ignoring leap days, that is, 8,760 hours). Users explore potential location and scale of renewable energy sources (stations, storage, transmission) to meet electricity demand. It is possible to model any geographic area and uses a number of open or publicaly available data sources:
o Maps can be created from OpenStreet Map (MapQuest) tiles
o Weather data files can be created from NASA (MERRA2) satellite data
o It uses US NREL SAM models to calculate energy generation
SIREN is available, packaged for Windows, on Sourceforge (https://sourceforge.net/projects/sensiren/). There's a help file (https://rawgit.com/ozsolarwind/siren/master/help.html) which describes "how it works"
|open_source_licensed=Yes
|license=Affero General Public License v3 (AGPL-3.0)
|model_source_public=Yes
|data_availability=some
|open_future=No
|modelling_software=Python, NREL SAM
|processing_software=Python
|sectors=Electricity,
|technologies=Renewables
|decisions=dispatch, investment
|timeresolution=Hour
|math_modeltype=Simulation, Other
|math_modeltype_shortdesc=User NREL SAM models to estimate hourly renewable generation for a range/number of renewable energy stations
|math_objective=Match generation to demand and minimise cost
|is_suited_for_many_scenarios=No
|report_references=http://www.sen.asn.au/modelling_findings
}}

File:Sen logo 99.png

2016-06-06T09:42:34Z

Angus King: