NASA's goal in Earth science is to observe, understand, and model the Earth system to discover how it is changing, to better predict change, and to understand the consequences for life on Earth. The Applied Sciences Program, within the Earth Science Division of the NASA Science Mission Directorate, serves individuals and organizations around the globe by expanding and accelerating societal and economic benefits derived from Earth science, information, and technology research and development.

The Prediction Of Worldwide Energy Resources (POWER) Project, funded through the Applied Sciences Program at NASA Langley Research Center, gathers NASA Earth observation data and parameters related to the fields of surface solar irradiance and meteorology to serve the public in several free, easy-to-access and easy-to-use methods. POWER helps communities become resilient amid observed climate variability by improving data accessibility, aiding research in energy development, building energy efficiency, and supporting agriculture projects.

The POWER project contains over 380 satellite-derived meteorology and solar energy Analysis Ready Data (ARD) at four temporal levels: hourly, daily, monthly, and climatology. The POWER data archive provides data at the native resolution of the source products. The data is updated nightly to maintain near real time availability (2-3 days for meteorological parameters and 5-7 days for solar). The POWER services catalog consists of a series of RESTful Application Programming Interfaces, geospatial enabled image services, and web mapping Data Access Viewer. These three service offerings support data discovery, access, and distribution to the project’s user base as ARD and as direct application inputs to decision support tools.

The latest data version update includes hourly-based source ARD, in addition to enhanced daily, monthly, annual, and climatology data. The daily time series for meteorology is available from 1981, while solar-based parameters start in 1984. The hourly source data are from Clouds and the Earth's Radiant Energy System (CERES) and Global Modeling and Assimilation Office (GMAO), spanning from 1984 for meteorology and from 2001 for solar-based parameters. The hourly data equips users with the ARD needed to model building system energy performance, providing information directly amenable to decision support tools introducing the industry standard EnergyPlus Weather file format.

The POWER Project contains over 380 satellite-derived meteorology and solar energy Analysis Ready Data (ARD) at four temporal levels: hourly, daily, monthly (by year 12 months + annual averages), and climatology. The POWER Data Archive provides data at the native resolution of the source data products. The data is updated nightly to maintain Near Real Time (NRT) availability (2-3 days for meteorological parameters and 5-7 days for solar). The POWER Project targets three specific user communities: Renewable Energy (RE), Sustainable Buildings (SB), and Agroclimatology (AG). The POWER Projects provides community specific parameters, output formats, naming conventions, and units that are commonly employed by each user community. The POWER Services Catalog consists of a series of RESTful Application Programming Interfaces (API), geospatial enabled image services, and a web mapping Data Access Viewer (DAV). These three different service offerings support data discovery, access, and distribution to our user base as ARD and as direct application inputs to decision support tools.

2021FEBEREC-STD-117

The data set consists of the hourly load demand, hourly solar irradiance and hourly wind speed of a community located in Northern part of Nigeria named Bara, Kirfi Local Government area of Bauchi state, Nigeria. The hourly solar resource data and wind resource data of the community for a period of one year is obtained from an existing database of the Power Data Access Viewer of National Aeronautic and Space Administration (NASA).

The Prediction of Worldwide Energy Resource (POWER) Project is funded through the NASA Applied Sciences Program within the Earth Science Mission Directorate. The POWER Project supports three user communities with solar and/or meteorological data: 1) Renewable Energy (RE), 2) Sustainable Buildings (SB), and 3) Agroclimatology (AG)POWER Data Sources:The POWER project provides access to community-based Analysis Ready Data (ARD) for meteorology and solar-related parameters, specifically formulated for assessing and designing renewable energy systems.The data is available on at the source models’ native latitude and longitude global grid.Temporal levels include Hourly, Daily, Monthly, Annual, and Climatology. Download options include single point, regional, and global data.Formats include NetCDF, CSV, ASCII, geoJSON, ICASA, & EPW.Meteorological parameters are derived from:NASA's GMAO MERRA-2 archive (Jan. 1, 1981 – 3 Months Behind Near Real Time)NASA's GEOS 5.12.4 FP-IT archive (End of MERRA2 – Near Real Time)Solar parameters are derived from:NASA's GEWEX/SRB release 4.0 archive (Jan. 1, 1984 – Dec. 31, 2000) NASA's CERES SYN1deg (Jan. 1, 2001 – 3 Months Behind Near Real Time)NASA's FLASHFlux (3 Months Behind Near Real Time – Near Real Time)If you have any comments or questions, please do not hesitate to contact us at larc-power-project@mail.nasa.gov

This dataset is as presented in the paper titled "Data article: Distributed PV power data for three cities in Australia." in the Journal of Renewable and Sustainable Energy, volume 11 by Jamie M, Bright, Sven Killinger and Nicholas A. Engerer.

Abstract:
We present a publicly available dataset containing photovoltaic (PV) system power measurements and metadata from 1,287 residential installations across three states/territories in Australia--- though mainly for the cities of Canberra, Perth and Adelaide.
The data is recorded between September 2016 and March 2017 at 10-min temporal resolution and consists of real inverter reported power measurements from PV systems that are well distributed throughout each city. The dataset represents a considerably valuable resource as public access to spatio-temporal PV power data is almost non-existent; this dataset has been used in numerous articles already by the authors. The PV power data is free to download and is available in its raw, quality controlled (QC) and `tuned' formats. Each PV system is accompanied by individual metadata including geolocation, user reported metadata and simulated parameterisation. Data provenance,download, usage rights and example usage are detailed within.
Researchers are encouraged to leverage this rich spatio-temporal dataset of distributed PV power data in their research.

Further information is available at ANU Data Commons and Solcast.
This dataset has an embargo period for 3 years after the ARENA funded ANU project closure, though data is always available through Solcast.

Usage rights:

There is a non-standard data usage rights agreement for this data. In the uploads is a 'license and metadata.txt' file that details the usage rights and metadata of the data. The exact agreement is reproduced here:

The data is released with bespoke terms. We state the crucial elements of these terms here. The dataset is freely provided to researchers as is with no guarantee of support. The dataset is not for commercial usage, but for research only. You are empowered to use this dataset however you wish in your research, through direct usage, adaptation, or improvements to the data itself. The data must not be redistributed, the access point for the data is exclusively through the website as described in Sec.III of the manuscript. Should you make significant changes to the data and wish to redistribute the new data, explicit permission must be obtained from the authors. Finally, appropriate accreditation to the creators must be made in all publications and outputs that arise from using this dataset in any way. To appropriately accredit the creators, we require that this exact data article (Bright et al., 2019) is referenced alongside its DOI: https://dx.doi.org/10.25911/5ca6a0640869a. Additionally, if using the QC version of the data, we also require a citation for the original papers detailing QCPV (Killinger et al., 2016a, 2016a). Furthermore, if using the tuned PV version of this data, we also require a citation for both the QCPV papers above and the PV tuning papers (Killinger et al., 2016b, 2017b) for full visibility of the data provenance. Lastly, the original hosts of this data PVoutput.org should be recognised for their efforts.

References:

Bright, Jamie M.; Killinger, Sven; and Engerer, Nicholas A. 2019. Data article: Distributed PV power data for three cities in Australia. Journal of Renewable and Sustainable Energy. Vol 11. See online for full details.

Killinger, Sven; Braam, Felix; Muller, Bjorn; Wille-Haussmann, Bernhard and McKenna, Russell, 2016a. Projection of power generation between differently-oriented PV systems. Solar Energy. 136, 153-165.

Killinger, Sven; Muller, Bjorn; Saint-Drenan, Yves Marie and McKenna, Russell. 2016b. Towards an improved nowcasting method by evaluating power profiles of PV systems to detect apparently atypical behavior. Conference Record of the IEEE Photovoltaic specialists Conference, pages 980-985.10.1109/PVSC.2016.7749757

Killinger, Sven; Engerer, Nicholas and Müller, Björn. 2017a. QCPV: A quality control algorithm for distributed photovoltaic array power output. Solar Energy. 143, 120-131.

Killinger, Sven; Bright, Jamie M.; Lingfors, David and Engerer, Nicholas A. 2017b. A tuning routine to correct systematic influences in reference PV systems’ power outputs. Solar Energy. 157, 6.

We present a publicly available dataset containing photovoltaic (PV) system power measurements and metadata from 1,287 residential installations across three states/territories in Australia--- though mainly for the cities of Canberra, Perth and Adelaide. The data is recorded between September 2016 and March 2017 at 10-min temporal resolution and consists of real inverter reported power measurements from PV systems that are well distributed throughout each city. The dataset represents a considerably valuable resource as public access to spatio-temporal PV power data is almost non-existent; this dataset has been used in numerous articles already by the authors. The PV power data is free to download and is available in its raw, quality controlled (QC) and `tuned' formats. Each PV system is accompanied by individual metadata including geolocation, user reported metadata and simulated parameterisation. Data provenance, usage rights and example usage are detailed within. Researchers are encouraged to leverage this rich spatio-temporal dataset of distributed PV power data in their research.

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