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5 results for “rooftop solar”
Global maps of area suitability for solar photovoltaics on rooftops and cropland
<p>This dataset consists of the following global maps:</p> <p>1. The suitable area for installing agri-photovoltaics or agrivoltaics on agricultural land cover in about 10 km x 10 km resolution for three scenarios of policy and social acceptance (optimistic, neutral and conservative)</p> <p>2. The percentage of PV-suitable building area of total area in 10km x 10km resolution</p> <p>3. The area suitability of rooftop-photovoltaics in a 10km x 10km resolution </p> <p>The maps are based on the land cover data from the Copernicus Land Monitoring Service from 2019 and the Open Street Map accessed in 2021.</p> <p>Updates from Version 1.0 :</p> <p>- New maps of agrivoltaic suitability due to updated methodology : inclusion of regional crop distribution </p>
Determinants of rooftop solar uptake: a comparative analysis of the residential and non-residential sectors in the Basque Country (Spain)
<p>Data for <strong>Determinants of rooftop solar uptake: a comparative analysis of the residential and non-residential sectors in the Basque Country (Spain)</strong></p> <p>Rooftop solar, both in the residential and the non-residential sector, is emerging rapidly as a popular source of clean electricity. Together with utility-scale photovoltaics, its future growth is essential to achieve decarbonization targets. Therefore, understanding adoption determinants for firms and households is key to efficiently promoting its diffusion. There is a gap, however, in the knowledge of non-residential adoption determinants, as less attention has been given to this sector compared to the residential sector. As a result of this gap, there is an absence of comparative analysis across sectors. As determinants of adoption cannot be assumed to be the same in both sectors, the objective of this research is threefold. First, to analyze whether the residential and non-residential sectors share key determinants of rooftop solar investment; second, to compare the sectoral differences in these determinants; and third, to assess the policy implications of the results obtained to further promote distributed solar photovoltaic energy. For this purpose, a regional case study in the Basque Country (Spain) was conducted, applying key theoretical frameworks to both sectors in a way that maximized the comparability of the results obtained across them. The results showed that adoption determinants are very different across sectors and, therefore, sector-specific policy actions need to be taken in each sector to efficiently promote rooftop solar. For the residential sector, policy actions could build upon behavioral aspects; for the non-residential sector, economic incentives are expected to be more successful, especially among medium size businesses, which are identified as the most promising segment.</p> <p> </p>
FACTSHEET ON ROOFTOP SOLAR DEVELOPMENT
<p>This is the first EVN data report on Rooftop Solar PV development in Vietnam for 2019.<br> It reports, for each of the 64 provinces in Vietnam, the number and total capacity of rooftop PV systems by type and size. Summary statistics on Rooftop Solar installations by 31/12/2019 in Vietnam</p> <ul> <li>Total installed RTS capacity: 378MWp</li> <li>Total number of systems: 22,232</li> <li>Average system capacity: <a href="http://16.9kWp/">16.9kWp</a></li> <li>Cumulated solar energy generated: 99,288MWh<br> </li> </ul>
Dataset for evaluating rooftop photovoltaic solar panels impact on urban temperature at city scale
<p>This dataset contains simulation outputs from the WRF/BEP+BEM v4.3.3 model, evaluating the impact of rooftop photovoltaic solar panels on urban temperatures in five cities: Kolkata, Austin, Sydney, Athens, and Brussels. The model uses one parent domain and two nested domains with resolutions of 18 km, 6 km, and 2 km, focusing on the 2 km resolution. Simulations cover the summer periods of each city, including panel surface temperature and urban state variables data. The dataset represents diverse climate types: tropical wet and dry (Kolkata), Mediterranean (Athens), moderate oceanic<em> </em>(Brussels), and subtropical humid (Sydney and Austin).</p>
Constructing a Model to Identify Markets for Rooftop Solar on Multifamily Housing
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.