Abstract: Photovoltaic (PV) energy generation plays a crucial role in the energy transition. Small-scale, rooftop PV installations are deployed at an unprecedented pace, and their safe integration into the grid requires up-to-date, high-quality information. Overhead imagery is increasingly being used to improve the knowledge of rooftop PV installations with machine learning models capable of automatically mapping these installations. However, these models cannot be reliably transferred from one region or imagery source to another without incurring a decrease in accuracy. To address this issue, known as distribution shift, and foster the development of PV array mapping pipelines, we propose a dataset containing aerial images, segmentation masks, and installation metadata (i.e., technical characteristics). We provide installation metadata for more than 28000 installations. We supply ground truth segmentation masks for 13000 installations, including 7000 with annotations for two different image providers. Finally, we provide installation metadata that matches the annotation for more than 8000 installations. Dataset applications include end-to-end PV registry construction, robust PV installations mapping, and analysis of crowdsourced datasets.
Abstract: While the extraction of natural resources has been well documented and analysed at the national level, production trends at the level of individual mines are more difficult to uncover, mainly due to poor availability of mining data with sub-national detail. In this paper, we contribute to filling this gap by presenting an open database on global coal and metal mine production on the level of individual mines. It is based on manually gathered information from more than 1900 freely available reports of mining companies, where every data point is linked to its source document, ensuring full transparency. The database covers 1171 individual mines and reports mine-level production for 80 different materials in the period 2000–2021. Furthermore, also data on mining coordinates, ownership, mineral reserves, mining waste, transportation of mining products, as well as mineral processing capacities (smelters and mineral refineries) and production is included.
“Community leaders and water researchers can now access publicly available online datasets curated and processed by NETL to better understand the composition of energy-related wastewater streams. The data will help mitigate environmental risks and identify possible sources of valuable critical minerals (CMs).
The National Energy Water Treatment and Speciation (NEWTS) Database provides information at no cost about the levels of toxins, concentrations of metals and other hazardous materials found in energy-related wastewater streams, which include power plant leachate, acid mine drainage, brackish water and oil and gas produced water. Researchers can input the data into computer software to develop appropriate remediation steps.
The NEWTS team is also developing a database dashboard showing sites across the nation where energy-related wastewater stream samples and composition data have been collected. Using the dashboard, community leaders and the public will be able to quickly obtain data from locations displayed on a map where various government agencies collect and analyze water samples from energy-related wastewater streams….”
Abstract: Promoting a transition to low-carbon energy systems to mitigate climate change requires an optimization of renewable energy (RE) planning. However, curated data for the most promising RE technologies, hydro-, wind and solar power, are missing, which limits data-based decision-making support. Here, a spatially explicit database for existing and proposed renewable power plants is provided: The Renewable Power Plant database for Africa (RePP Africa) encompasses 1074 hydro-, 1128 solar, and 276 wind power plant records. For each power plant, geographic coordinates, country, construction status, and capacity (in megawatt) are reported. The number of RePP Africa records exceeds the respective values in other existing open-access databases and matches available cumulative capacity data reported by international energy organizations best with deviations <13% for hydro-, <23% for wind, and <32% for solar power plants. This contemporary database is the most harmonized open-accessible reference source on RE power plants across Africa for stakeholders from science, (non-)governmental organizations, consulting, and industry; providing a fundamental data basis for the development of an integrated sustainable RE mix.
Abstract: This paper describes OSeMOSYS Global, an open-source, open-data model generator for creating global electricity system models for an active global modelling community. This version of the model generator is freely available and can be used to create interconnected electricity system models for both the entire globe and for any geographically diverse subset of the globe. Compared to other existing global models, OSeMOSYS Global allows for full user flexibility in determining the time slice structure and geographic scope of the model and datasets, and is built using the widely used fully open-source OSeMOSYS energy system model. This paper describes the data sources, structure and use of OSeMOSYS Global, and provides illustrative workflow results.
“The aim of the Data Licensing Advisory group is to develop the standard licences that are required to allow Shared Data to flow through Open Energy Access Control, in alignment with the Data Sensitivity classes. This will include key policies, such as conditions for participation, roles and responsibilities. The outputs of this group will be the necessary licences and requirements for a functioning Access Control. …”
“The mission of OurEnergyPolicy.org is to facilitate substantive, responsible dialogue on energy policy issues, and provide this dialogue as a resource for the American people, policymakers, and the media. By bringing together energy experts in productive national discourse, OurEnergyPolicy.org enhances the potential of identifying, adopting, and implementing effective energy policy. OurEnergyPolicy.org also serves as a one-stop resource hub for all things energy policy, and includes a free Resource Library, aggregated Energy Headlines, national Energy Events Calendar and more….”
Abstract: Energy policy often builds on insights gained from quantitative energy models and their underlying data. As climate change mitigation and economic concerns drive a sustained transformation of the energy sector, transparent and well-founded analyses are more important than ever. We assert that models and their associated data must be openly available to facilitate higher quality science, greater productivity through less duplicated effort, and a more effective science-policy boundary. There are also valid reasons why data and code are not open: ethical and security concerns, unwanted exposure, additional workload, and institutional or personal inertia. Overall, energy policy research ostensibly lags behind other fields in promoting more open and reproducible science. We take stock of the status quo and propose actionable steps forward for the energy research community to ensure that it can better engage with decision-makers and continues to deliver robust policy advice in a transparent and reproducible way.
“The Department of Energy (DOE) Office of Scientific and Technical Information (OSTI) is building a new DOE software submission and search tool. DOE CODE is the reimagining of OSTI’s current product for the submission of software, the Energy Science and Technology Software Center, or ESTSC. Since DOE CODE is still under development, if you need to submit, search, or order software, please visit the ESTSC site for instructions.”
“According to the World Energy Outlet over 1.2 billion people around the world lack access to reliable electricity in 2016. The objective of the Clean Energy Data Science Challenge was to mine and leverage open data to promote the development of innovative and scalable solutions.”
“OPENing UP new methods, indicators and tools for peer review, dissemination of research results, and impact measurement….Open Access and Open Scholarship have revolutionized the way scholarly artefacts are evaluated and published, while the introduction of new technologies and media in scientific workflows has changed the “how and to whom” science is communicated, and how stakeholders interact with the scientific community. OpenUP addresses key aspects and challenges of the currently transforming science landscape and aspires to come up with a cohesive framework for the review-disseminate-assess phases of the research life cycle that is fit to support and promote Open Science….Through analysis, consultation, hands-on engagement with researchers, publishers, institutions and funders, industry and citizens, OpenUP will a) define a framework that defines roles and processes, benefits and opportunities, b) validate the proposed mechanisms through a series of pilots involving researchers from four scientific communities (Life Sciences, Social Sciences, Arts & Humanities, Energy), and c) come up with practical policy recommendations and guidelines to be used by EU, national and institutional policymakers at different settings. OpenUP will engage with all stakeholders via a series of outreach and training events, and the creation of an Open Information Hub, a collaborative web based Knowledge Base that will host a catalogue of open tools/services, methodologies, best practices from various disciplines or settings, success stories, reports. This increased level of engagement and knowledge will feed into the development of research and innovation policies that aim to support and complement Open Science….”
“The list of reasons why energy models and data are not openly available is long: business confidentiality; concerns over the security of critical infrastructure; a desire to avoid exposure and scrutiny; worries about data being misrepresented or taken out of context; and a lack of time and resources.
This secrecy is problematic, because it is well known that closed systems hide and perpetuate mistakes. A classic example is the spreadsheet error discovered in the influential Reinhart–Rogoff paper used to support economic policies of national austerity. The European Commission’s Energy Roadmap 2050 was based on a model that could not be viewed by outsiders, leaving it open to criticism. Assumptions that remain hidden, like the costs of technologies, can largely determine what comes out of such models. In the United Kingdom, opaque and overly optimistic cost assumptions for onshore wind went into models used for policymaking, and that may well have delayed the country’s decarbonization.
This closed culture is alien to younger researchers, who grew up with collaborative online tools and share code and data on platforms such as GitHub. Yet academia’s love affair with metrics and the pressure to publish set the wrong incentives: every hour spent on cleaning up a data set for public release or writing open-source code is time not spent working on a peer-reviewed paper.”
“The Energy Department’s (DOE) Advanced Research Projects Agency-Energy (ARPA-E) today announced $11 million in funding for seven transformational projects that will develop realistic, open-access models and data repositories to aid in improving the U.S. electric grid….”