Companies that want to burnish their sustainable credentials have increasingly been turning to renewable energy to supply their data centres and other power demand. However, traditional Power Purchase Agreements (PPAs) for renewable energy only match supply and demand on average over a longer period such as a year. If the renewable energy comes from variable wind or solar power, this means that within the year there are many periods of oversupply and undersupply. There is growing interest from corporations such as Google to match their demand with clean energy supply on a truly 24/7 basis, whether that is using variable renewables paired with storage, or using dispatchable clean sources such as geothermal power. In 2020 Google committed to operating entirely on 24/7 carbon-free energy (CFE) at all of its data centres and campuses worldwide by 2030. We will explore the costs and benefits of 24/7 carbon-free PPAs, both for Google and for the power systems in which they operate. We will also discuss implementation issues, market integration, and the possibility for demand-side management both in time and between different data centres.
Tom Brown is professor for "Digital Transformation in Energy Systems" at the Technical University of Berlin. He researches cost-optimal pathways for the energy system, with a particular focus on revealing the trade-offs between energy resources, network expansion, flexibility and public acceptance of new infrastructure. He is also a strong supporter of openness and transparency in research data and software, with the goal to enable a vigorous public debate on the trade-offs necessary to reach climate neutrality. He is one of the lead developers of the widely-used open-source toolbox Python for Power System Analysis (PyPSA). Before joining TU Berlin in 2021, he led a Helmholtz Young Investigator Group at the Karlsruhe Institute of Technology. He did his BA and MMath at Cambridge University and his PhD at Queen Mary, University of London.
The design of future energy systems that are efficient, ecologically friendly, robust and scalable is a core concern of our societies. Another very relevant development in recent years is the one towards a data-driven perspective on system design. In the context of energy systems, a broad variety of data, often huge in volume, is available. For instance, each smart meter is generating data streams, which often are recorded and archived. On the other side, this is not the case for all aspects of energy systems, even though the availability of data is crucial for the development of new methods. The questions how data describing energy systems can be captured and processed, how its availability can be increased, and what can be learned from it are fundamentally important. This last aspect includes predictions of various kinds of supply and demand, predictive maintenance of energy infrastructures, the processing of energy-consumption data in a way that respects the privacy of the individuals involved as well as business secrets etc.
This workshop is interdisciplinary in nature, i.e., brings together individuals interested in both data management/data analytics and energy systems. Its objectives are the following ones:
The workshop solicits submissions on the following topics – all of them specific to energy data/energy systems and their characteristics:
On a methodological level, the workshop is open to any kind of submission:
Two types of contributions are solicited:
The submission must be in PDF format and be formatted according to the official ACM Proceedings format. Papers that do not meet the size and formatting requirements may not be reviewed. Word and LaTeX templates are available at http://www.acm.org/publications/article-templates/proceedings-template.html. The proceedings of the workshop will be published by ACM Digital Library along with the e-Energy conference proceedings.
Submissions are made by HotCRP: https://eenergy22eda.hotcrp.com/
Please turn to Klemens Böhm (klemens dot boehm at kit dot edu) for any questions or comments.