Workshops

ACM SIGEnergy Workshop on Cybersecurity and Privacy of Energy Systems (EnergySP)

Abstract: Cybersecurity and privacy are an important pillar of energy systems. Modernized energy systems, including smart grid, distributed/renewable energy resources, EV-charging infrastructure, smart homes, and smart buildings, have been facing a number of cybersecurity attacks. On the other hand, extensive data collection from such systems are calling for stronger privacy protection.

ACM SIGEnergy Workshop on Cybersecurity and Privacy of Energy Systems (EnergySP) aims to establish an open forum for novel research ideas to be exchanged and shared from the energy systems and smart grid communities in the context of cybersecurity and privacy. We aim to bring together diverse experts from the cybersecurity and privacy areas as well as from those from the energy sector to establish cross-disciplinary exchanges of knowledge and insights to tackle the critical challenges in securing our energy future and providing privacy assurance to energy applications.

We encourage researchers and experts in the field of cybersecurity energy systems to take the opportunity to use this workshop to share their work and open the discussion of new ideas on this evolving topic.

Topics of interest include, but are not limited to, the following:

Cryptographic systems, secure key management, authentication, provenance, and access control for energy systems
Cybersecurity of distributed energy resources and IoT devices
Security analysis of energy management systems and grid controlling systems
Industry standardization of secure energy management and control protocols
Detection, prevention, and mitigation of cyber attacks and system anomalies in smart energy systems
Cloud/Edge security for smart energy systems
Machine/Deep learning and artificial intelligence approaches for security and privacy in smart energy systems
Threat intelligence collection and analysis for smart energy systems
Deception technologies for smart energy systems
Moving target defense for smart energy systems
Digital twins and testbeds for security and privacy risk assessment of smart energy systems
SCADA and legacy system security
Security by design and verification tools for smart energy systems
Cyber attack and defense case studies on smart energy systems
Human factors aspects in cybersecurity and privacy in smart energy systems
Privacy-preserving energy systems and applications
Privacy protection of energy data collection and sharing
Blockchain-based secure energy systems
Legal aspects and compliance of smart energy systems
Economics of cybersecurity in energy systems

Dates:
Paper submission: ~~March 24, 2025 (AOE)~~ April 1, 2025 (AOE)

Submission:
We invite papers with 4-6 pages in 9-point ACM proceedings template with double-column format (i.e., excluding references) and unlimited number of pages for appendices and references. The submission is not anonymous. Submissions will be made to HotCRP: https://energysp25.hotcrp.com.

Accepted papers will appear in ACM digital library.

Contact: For any questions, please contact one of the organisers:

Sid Chi-Kin Chau ([email protected])
Daisuke Mashima ([email protected])
Ghada Elbez ([email protected])
Kaibin Bao ([email protected])
Zbigniew Kalbarczyk ([email protected])

Website: Please find more information (e.g., scope, submission instructions, and workshop schedule) on the Workshop Website: https://energysp.github.io/.

The 1st International Workshop on Advanced Deep Reinforcement Learning for Energy Systems (ADELE)

Abstract: The 1st International Workshop on Advanced Deep Reinforcement Learning for Energy Systems (ADELE) welcomes submissions from academic and industry focusing on Deep Reinforcement Learning and its applications to the energy domain. The workshop is geared towards presenting, exploring, and discussing newest approaches from the DRL domain and inspiring quick transition towards application and further research by scientists in the energy domain. ADELE recognizes that the premier targets of DRL research is not the energy domain and, therefore, strives to foster close cooperation between DRL and energy scientists.

Topics of interest include, but are not limited to, the following:

Approaches to covering large state/action spaces, including handling underlying physical properties and controller conflicts
State space representations
Approaches to eXplainable Deep Reinforcement Learning suitable to large and complex (e.g., mixed discrete-continuous) state/action spaces
Safe and Risk-averse DRL
Offline learning from domain user knowledge without explicit trajectory encoding
Physics-informed or model-based DRL
Modifications of existing model-free algorithms wrt. the energy domain
Neuroevolutionary DRL
Hybrid agents (e.g., DRL-based extensions of known controllers)
Agent verification

Dates:
Paper submission: April 1, 2025, 23:59 (AOE)
Notification: April 15, 2025, 23:59 (AOE)
Camera ready: May 1, 2025, 23:59 (AOE) Final Version in ACM TAPS

Submission:
ADELE invites submissions in the following format:

Full workshop papers, up to 10 pages, following the ACM template according to the main conference’s guidelines (https://energy.acm.org/conferences/eenergy/2025/cfp.php).
Tutorials, with an accompanying paper of up to 4 pages, following the same templates as a full workshop paper.

The submission site of ADELE is located at: https://adele25.hotcrp.com/. Submissions will be peer-reviewed by at least 3 reviewers. Presentations will honor the workshop format by providing 20 minutes with the actual slide deck and additional 10 minutes for discussion.

Program Committee:

Omid Ardakanian, University of Alberta, Canada
Dan Wang, The Hong Kong Polytechnic University, Hong Kong, China
Florence Carton, Total Energies, France
Tianyu Zhang, Autodesk Research, Canada
Eric MSP Veith, Carl von Ossietzky University Oldenburg
Arlena Wellßow, Carl von Ossietzky University Oldenburg
Torben Logemann, Carl von Ossietzky University Oldenburg

Contact: For any questions, please contact:

Eric Veith ([email protected])

The 1st International Workshop on Computational Aspects of Energy Flexibility (CAEF)

Abstract: Flexibility in electricity demand and supply is used to address challenges in markets, grid congestion, reducing CO2 emissions, etc. The amount of flexibility rapidly increases due to the electrification of transport and heat. Many of the new devices introduced by the electrification have a communication interface and implement a flexibility interface. To efficiently make use of this flexibility, it needs to be aggregated and/or coordinated. This requires advances in modeling of flexibility, distributed optimization of flexibility, computational-aware flexibility markets, and online optimization of flexibility. The use of flexibility itself introduces new challenges related to privacy, cybersecurity, and robustness.

We invite papers that address computational challenges related to flexibility. Topics of interest include (but are not limited to):

Mathematical modeling of flexibility: (dis)aggregation of flexibility, quantifying flexibility, prediction of flexibility, generation of flexibility data;
Communication of flexibility: flexibility protocols and standardization, privacy preserving communication of flexibility, robustness of ICT systems for flexibility, cybersecurity of demand-side management;
Algorithms for using flexibility: algorithms for flexibility coordination, distributed optimization, performance guarantees of algorithms, computational efficiency, online algorithms, learning-augmented algorithms;
Computational aspects of flexibility-markets: computation-aware flexibility market design, computational efficiency, algorithms for computing equilibria.

Dates:
Paper Registration and Submission: March 31, 2025 (AOE)

Submission:
All submissions must be at most 6 pages (including references, figures, and appendices), formatted in 9-point ACM double-column format, single-blind. Papers should present original work, not published, accepted or under review for any other publication. Submissions are made to HotCRP: https://caef25.hotcrp.com/.

Accepted papers will appear in ACM digital library.

Contact: For any questions, please contact one of the organizers:

Marco Gerards ([email protected])
Gerwin Hoogsteen ([email protected])
Johann Hurink ([email protected])

Website: Please find more information (e.g., scope, submission instructions, and workshop schedule) on the workshop website: https://sites.google.com/utwente.nl/caef2025.

The 6th International Workshop on Energy Data and Analytics (EDA)

Abstract: The design of efficient, eco-friendly, and scalable energy systems is critical to addressing the environmental impacts of current energy practices, with renewable energy offering vast untapped potential. This workshop focuses on leveraging data-driven approaches and FAIR principles to enhance energy system innovation, addressing challenges in data availability, processing, and applications such as supply-demand predictions, predictive maintenance, and privacy-conscious analysis. With a special focus on FAIR data and the challenges and opportunities of research data and software for 2025, we invite experts from academia and industry to discuss their experiences and best practices in this domain.

The workshop invites submissions on the following topics – all of them specific to energy data or energy systems and their characteristics:

New approaches and techniques to analyze energy data and turn it into actionable insights
Data science for energy data
Tools and techniques for management and archival of energy data
Measurement data from field studies and real-world systems
Data from simulations of energy systems
Synthetic data generation techniques
Data visualization
Data integration and data quality issues
Data privacy and anonymization techniques
Modeling and representation of energy‐specific knowledge
Reusability of research data: challenges and success stories
Industrial data and IP-related challenges for data exchange

Dates:
Paper Submission: ~~March 28, 2025 (AOE)~~ April 1, 2025 (AOE)
Notification of Acceptance: ~~April 24, 2025 (AOE)~~ April 30, 2025 (AOE)
Camera-ready: May 9, 2025, (AOE)

Submission:
Two types of contributions are solicited:

Full papers, up to 8 pages in 9-point ACM double-column format (i.e., excluding references) and unlimited number of pages for appendices and references, single-blind.
Short papers, up to 4 pages in 9-point ACM double-column format (i.e., excluding references) and unlimited number of pages for appendices and references, single-blind.

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 https://www.acm.org/publications/proceedings-template.

Submissions are made via HotCRP: https://eda25.hotcrp.com/

Contact: For any questions, please get in touch with one of the Workshop Chairs:

Nicole Ludwig (University of Tübingen, Germany), ([email protected])
Astrid Nieße (OFFIS, Germany), ([email protected])
Omid Ardakanian (University of Alberta), ([email protected])
Klemens Böhm (KIT, Germany), ([email protected])

Website: Please find more information (e.g., scope, submission instructions) on the Workshop Website: https://nfdi4energy.uol.de/sites/eda_workshop/.

13th International Workshop on Energy-Efficient Data Centres (E2DC 2025)

Abstract: Data centres (DCs) are the backbone of the digital economy, supporting everything from artificial intelligence (AI) innovation to critical cloud services. However, their rapid expansion and growing energy demands make efficiency and sustainability urgent priorities. Europe is at the forefront of this transformation, driven by rising energy costs, ambitious ultra-low carbon goals, and a commitment to a greener digital future.

Over the past five decades, computing platforms have evolved, each requiring tailored data centre architectures to maximise resource efficiency and environmental sustainability. Research in this space must integrate computing systems, infrastructure (e.g., cooling, power grid integration), and advanced algorithms to address efficiency, security, sovereignty, and robustness challenges.

This workshop continues the E2DC series, bringing together researchers and industry leaders to explore next-generation energy-efficient AI data centres. A holistic approach is encouraged, focusing on how DCs interact with smart cities, smart grids, and integrated energy systems. With AI workloads growing exponentially, solutions must optimize cooling, workload distribution, heat reuse, and renewable energy integration to build resilient and sustainable infrastructure.

With energy challenges intensifying and digital infrastructure playing a crucial role in Europe’s sustainability efforts, this workshop provides an ideal platform to discuss scientific advancements and cutting-edge solutions. Researchers working at the intersection of AI, energy informatics, and data centre sustainability are invited to contribute and help shape the future of energy-smart AI computing.

Dates:
Paper Registration and Submission: ~~March 24, 2025~~ April 7, 2025
Notification of Acceptance: April 21, 2025
Final Manuscript Due: May 9, 2025

Submission:
We invite submissions of up to 8 pages in length (or 4-pages for short/position papers), formatted using standard 9-point ACM double-column format (sigconf proceedings template), single-blind. Papers that do not meet the size and formatting requirements may not be reviewed. Word and LaTeX templates are available on the ACM Publications Website.

Contact: For any questions, please contact one of the organisers:

Ariel Oleksiak, Poznan Supercomputing and Networking Center, Poland ([email protected])
Jon Summers, RISE Research Institutes of Sweden, Sweden ([email protected])

Website: Please follow the Workshop Website: https://e2dc.eu, which will be constantly updated with more information and news (e.g., scope, submission instructions, and workshop schedule).

AI-Driven Energy Efficiency in Dynamic Systems (AI-DEEDS)

Unlocking Energy Efficiency Through Physics-Informed AI:
Machine learning (ML) is revolutionizing engineering and physical sciences by enabling advanced data-driven solutions across estimation, forecasting, sensing, and control. At the forefront of this transformation, physics-informed AI offers a unique opportunity to model, understand, and optimize dynamic physical systems, driving breakthroughs in energy efficiency and sustainability.
The Workshop on Physics-Informed AI for Energy Efficiency in Dynamic Systems serves as a nexus for domain experts, practitioners, and ML/AI developers to advance innovation at this critical intersection. Hosted by the AI Institute in Dynamic Systems, this workshop is dedicated to addressing the complexities of dynamic systems in engineering and science by fostering a vibrant research community and introducing transformative tools and frameworks.

Workshop Highlights:

Developing a Unified Framework: Build a taxonomy of architectures for modeling dynamic systems and foster collaboration across disciplines.
Enabling Open Collaboration: Share datasets, insights, and methodologies to drive impactful solutions in energy efficiency.
Learn from Thought Leaders: Hear from interdisciplinary domain experts such as Nathan Kutz, John Sipple, Michael Kane, Hod Lipson, and Chris Develder.
Introducing the Common Task Framework (CTF): Participate in an open competition platform for benchmarking algorithms on curated dynamic system datasets.
Tackling Real-World Challenges: Join a CTF challenge on predicting HVAC dynamics, leveraging a dataset from commercial office buildings to address critical issues in environmental sustainability.

Through engaging keynote speeches, invited talks, and contributed presentations, this workshop will not only explore cutting-edge research but also create actionable pathways for reshaping how ML tackles the pressing challenges of energy efficiency. The introduction of the CTF aims to establish a shared, objective foundation for testing and comparing algorithms, enabling cross-disciplinary collaboration and impactful progress.

Topics of Interest:
Topics of interest include, but are not limited to, the following:

Physics-Informed ML

Integrating physical constraints (e.g., conservation laws) into models.
Regularization via physics priors in optimization.
Symmetry-aware architectures (e.g., CNNs, kernels).
Real-time control using physics-based ML.

Hybrid Physics and Data-Driven Models

Combining physical constraints with data-driven models for time series.
Reduced-order modeling for complex flows.
Discovering governing equations.
Integrating data collection, control, and modeling.

Optimization in Dynamical Systems

Nonconvex optimization with physical constraints.
Low-rank reduction for structured data.
Sensor optimization and uncertainty quantification.
Optimal sensor placement for system control.

Reinforcement Learning (RL) for Control

Scalable RL for multi-agent systems.
Robust RL under model mismatch.
Model-based and model-free hybrid control.
Control architectures for physics-driven RL.

Uncertainty and Risk Quantification

Uncertainty quantification in sensor placement and control.
Robust control under uncertainty.
Ethical and interpretable models for safety.
Real-time control with embedded uncertainty.

Through engaging keynote speeches, invited talks, and contributed presentations, this workshop will not only explore cutting-edge research but also create actionable pathways for reshaping how ML tackles the pressing challenges of energy efficiency. The introduction of the CTF aims to establish a shared, objective foundation for testing and comparing algorithms, enabling cross-disciplinary collaboration and impactful progress.

Key Dates:

Workshop Papers:

Submission opens: 20 January 2025
Paper deadline: 28 March 2025, 11:59 pm AoE
Acceptance notification: 28 April 2025, 11:59 pm AoE
Camera-ready deadline: 9 May 2025, 11:59 pm AoE

Contest:

Contest deadline: 25 May 2025, 11:59 pm AoE

Registration:

Registration begins: 10 Feb 2025

Paper Submission:

Maximum of 4 pages (excluding references).
An additional fifth page is allowed for the camera-ready version.
Appendices are permitted but optional for reviewers to consider.
Papers must use the ACM conference template.
Submissions will undergo a double-blind review process.
Accepted papers will be presented during the poster session.
The top three accepted papers will be invited for Contributed Talks.
Submission Platform: https://dynamicai25.hotcrp.com/

Common Task Framework Challenge:

Focus:

Predicting HVAC dynamics using:

Google’s open-source TensorFlow dataset with six years of real-world telemetry data from large commercial office buildings.
An optional open-source HVAC simulator provided by Google.

Criteria:

Accuracy will be the primary metric for evaluation.

Participation:

The top four submissions on the live leaderboard will deliver Lightning Talks during the workshop.
Sage Bionetworks will use a real holdout test set (not publicly released) to rank solutions on the live leaderboard.

Speakers: