Aim and Scope: Low-carbon goals, energy crisis, and demand increasing lead to the use of advanced computation and communication technologies into the smart energy systems (SESs) to enable the environmental-friendly, real-time, and economic control and operation. However, the widespread deployment of electronic devices enabling the new technologies cause significantly increased operational uncertainty with frequent dynamic phenomena, which bring about unprecedented challenges for SESs to keep working with traditional control and operation methods. Artificial intelligence (AI) and machine learning (ML) approaches are promising in addressing these challenges as the SESs have the capability to collect and process massive amounts of high-dimensional and multi-type data about the system operations. The energy sectors will benefit from the intelligent methods, enabling innovative and real-time operational strategies for hierarchical management to achieve interactive functions, such as multi-level control and optimization of all-grid-level distributed energy resources, voltage and frequency regulation, special protection schemes to infer potential contingencies, and etc. Nevertheless, since the intelligent operations of SESs deeply depend on a huge amount of data about the system status, the vulnerabilities exposed in the IP-based electronic devices engender a variety of opportunities for malicious adversaries to access private data or interrupt the processes of energy generation, transmission, and distribution. What’s more, the machine learning society has revealed and demonstrated that the adversary could construct adversarial examples against ML models, which also brings about concerns to use the ML approaches in SESs.
As such, it is apparent that intelligence and security are on the brink of having significant impacts on the operation and control of SESs. This workshop aims to bring together researchers and participants in the field of intelligence and security for SESs and call for innovative research solutions for intelligence-enabled SESs and the security-enhanced SESs. This workshop will focus on (but is not limited to) the following topics:
- ML-based/Data-driven operation and planning for SESs
- Physics-informed/-constrained ML methods for the control and optimization of SESs
- ML-based/Data-driven detection and identification of faults and attacks in SESs
- Intelligent and secure approaches for energy and data transmission and trading in SESs
- Security and privacy analysis of ML-based applications in SESs
- Trust AI for SESs
- Countermeasures to enhance the security of AI-enabled SESs
Paper submission instruction:
Refer to Submission instructions for more information.
One best paper will be selected from the accepted papers!
Important Dates:
Paper Submission Deadline: 15 July 2022 10 August 2022 (Extended)
Paper Acceptance Deadline: 20 August 2022 28 August 2022 (Extended)
Final Paper Deadline: 9 September 2022 30 September 2022
ORGANIZERS
Organizer 1: Peng Cheng (Chair), Zhejiang University
Email: lunarheart@zju.edu.cn
Organizer 2: Ruilong Deng (Co-chair), Zhejiang University
Email: dengruilong@zju.edu.cn
Organizer 3: Zhenyong Zhang (Co-chair), Guizhou University
Email: zyzhangnew@gmail.com
