TY - JOUR
T1 - A perspective on the enabling technologies of explainable AI-based industrial packetized energy management
AU - Gutierrez-Rojas, Daniel
AU - Narayanan, Arun
AU - Santos Nunes Almeida, Cássia R.
AU - Almeida, Gustavo M.
AU - Pfau, Diana
AU - Tian, Yu
AU - Yang, Xu
AU - Jung, Alex
AU - Nardelli, Pedro H.J.
N1 - Funding Information:
This paper is partly supported by Research Council of Finland (former Academy of Finland) via EnergyNet Fellowship no. 321265/no. 328869, X-SDEN project no. 349965, and Intelligent Techniques in Condition Monitoring of Electromechanical Energy Conversion Systems dec. no. 331197. The authors would like to thank Dr. G. Hoogsteen from University of Twente, Netherlands, and the associated team for offering an academic license of DEMKit and Dr. Arthur Sena for making Figure 4. The authors declare no competing interests.
Funding Information:
This paper is partly supported by Research Council of Finland (former Academy of Finland) via EnergyNet Fellowship no. 321265 /no. 328869 , X-SDEN project no. 349965 , and Intelligent Techniques in Condition Monitoring of Electromechanical Energy Conversion Systems dec. no. 331197 .
Publisher Copyright:
© 2023 The Author(s)
PY - 2023/12/15
Y1 - 2023/12/15
N2 - This paper reviews the key information and communication technologies that are necessary to build an effective industrial energy management system considering the intermittence of renewable sources like wind and solar †. In particular, we first introduce the concept of software-defined energy networks in the context of industrial cyber-physical systems aiming at the optimal energy resource allocation in terms of its environmental impact. The task is formulated as a dynamic scheduling problem where supply and demand must match at minute-level timescale, also considering energy storage units. The use of (explainable and trustworthy) artificial intelligence (AI), (informative) networked data, demand-side management, machine-type (wireless) communications, and energy-aware scheduling in industrial plants are explored in detail. The paper also provides a framework for understanding the complexities of managing renewable energy sources in industrial plants while maintaining efficiency and environmental sustainability.
AB - This paper reviews the key information and communication technologies that are necessary to build an effective industrial energy management system considering the intermittence of renewable sources like wind and solar †. In particular, we first introduce the concept of software-defined energy networks in the context of industrial cyber-physical systems aiming at the optimal energy resource allocation in terms of its environmental impact. The task is formulated as a dynamic scheduling problem where supply and demand must match at minute-level timescale, also considering energy storage units. The use of (explainable and trustworthy) artificial intelligence (AI), (informative) networked data, demand-side management, machine-type (wireless) communications, and energy-aware scheduling in industrial plants are explored in detail. The paper also provides a framework for understanding the complexities of managing renewable energy sources in industrial plants while maintaining efficiency and environmental sustainability.
KW - Energy management
KW - Energy Modeling
KW - Energy resources
UR - http://www.scopus.com/inward/record.url?scp=85179752441&partnerID=8YFLogxK
U2 - 10.1016/j.isci.2023.108415
DO - 10.1016/j.isci.2023.108415
M3 - Article
AN - SCOPUS:85179752441
SN - 2589-0042
VL - 26
JO - iScience
JF - iScience
IS - 12
M1 - 108415
ER -