TY - GEN
T1 - Hybrid Physics and Machine Learning Models of Desktop-scale Naval Power Systems
AU - Overlin, Matthew
AU - McBain, Alexander
AU - Quattlebaum, Justin
AU - Roper, Joshua
AU - Thornton, Eric
AU - Iannucci, Steven
AU - Hultgren, Eric
N1 - Funding Information:
ACKNOWLEDGMENT The authors would like to acknowledge other personnel within PacMar Technologies who have provided valuable feedback regarding the work in this paper and the Office of Naval Research (ONR) for their financial support.
Publisher Copyright:
© 2023 IEEE.
PY - 2023/5/31
Y1 - 2023/5/31
N2 - The U.S. Navy is considering medium voltage DC (MVDC) power systems as opposed to traditional AC power systems in order to accommodate modern shipboard systems: high power sensors, electronic warfare, and weapons systems. A digital twin of an MVDC naval power system is useful so that its operation can be better understood. In this work, a scaled-down demonstration model of a modern MVDC naval power system is studied through a series of experiments showing the operational benefits of the system when implemented with digital twin technologies. Two portable hybrid unified models of the scaled demonstration system were developed with incorporated machine learning techniques to show improved autonomous control. Because the unified models are portable, they may be developed in one tool, but then used with another tool on another platform. In a field setting, for example, a unified model may be simulated alongside an actual Navy ship to better understand its operation and vice versa.
AB - The U.S. Navy is considering medium voltage DC (MVDC) power systems as opposed to traditional AC power systems in order to accommodate modern shipboard systems: high power sensors, electronic warfare, and weapons systems. A digital twin of an MVDC naval power system is useful so that its operation can be better understood. In this work, a scaled-down demonstration model of a modern MVDC naval power system is studied through a series of experiments showing the operational benefits of the system when implemented with digital twin technologies. Two portable hybrid unified models of the scaled demonstration system were developed with incorporated machine learning techniques to show improved autonomous control. Because the unified models are portable, they may be developed in one tool, but then used with another tool on another platform. In a field setting, for example, a unified model may be simulated alongside an actual Navy ship to better understand its operation and vice versa.
KW - Digital twin
KW - Hybrid power systems models
KW - Machine learning in power systems
KW - Naval power systems
UR - http://www.scopus.com/inward/record.url?scp=85162241930&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/4b10bcc2-f721-3162-8df3-73bb74bd4eec/
U2 - 10.1109/APEC43580.2023.10131490
DO - 10.1109/APEC43580.2023.10131490
M3 - Conference contribution
AN - SCOPUS:85162241930
SN - 9781665475396
T3 - 2023 IEEE Applied Power Electronics Conference and Exposition (APEC)
SP - 1802
EP - 1807
BT - Conference Proceedings - IEEE Applied Power Electronics Conference and Exposition - APEC
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th Annual IEEE Applied Power Electronics Conference and Exposition, APEC 2023
Y2 - 19 March 2023 through 23 March 2023
ER -