TY - GEN
T1 - Load Profile Cycle Recognition for Industrial DC Microgrids with Energy Storage Systems
AU - Männel, Alexander
AU - Müller, Kevin
AU - Knöchelmann, Elias
AU - Ortmaier, Tobias
N1 - Funding information: VII. ACKNOWLEDGMENT This project was part of the DC-INDUSTRIE research project, funded by the German Federal ministry of Economic Affairs and Energy (BMWi). For further information see: www.dc-industrie.de. The authors would like to thank M. Schappler for revising this paper.
PY - 2020
Y1 - 2020
N2 - Many consumers in production plants like industrial robots or tool machines perform repetitive movements, which lead to a cyclic load demand. However, these load profiles can usually only be roughly estimated at the planning stage. Hence, a subsequent online adaptation of the energy distribution is useful for cases, such as balancing between the charging and discharging amount of energy storage systems to improve those lifetime and usage. This paper presents a novel method of online adaptation for the load distribution of production processes within industrial direct current (DC) microgrids. The online load profile cycle recognition was used to adapt the energy distribution among the sources and loads in the DC microgrid. These sources can be inverters, rectifiers, energy storage systems or decentralized power supply units, such as photo voltaic systems. The approach consists of three major points, the load profile cycle recognition, the load profile analysis and the online adaptation of the energy distribution. This solution was tested in simulation and in experiment with a test rig, that contains an inverter and an energy storage system. The results show, that the load profile will be recognized latest from the third cycle and that the imbalance between charging and discharging amounts of the energy storage is less than 0.6% for each cycle after adaptation.
AB - Many consumers in production plants like industrial robots or tool machines perform repetitive movements, which lead to a cyclic load demand. However, these load profiles can usually only be roughly estimated at the planning stage. Hence, a subsequent online adaptation of the energy distribution is useful for cases, such as balancing between the charging and discharging amount of energy storage systems to improve those lifetime and usage. This paper presents a novel method of online adaptation for the load distribution of production processes within industrial direct current (DC) microgrids. The online load profile cycle recognition was used to adapt the energy distribution among the sources and loads in the DC microgrid. These sources can be inverters, rectifiers, energy storage systems or decentralized power supply units, such as photo voltaic systems. The approach consists of three major points, the load profile cycle recognition, the load profile analysis and the online adaptation of the energy distribution. This solution was tested in simulation and in experiment with a test rig, that contains an inverter and an energy storage system. The results show, that the load profile will be recognized latest from the third cycle and that the imbalance between charging and discharging amounts of the energy storage is less than 0.6% for each cycle after adaptation.
KW - Cycle Recognition
KW - Energy Storage Systems
KW - Industrial DC Microgrid
KW - Online Adaptation
KW - Voltage Droop Control
UR - https://www.scopus.com/pages/publications/85089477640
U2 - 10.15488/10381
DO - 10.15488/10381
M3 - Conference contribution
AN - SCOPUS:85089477640
SN - 978-1-7281-5636-1
T3 - Proceedings of the IEEE International Symposium on Industrial Electronics
SP - 904
EP - 911
BT - 2020 IEEE 29th International Symposium on Industrial Electronics (ISIE)
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 29th IEEE International Symposium on Industrial Electronics, ISIE 2020
Y2 - 17 June 2020 through 19 June 2020
ER -