Dipl.-Wirt.-Ing. Christian Hotz

Dipl.-Wirt.-Ing. Christian Hotz

Address
Hamburg University of Technology
Electrical Power and Energy Technology (ieet)
Harburger Schloßstraße 20
21079 Hamburg
Office
Building HS20
Room 4.14a
Phone
Tel: +49 40 42878 2378
Fax: +49 40 42878 2382
Email
christian.hotz(at)tuhh.de
Office Hours
Nach Absprache

Publications

[81813]
Title: Online Monitoring of Power System Small Signal Stability Using Artificial Neural Networks Proceedings of Conference on Sustainable Energy Supply and Energy Storage Systems (NEIS 2019)
Written by: Hotz, C.; Becker, C.
in: September 2019 2019
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Address: Hamburg
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[BibTex]

Note:

Abstract: Shifting paradigms in electrical power generation, transmission and consumption will affect system dynamics and may negatively influence its small signal stability in the long run. A smaller stability margin calls for smart methods to monitor the current state of the power system to be able to detect critical situations immediately. This paper proposes a method based on artificial neural networks that is capable of providing an online supervision service, which works in real-time due to its low demand for computational resources. Additionally, the requirements regarding system state information of such a monitoring system are investigated to assess the measurement and communication setup necessary for its proper functionality and thus its applicability to real power systems.

Supervised Theses (in progress)

[81813]
Title: Online Monitoring of Power System Small Signal Stability Using Artificial Neural Networks Proceedings of Conference on Sustainable Energy Supply and Energy Storage Systems (NEIS 2019)
Written by: Hotz, C.; Becker, C.
in: September 2019 2019
Volume: Number:
on pages:
Chapter:
Editor:
Publisher:
Series:
Address: Hamburg
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI:
URL:
ARXIVID:
PMID:

[BibTex]

Note:

Abstract: Shifting paradigms in electrical power generation, transmission and consumption will affect system dynamics and may negatively influence its small signal stability in the long run. A smaller stability margin calls for smart methods to monitor the current state of the power system to be able to detect critical situations immediately. This paper proposes a method based on artificial neural networks that is capable of providing an online supervision service, which works in real-time due to its low demand for computational resources. Additionally, the requirements regarding system state information of such a monitoring system are investigated to assess the measurement and communication setup necessary for its proper functionality and thus its applicability to real power systems.

Supervised Theses (finished)

[81813]
Title: Online Monitoring of Power System Small Signal Stability Using Artificial Neural Networks Proceedings of Conference on Sustainable Energy Supply and Energy Storage Systems (NEIS 2019)
Written by: Hotz, C.; Becker, C.
in: September 2019 2019
Volume: Number:
on pages:
Chapter:
Editor:
Publisher:
Series:
Address: Hamburg
Edition:
ISBN:
how published:
Organization:
School:
Institution:
Type:
DOI:
URL:
ARXIVID:
PMID:

[BibTex]

Note:

Abstract: Shifting paradigms in electrical power generation, transmission and consumption will affect system dynamics and may negatively influence its small signal stability in the long run. A smaller stability margin calls for smart methods to monitor the current state of the power system to be able to detect critical situations immediately. This paper proposes a method based on artificial neural networks that is capable of providing an online supervision service, which works in real-time due to its low demand for computational resources. Additionally, the requirements regarding system state information of such a monitoring system are investigated to assess the measurement and communication setup necessary for its proper functionality and thus its applicability to real power systems.