- Written by Dr. Thomas Fritsch
At the 8th Regensburg Transformer Symposium Dr. Thomas Fritsch will give a talk entitled „On the Current State of Artificial Intelligence (AI) and its (possible) Use in the Energy Industry“. The abstract to this can be found after the links to the organizer and the conference schedule.
Organizer: DTC Daemisch Transformer Consult
Schedule: Draft of the conference schedule (only available in German)
Speaker: Dr. Thomas Fritsch, CEO of Tokeya Deep Data Dive GmbH & Co. KG
Co-Speaker: Dr. Frank Wirner, CTO of Tokeya Deep Data Dive GmbH & Co. KG
Abstract:
The near-perfect concurrence of 4 fundamental technological trends – very fast (also parallel computers; very high communication and storage density (smartphones, tablets etc., cloud storage & computing); very large amounts of data (Big Data - e. g. from sensors) and very effective new algorithms (Deep Neural Networks) – has since 2012 experienced a breathtaking upturn in artificial intelligence (AI). Since then, the AI has penetrated important areas of society all over the world at an ever faster pace.
The talk will highlight the current state of development of the AI and explain why reporting on it is not a hype (this time). The working method of the main carriers of the AI, the (deep) neural networks (NN), is explained by means of practical examples from the energy technology and economy. It is made clear that this technology is a very efficient, because adaptive technical implementation of well-founded (complex) statistical learning procedures, which cannot be equated in any way with the known “expert systems” (and their weaknesses).
The topic of predictive maintenance of important equipment of the network infrastructure (e.g. of power transformers in the power grids), which is of interest to practitioners and participants of the transformer symposium, will be treated by means of an online software tool for the intelligent condition assessment of anonymized transformer data of an industrial partner as an example for the possible efficient use of AI methods in transformer diagnostics.
The talk concludes with an outlook on the presently foreseeable future development of the AI without succumbing to the usual and common threat scenarios or euphemisms of the potential actual dangers of the AI.
Slides of the talk: PDF Download (only available in German; new page 11)
In the talk addressed video: Google’s self-driving car
- Written by Dr. Thomas Fritsch
We are extremely pleased to announce our first order for 2018. We will be responsible for the company A. Eberle GmbH & Co. KG Nuremberg to implement the introduction of AI. The focus here is on devices from A. Eberle for the measurement of power quality parameters of power grids. AI is used here for time series prediction. By means of neural networks, qualitative changes in supply voltage and supply frequency are to be detected as well as faults in the networks are to be located.
- Written by Dr. Thomas Fritsch
We are pleased to announce that the project PoPAI (Power Prediction by AI) was successfully accepted by the company A. Eberle GmbH & Co. KG Nuremberg on 29th March 2018.
The PoPAI project dealt with the prediction of important parameters in the electricity grid such as voltage and frequency. For this purpose, standard models such as ARIMA and artificial neural networks were implemented. With a practical graphical frontend (web interface) the parameters of the prediction (period of the prediction, retrospective time lag window, data resolution, …) can be set and the results can be visualized. The quality of prediction was good, best was the prediction of the neural network.
An example prediction by the neural network (red) for 6 hours
and for 48 hours
- Written by Dr. Thomas Fritsch
The current data privacy statement is available in the „Contact“ menu at „Data privacy statement“. It is available only on German.
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