Pascal A. Schirmer
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Neuromorphic Information Coding in Power Electronic Grids - Concept and Modeling Open
Information coding plays a fundamental role in power electronic systems for data synthesis and processing. The emergence of neuromorphic intelligence has created new energyefficient and distributed computing opportunities in power electron…
An Instrumental High-Frequency Smart Meter with Embedded Energy Disaggregation Open
Most available smart meters sample at low rates and transmit the acquired measurements to a cloud server for further processing. This article presents a prototype smart meter operating at a high sampling frequency (15 kHz) and performing e…
On the Sensitivity Analysis in Reliability Evaluation for Power Electronic Converters Open
Power electronic converters are essential in modern electrical and electronic applications, necessitating the study on power electronic reliability for dependable design and operation. In earlier research on power electronic reliability, t…
Multivariate Constrained Elastic Matching With Application in Real-Time Energy Disaggregation Open
Non-Intrusive Load Monitoring (NILM) aims to estimate the power consumption of electrical appliances from the aggregated power consumption. While recent machine learning approaches have demonstrated very high disaggregation accuracies, ens…
PyDTS: A Python Toolkit for Deep Learning Time Series Modelling Open
In this article, the topic of time series modelling is discussed. It highlights the criticality of analysing and forecasting time series data across various sectors, identifying five primary application areas: denoising, forecasting, nonli…
Federated Computing in Electric Vehicles to Predict Coolant Temperature Open
Reducing greenhouse gas emissions in mobility is paramount to achieving a carbon-neutral society. However, battery-electrical vehicles (BEV) introduce unique engineering challenges to protect expensive electrical components from overheatin…
Zero-voltage and frequency pattern selection for DC-link loss minimization in PWM-VSI drives Open
The modulation of a voltage source inverter output causes losses and harmonic distortions on the load side and the DC-link capacitor due to the discrete switching of the semiconductors. High-frequent voltage pulses are digitally programmed…
2D Transformations of Energy Signals for Energy Disaggregation Open
The aim of Non-Intrusive Load Monitoring is to estimate the energy consumption of individual electrical appliances by disaggregating the overall power consumption that has been sampled from a smart meter at a house or commercial/industrial…
Device and Time Invariant Features for Transferable Non-Intrusive Load Monitoring Open
Non-Intrusive Load Monitoring aims to extract the energy consumption of individual electrical appliances through disaggregation of the total power consumption as measured by a single smart meter in a household. Although when data from the …
Double Fourier Integral Analysis Based Convolutional Neural Network Regression for High-Frequency Energy Disaggregation Open
© 2021 IEEE. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/ 10.1109/TETCI.2021.3086226
Identification of TV Channel Watching from Smart Meter Data Using Energy Disaggregation Open
Smart meters are used to measure the energy consumption of households. Specifically, within the energy consumption task, a smart meter must be used for load forecasting, the reduction in consumer bills as well as the reduction in grid dist…
Modelling of Electrical Appliance Signatures for Energy Disaggregation Open
The rapid development of technology in the electrical sector within the last 20 years has led to growing electric power needs through the increased number of electrical appliances and automation of tasks. In contrary, reduction of the over…
Reducing Grid Distortions Utilizing Energy Demand Prediction and Local Storages Open
© 2021 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
Binary versus Multiclass Deep Learning Modelling in Energy Disaggregation Open
This paper compares two different deep-learning architectures for the use in energy disaggregation and Non-Intrusive Load Monitoring. Non-Intrusive Load Monitoring breaks down the aggregated energy consumption into individual appliance con…
Identification of TV Channel Watching from Smart Meter Data Using Energy\n Disaggregation Open
Smart meters are used to measure the energy consumption of households.\nSpecifically, within the energy consumption task smart meter have been used for\nload forecasting, reduction of consumer bills as well as reduction of grid\ndistortion…
Energy Disaggregation Using Two-Stage Fusion of Binary Device Detectors Open
A data-driven methodology to improve the energy disaggregation accuracy during Non-Intrusive Load Monitoring is proposed. In detail, the method uses a two-stage classification scheme, with the first stage consisting of classification model…
Robust energy disaggregation using appliance-specific temporal contextual information Open
An extension of the baseline non-intrusive load monitoring approach for energy disaggregation using temporal contextual information is presented in this paper. In detail, the proposed approach uses a two-stage disaggregation methodology wi…
Energy Disaggregation Using Elastic Matching Algorithms Open
In this article an energy disaggregation architecture using elastic matching algorithms is presented. The architecture uses a database of reference energy consumption signatures and compares them with incoming energy consumption frames usi…
Statistical and Electrical Features Evaluation for Electrical Appliances Energy Disaggregation Open
In this paper we evaluate several well-known and widely used machine learning algorithms for regression in the energy disaggregation task. Specifically, the Non-Intrusive Load Monitoring approach was considered and the K-Nearest-Neighbours…