Search Results for author: Veit Hagenmeyer

Found 29 papers, 12 papers with code

Non-standard power grid frequency statistics in Asia, Australia, and Europe

1 code implementation31 Aug 2023 Xinyi Wen, Mehrnaz Anvari, Leonardo Rydin Gorjao, G. Cigdem Yalcin, Veit Hagenmeyer, Benjamin Schafer

Furthermore, we emphasize the need to analyze data from a large range of synchronous areas to obtain generally applicable models.

Advancing Distributed AC Optimal Power Flow for Integrated Transmission-Distribution Systems

no code implementations25 Aug 2023 Xinliang Dai, Junyi Zhai, Yuning Jiang, Yi Guo, Colin N. Jones, Veit Hagenmeyer

This paper introduces a distributed operational solution for coordinating integrated transmission-distribution (ITD) systems regarding data privacy.

Computational Efficiency energy management +1

Transformer Training Strategies for Forecasting Multiple Load Time Series

1 code implementation19 Jun 2023 Matthias Hertel, Maximilian Beichter, Benedikt Heidrich, Oliver Neumann, Benjamin Schäfer, Ralf Mikut, Veit Hagenmeyer

We evaluate whether a Transformer load forecasting model benefits from a transfer learning strategy, where a global univariate model is trained on the load time series from multiple clients.

Load Forecasting Time Series +1

ProbPNN: Enhancing Deep Probabilistic Forecasting with Statistical Information

no code implementations6 Feb 2023 Benedikt Heidrich, Kaleb Phipps, Oliver Neumann, Marian Turowski, Ralf Mikut, Veit Hagenmeyer

Therefore, in the present paper, we introduce a deep learning-based method that considers these calendar-driven periodicities explicitly.

Time Series Time Series Analysis

Creating Probabilistic Forecasts from Arbitrary Deterministic Forecasts using Conditional Invertible Neural Networks

no code implementations3 Feb 2023 Kaleb Phipps, Benedikt Heidrich, Marian Turowski, Moritz Wittig, Ralf Mikut, Veit Hagenmeyer

More specifically, we apply a cINN to learn the underlying distribution of the data and then combine the uncertainty from this distribution with an arbitrary deterministic forecast to generate accurate probabilistic forecasts.

Occupant-Oriented Demand Response with Multi-Zone Thermal Building Control

1 code implementation9 Jan 2023 Moritz Frahm, Thomas Dengiz, Philipp Zwickel, Heiko Maaß, Jörg Matthes, Veit Hagenmeyer

In future energy systems with high shares of renewable energy sources, the electricity demand of buildings has to react to the fluctuating electricity generation in view of stability.

Model Predictive Control

AutoPV: Automated photovoltaic forecasts with limited information using an ensemble of pre-trained models

no code implementations13 Dec 2022 Stefan Meisenbacher, Benedikt Heidrich, Tim Martin, Ralf Mikut, Veit Hagenmeyer

To tackle the problem of missing information about the PV mounting configuration, we use new data that become available during operation to adapt the ensemble weights to minimize the forecasting error.

Analytical Uncertainty Propagation for Multi-Period Stochastic Optimal Power Flow

1 code implementation6 Dec 2022 Rebecca Bauer, Tillmann Mühlpfordt, Nicole Ludwig, Veit Hagenmeyer

The increase in renewable energy sources (RESs), like wind or solar power, results in growinguncertainty also in transmission grids.

Predicting the power grid frequency of European islands

no code implementations27 Sep 2022 Thorbjørn Lund Onsaker, Heidi S. Nygård, Damià Gomila, Pere Colet, Ralf Mikut, Richard Jumar, Heiko Maass, Uwe Kühnapfel, Veit Hagenmeyer, Benjamin Schäfer

In the present paper, we utilize measurements of the power grid frequency obtained in European islands: the Faroe Islands, Ireland, the Balearic Islands and Iceland and investigate how their frequency can be predicted, compared to the Nordic power system, acting as a reference.

Analytical Uncertainty Propagation for Multi-Period Stochastic Optimal Power Flow

1 code implementation12 Apr 2022 Rebecca Bauer, Tillmann Mühlpfordt, Nicole Ludwig, Veit Hagenmeyer

One key strategy to cope with this uncertainty is the use of distributed energy storage systems (ESSs).

Rapid Scalable Distributed Power Flow with Open-Source Implementation

1 code implementation30 Mar 2022 Xinliang Dai, Yichen Cai, Yuning Jiang, Veit Hagenmeyer

This new variant is characterized by using a reduced modelling method of the distributed AC PF problem, which is reformulated as a zero-residual least-squares problem with consensus constraints.

ALDI++: Automatic and parameter-less discord and outlier detection for building energy load profiles

1 code implementation13 Mar 2022 Matias Quintana, Till Stoeckmann, June Young Park, Marian Turowski, Veit Hagenmeyer, Clayton Miller

Data-driven building energy prediction is an integral part of the process for measurement and verification, building benchmarking, and building-to-grid interaction.

Benchmarking BIG-bench Machine Learning +1

Automated generation of large-scale distribution grid models based on open data and open source software using an optimization approach

no code implementations28 Feb 2022 Hüseyin K. Çakmak, Luc Janecke, Veit Hagenmeyer

The increasing share of renewable energy sources on distribution grid level as well as the emerging active role of prosumers lead to both higher distribution grid utilization, and at the same time greater unpredictability of energy generation and consumption.

What ODE-Approximation Schemes of Time-Delay Systems Reveal about Lyapunov-Krasovskii Functionals

no code implementations26 Feb 2022 Tessina H. Scholl, Veit Hagenmeyer, Lutz Gröll

A core insight is that the Lyapunov-Krasovskii theorem resembles a theorem for Lyapunov-Rumyantsev partial stability in ODEs.

Numerical Integration

Review of automated time series forecasting pipelines

no code implementations3 Feb 2022 Stefan Meisenbacher, Marian Turowski, Kaleb Phipps, Martin Rätz, Dirk Müller, Veit Hagenmeyer, Ralf Mikut

We conclude that future research has to holistically consider the automation of the forecasting pipeline to enable the large-scale application of time series forecasting.

Feature Engineering Hyperparameter Optimization +2

Smart Data Representations: Impact on the Accuracy of Deep Neural Networks

1 code implementation17 Nov 2021 Oliver Neumann, Nicole Ludwig, Marian Turowski, Benedikt Heidrich, Veit Hagenmeyer, Ralf Mikut

In the present paper, we analyze the impact of data representations on the performance of Deep Neural Networks using energy time series forecasting.

Time Series Time Series Forecasting

Concepts for Automated Machine Learning in Smart Grid Applications

no code implementations26 Oct 2021 Stefan Meisenbacher, Janik Pinter, Tim Martin, Veit Hagenmeyer, Ralf Mikut

Forecasts are elementary for sector coupling, where energy-consuming sectors are interconnected with the power-generating sector to address electricity storage challenges by adding flexibility to the power system.

Autonomous Vehicles BIG-bench Machine Learning +2

The strong effect of network resolution on electricity system models with high shares of wind and solar

no code implementations22 Jan 2021 Martha Maria Frysztacki, Jonas Hörsch, Veit Hagenmeyer, Tom Brown

If we focus on the effect of renewable resource resolution and ignore network restrictions, we find that a higher resolution allows the optimal solution to concentrate wind and solar capacity at sites with better capacity factors and thus reduces system costs by up to 10% compared to a low resolution model.

Physics and Society Computation

Data-Driven Copy-Paste Imputation for Energy Time Series

1 code implementation5 Jan 2021 Moritz Weber, Marian Turowski, Hüseyin K. Çakmak, Ralf Mikut, Uwe Kühnapfel, Veit Hagenmeyer

The CPI method copies data blocks with similar properties and pastes them into gaps of the time series while preserving the total energy of each gap.

Fault Detection Imputation +5

Mitigating heat demand peaks in buildings in a highly renewable European energy system

no code implementations3 Dec 2020 Elisabeth Zeyen, Veit Hagenmeyer, Tom Brown

Space and water heating accounts for about 40% of final energy consumption in the European Union and thus plays a key role in reducing overall costs and greenhouse gas emissions.

Physics and Society

Distributed Power Flow and Distributed Optimization -- Formulation, Solution, and Open Source Implementation

2 code implementations20 Nov 2020 Tillmann Mühlpfordt, Xinliang Dai, Alexander Engelmann, Veit Hagenmeyer

Solving the power flow problem in a distributed fashion empowers different grid operators to compute the overall grid state without having to share grid models-this is a practical problem to which industry does not have off-the-shelf answers.

Optimization and Control Systems and Control Systems and Control

A novel receiver design for energy packet-based dispatching

no code implementations1 Nov 2020 Friedrich Wiegel, Edoardo De Din, Antonello Monti, Klaus Wehrle, Marc Hiller, Martina Zitterbart, Veit Hagenmeyer

By means of a DC grid example, simulation results show the performance and applicability of the proposed novel receiver for packet-based energy dispatching.

Integrating Battery Aging in the Optimization for Bidirectional Charging of Electric Vehicles

no code implementations23 Sep 2020 Karl Schwenk, Stefan Meisenbacher, Benjamin Briegel, Tim Harr, Veit Hagenmeyer, Ralf Mikut

Smart charging of Electric Vehicles (EVs) reduces operating costs, allows more sustainable battery usage, and promotes the rise of electric mobility.

Database of Power Grid Frequency Measurements

no code implementations2 Jun 2020 Richard Jumar, Heiko Maaß, Benjamin Schäfer, Leonardo Rydin Gorjão, Veit Hagenmeyer

Data were collected using a self-developed measurement instrument, the Electrical Data Recorder (EDR), connected mostly to conventional power sockets.

PolyChaos.jl -- A Julia Package for Polynomial Chaos in Systems and Control

1 code implementation8 Apr 2020 Tillmann Mühlpfordt, Frederik Zahn, Veit Hagenmeyer, Timm Faulwasser

With PolyChaos we provide a Julia software package that delivers the desired functionality: given a probability density function, PolyChaos offers several numerical routines to construct the respective orthogonal polynomials, and the quadrature rules together with tensorized scalar products.

Systems and Control Numerical Analysis Systems and Control Numerical Analysis Optimization and Control

Cannot find the paper you are looking for? You can Submit a new open access paper.