arXiv subjects

Edgar Jungblut

Publications and source records attributed to Edgar Jungblut.

4 recordsLinked to original sources

arXiv2024

Automated and Connected Driving: State-of-the-Art and Implications for Future Scenario Analysis

Automated driving can have a huge impact on the transport system in passenger, as well as freight applications; however, market and technological development are difficult to foresee. Therefore, a systems analysis is called for to answer the question: What is the impact of automated driving on the techno-economic performance of transport systems? It is important to quantify the potential impacts not only on a local scale and for specific use cases but for entire transport systems at large. Here, we provide an overview of the current state of automated driving, including academic research in addition to industrial development. For industrial development, we find that it will take at least until 2030-2040 for automated vehicles to be widely available for passenger transport. For freight transport on the other hand, automated vehicles might already be used within the next years at least on motorways. For academic research, we find that most studies on passenger transport consider shared automated vehicles separated from other transport modes and consider specific regions only. For freight transport we find that operational strategies and usage potentials for level 4 and 5 trucks lack alignment with real-life use cases and driving profiles. Based on this, we develop an analytical framework for future research. This includes a mode choice model for passenger transport demand calculations, a total cost of ownership model for freight trucks, transport statistics for freight flows, a microscopic traffic simulation to assess the impact of automated vehicles on traffic flow, and a road network analysis.

physics.soc-ph↗

arXiv2023

Spatial Structures of Wind Farms: Correlation Analysis of the Generated Electrical Power

We investigate the interaction of many wind turbines in a wind farm with a focus on their electrical power production. The operational data of two offshore wind farms with a ten minute and a ten second time resolution, respectively, are analyzed. For the correlations of the active power between turbines over the entire wind farms, we find a dominant collective behavior. We manage to subtract the collective behavior and find a significant dependence of the correlation structure on the spatial structure of the wind farms. We further show a connection between the observed correlation structures and the prevailing wind direction. We attribute the differences between the two wind farms to the differences in the turbine spacing within the two wind farms.

stat.AP↗

arXiv2023

Non-stationarity in correlation matrices for wind turbine SCADA-data and implications for failure detection

Modern utility-scale wind turbines are equipped with a Supervisory Control And Data Acquisition (SCADA) system gathering vast amounts of operational data that can be used for analysis to improve operation and maintenance of turbines. We analyze high frequency SCADA-data from the Thanet offshore wind farm in the UK and evaluate Pearson correlation matrices for a variety of observables with a moving time window. This renders possible a quantitative assessment of non-stationarity in mutual dependencies of different types of data. We show that a clustering algorithm applied to the correlation matrices reveals distinct correlation structures for different states. Looking first at only one and then at multiple turbines, the main dependence of these states is shown to be on wind speed. This is in accordance with known turbine control systems, which change the behavior of the turbine depending on the available wind speed. We model the boundary wind speeds separating the states based on the clustering solution. Our analysis shows that for high frequency data the control mechanisms of a turbine lead to detectable non-stationarity in the correlation matrix. The presented methodology allows accounting for this with an automated pre-processing by sorting new data based on wind speed and comparing it to the respective operational state, thereby taking the non-stationarity into account for an analysis.

stat.AP↗

arXiv2022

Two Price Regimes in Limit Order Books: Liquidity Cushion and Fragmented Distant Field

The distribution of liquidity within the limit order book is essential for the impact of market orders on the stock price and the emergence of price shocks. Limit orders are characterized by stylized facts: The number of inserted limit orders declines with the price distance from the quotes following a power law and limit order lifetimes and volumes are power law distributed. Strong dependencies among these quantities add to the complexity of limit order books. Here we analyze the limit order book in the dimensions of price, time, limit order lifetime and volume altogether. This allows us to identify regularities which are not visible in marginal distributions. Particularly we find that the limit order book is divided into two regimes. Around the quotes we find a densely filled regime with mostly short living limit orders closely adapting to the price. Far away from the quotes we find a sparse filling with long living limit orders, mostly inserted at particular times of the day being prone to flash crashes. We determine the characteristics of those two regimes and point out the main differences. Based on our research we propose a model for simulating the regime around the quotes.

q-fin.ST↗