Marcus Voß

Marcus Voß
Technische Universität Berlin | TUB · Distributed Artificial Intelligence Laboratory

Master of Science

About

19
Publications
4,151
Reads
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105
Citations
Introduction
Currently working on data analysis of low-voltage level smart meter data and low-voltage load forecasting

Publications

Publications (19)
Conference Paper
Full-text available
The sample mean is one of the most fundamental concepts in statistics with far-reaching implications for data mining and pattern recognition. Household load profiles are compared to the aggregated levels more intermittent and a specific error measure based on local permutations has been proposed to cope with this when comparing profiles. We formall...
Article
Full-text available
The structural mass of a building provides inherent thermal storage capability. Through sector coupling, the building mass can provide additional flexibility to the electric power system, using, for instance, combined heat and power plants or power-to-heat. In this work, a mathematical model of building inertia thermal energy storage (BITES) for in...
Preprint
Full-text available
The increased digitalisation and monitoring of the energy system opens up numerous opportunities % and solutions which can help to decarbonise the energy system. Applications on low voltage (LV), localised networks, such as community energy markets and smart storage will facilitate decarbonisation, but they will require advanced control and managem...
Preprint
Full-text available
The transition to a fully renewable energy grid requires better forecasting of demand at the low-voltage level to increase efficiency and ensure reliable control. However, high fluctuations and increasing electrification cause huge forecast variability, not reflected in traditional point estimates. Probabilistic load forecasts take future uncertain...
Article
The increased digitalisation and monitoring of the energy system opens up numerous opportunities to decarbonise the energy system. Applications on low voltage, local networks, such as community energy markets and smart storage will facilitate decarbonisation, but they will require advanced control and management. Reliable forecasting will be a nece...
Conference Paper
Full-text available
Lowly aggregated load profiles such as of individual households or buildings are more fluctuating and relative forecast errors are comparatively high. Therefore, the prevalent point forecasts are not sufficiently capable of optimally capturing uncertainty and hence lead to non-optimal decisions in different operational tasks. We propose an approach...
Conference Paper
Full-text available
The increasing amount of both, renewable energy production and electric vehicle usage, puts considerable stress on smart grids, making it necessary to synchronize vehicle charging with energy production, but also allowing to use those vehicles as additional energy storages. In this paper, we combine machine learning and evolutionary algorithms to c...
Article
Due to the fact that electric vehicles have not broadly entered the vehicle market there are many attempts to convince producers to integrate technologies that utilise embedded batteries for purposes different from driving. The vehicle-to-grid technology, for instance, literally turns electric vehicles into a mobile battery, enabling new areas of a...
Conference Paper
Full-text available
With the current rise of electric vehicles, it is possible to use those vehicles for storing surplus energy from renewable energy sources; however, this can be in conflict with providing and ensuring the mobility of the vehicle’s user. At DAI-Labor, we have a large number of both, past and upcoming projects concerned with those two aspects of manag...
Conference Paper
There are many approaches to integrate electric vehicles into smart grid architectures by optimizing their charging- and feeding periods. Most approaches, however, were never applied in reality since every field-test requires an existing and expensive infrastructure. In this paper we compare the performance of four different scheduling algorithms....
Conference Paper
In this paper, we evaluate a time series based method for predicting the first daily departure time (FDDT) of commuter vehicles. This task is relevant for the grid integration of plug-in electric vehicles (PEVs), since it allows for actively managing their electricity demand during the connection interval. Our study is based on a sample of 445 vehi...

Questions

Question (1)
Question
For a industry research project we can get distribution grid models which they have modeled in PowerFactory. We would like to work with the models in OpenDSS and Matlab and of course would like to spare remodeling the grids in the software. I can't find anything online to achieve this.
Has anybody achieved exporting from PowerFactory to OpenDSS? Maybe even a self written script to achieve this which he/she is willing to share?
Kind regards,
Marcus

Network

Cited By

Projects

Projects (4)
Project
SINTEG drives forward the development of a smart energy supply: ● to identify flexibility potentials and strengthen sector coupling ● to develop flexibility mechanisms for grids ● to utilise digitisation as enabler and for value-added services in a smart energy system ● to be pioneers of feasible energy transition solutions by using regulatory sandboxes in real-world testing environments, and ● to increase citizen participation by creating insight and awakening passion for an opportunity-oriented energy system transformation. Project: www.sinteg.de/en/ for more details. LinkedIn Group: bit.ly/SINTEG-LI Who-is-Who: www.wirsinteg.de (also in EN)
Project
WindNODE is subsidized by the German Federal Ministry for Economic Affairs (BMWi) as a ‘smart energy showcase’. It demonstrates a network of flexible energy consumers who can align their consumption of electricity with the intermittent offer of wind and solar power stations. To achieve this goal we work on load forecasts of households and buildings.