@phdthesis{Abang, author = {Abang, Roger Atini}, title = {Thermodynamic modeling and experimental investigations of high temperature corrosion and oxidation due to increased power plant cycling}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus4-40032}, pages = {201}, language = {en} } @misc{SakkasRoger, author = {Sakkas, Nikolaos Panagiotis and Roger, Abang}, title = {Thermal load prediction of communal district heating systems by applying data-driven machine learning methods}, series = {Energy Reports}, volume = {8}, journal = {Energy Reports}, issn = {2352-4847}, doi = {10.1016/j.egyr.2021.12.082}, pages = {1883 -- 1895}, abstract = {Load forecasting is an essential part of the operational management of combined heat and electrical power units, since a reliable hour- and day-ahead estimation of their thermal and electrical load can significantly improve their technical and economic performance, as well as their reliability. Among different types of prediction techniques, data-driven machine learning methods appear to be more suitable for load estimation in operational systems, compared to the classical forward approach. Research so far has been concentrated mainly on the magnitude of buildings with single load types. It has only been extended to a limited degree on the level of a district heating network where several end users with different characteristics merge into one bigger scale heat consumer (city or group of communities). In this study, artificial neural networks are utilized, to develop a load prediction model for district heating networks. A segmented analytical multi-phase approach is employed, to gradually optimize the predictor by varying the characteristics of the input variables and the structure of the neural network. The comparison against the load prediction time series generated by a local communal energy supplier using a commercial software reveals that, although the latter is enhanced by manual human corrections, the optimized fully automatic predictors developed in the present study generate a more reliable load forecast.}, language = {en} } @inproceedings{CorreadaSilvaKrautz, author = {Correa da Silva, Rodrigo and Krautz, Hans Joachim}, title = {Theoretical investigation of pulverized coal combustion in air and in O2/CO2 atmospheres}, language = {en} } @inproceedings{CorreadaSilvaKrautz, author = {Correa da Silva, Rodrigo and Krautz, Hans Joachim}, title = {Theoretical analysis of heat transfer in a pulverized coal combustion chamber under O2/CO2 atmosphere}, language = {en} } @inproceedings{KassTappeKrautz, author = {Kaß, Helge and Tappe, Stephanie and Krautz, Hans Joachim}, title = {The combustion of dry lignite under Oxyfuel process conditions in a 0.5 MWth test plant}, language = {en} } @misc{MieckKrautz, author = {Mieck, Sebastian and Krautz, Hans Joachim}, title = {Systematic analysis and preparation of high resolution in-situ measurements for the estimation of PV module parameters}, series = {VGB PowerTech}, volume = {98}, journal = {VGB PowerTech}, number = {8}, issn = {1435-3199}, pages = {75 -- 81}, abstract = {In the last two decades, a rapid expansion of photovoltaic (PV) power plants of different sizes has taken place. Along with this, the interest from science and industry is growing, exploring the strengths and weaknesses of this technology as well as further developing the efficiency in its production and operation. For planning and operating of PV power plants, valid energy yield forecasts are desirable. These forecasts are also important to draw conclusions for the monitoring of future PV technologies. The analysis, evaluation and processing of meteorological and technical measurement datasets play an essential role. In this article, high-resolution measurement data sets of a mobile, autarkic test system are analyzed firstly. The measured data are checked for plausibility and validity with the corresponding methods. After this observations and phenomena with meteorological cause are described. In a second step, a practicable procedure for the preparation of the measurement data is presented, in order to make it suitable for further calculations, e.g. identification of photovoltaic module parameters for energy yield calculations. The focus is particularly on the flexibility, adaptability and code performance of the processing procedure. Results, evaluations and outlooks on the methods used, measurement data and selected software packages are made.}, language = {en} } @inproceedings{RombrechtKrautz, author = {Rombrecht, Hans-Bernd and Krautz, Hans Joachim}, title = {Results and operation experiences of the lignite fired laboratory-scale plant with pressurized circulating fluidized bed combustion of the 2nd generation (PFBC)}, language = {en} } @inproceedings{RistauMrozKrautz, author = {Ristau, Herbert and Mroz, Marcin and Krautz, Hans Joachim}, title = {Research and Development of Progressive Power Plant Techniques at the Brandenburg University of Technology Cottbus}, language = {en} } @inproceedings{FischerTannertVoigtetal., author = {Fischer, Ulrich and Tannert, Daniel and Voigt, Andre and Ziems, Christian and Krautz, Hans Joachim and Barz, Mirko and Dinkler, Konstantin}, title = {Renewable Energy Storage by Hydrogen Production from Water Electrolysis}, series = {Technical and Economic Aspects of Renewable Energies - Know-How Transfer as Development Opportunity for Southern Europe}, booktitle = {Technical and Economic Aspects of Renewable Energies - Know-How Transfer as Development Opportunity for Southern Europe}, publisher = {Mensch und Buch}, address = {Berlin}, isbn = {978-3-86387-721-7}, pages = {118 -- 126}, language = {en} } @misc{KatzerBabulKlattetal., author = {Katzer, Christian and Babul, Konrad and Klatt, Matthias and Krautz, Hans Joachim}, title = {Quantitative und qualitative relationship between swirl burner operating conditions and pulverized coal flame length}, series = {Fuel Processing Technology}, volume = {156}, journal = {Fuel Processing Technology}, issn = {0378-3820}, doi = {10.1016/j.fuproc.2016.10.013}, pages = {138 -- 155}, language = {en} }