Ústav procesního inženýrství

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Industrial waste heat utilization in the European Union—An engineering-centric review
(MDPI, 2024-04-27) Turek, Vojtěch; Kilkovský, Bohuslav; Daxner, Ján; Babička Fialová, Dominika; Jegla, Zdeněk
Efficient utilization of waste heat from industrial processes can be a significant source of energy savings for production plants as well as the driver of sustainable operation and emissions abatement. Industrial waste heat usually is contained in liquid or gaseous outlet streams. Alt-hough the possible ways to utilize waste heat are discussed by a wide variety of papers, these either provide only a general overview of utilization options and opportunities or focus on a narrow range of industrial processes. The aim of the present paper is to discuss practical aspects of waste heat utilization in the European Union so that the reader gains perspective on (i) thermal classification of waste heat, (ii) liquid and gaseous waste streams and their temperatures typical for industrial use cases, (iii) technical, economic, physical, and environmental aspects barring full utilization of the contained heat, (iv) waste heat sources in various industries, and (v) standard-ized equipment and technologies applicable to industrial waste heat utilization, including their advantages, disadvantages and weak points.
Hierarchical optimisation model for waste management forecasting in EU
(SPRINGER, 2022-12-01) Smejkalová, Veronika; Šomplák, Radovan; Pluskal, Jaroslav; Rybová, Kristýna
The level of waste management varies significantly from one EU state to another and therefore they have different starting position regarding reaching defined EU targets. The forecast of waste production and treatment is essential information for the expected future EU targets fulfilment. If waste treatment does not meet the targets under the current conditions, it is necessary to change waste management strategies. This contribution presents a universal approach for forecasting waste production and treatment using optimisation models. The approach is based on the trend analysis with the subsequent data reconciliation (quadratic programming). The presented methodology also provides recommendations to include the quality of trend estimate and significance of territory in form of weights in objective function. The developed approach also allows to put into context different methods of waste handling and production. The variability of forecast is described by prediction and confidence intervals. Within the EU forecast, the expected demographic development is taken into account. The results show that most states will not meet EU targets with current trend of waste management in time. Presented methodology is developed at a general level and it is a suitable basis for strategic planning at the national and transnational level.
Optimal control of combined heat and power station operation
(Springer Nature, 2023-09-13) Kůdela, Jakub; Suja, Jerguš; Šomplák, Radovan; Pluskal, Jaroslav; Hrabec, Dušan
Combined heat and power stations have become one of the most utilized units of district heating systems. These stations usually contain several boilers for burning fossil fuels and renewable resources used for heating up steam, which can be used either for residential and commercial heating or electricity generation. To ensure efficiency, a boiler should either run continuously (for at least a given period) on a power output higher than a given threshold or switch off. The optimal control of the plant operations should combine an efficient setup for the turbine and boilers in operation, reflecting the demand for steam and the price of electricity, and a schedule that describes which boilers should be in operation at a given time. This paper proposes a method for optimal control of combined heat and power station operation for a given time horizon. The method is based on a two-level approach. The lower-level models correspond to finding the optimal setup of the combined heat and power station parameters for an hourly demand for different kinds of steam. The upper-level model corresponds to the optimal schedule of the operations of the individual boilers, which is planned for the entire time horizon. The lower-level model is modeled as a mixed-integer linear programming problem and is solved using parametric programming. A dynamic programming algorithm solves the upper-level model with a rolling horizon. The validity of the proposed method and its computational complexity for different granularity of the time horizon, different ranges of the parameters, varying demand for various kinds of steam, and varying electricity prices are investigated in a case study. The presented approach can be readily applied to other control problems with a similar structure.
Machine Learning Method for Changepoint Detection in Short Time Series Data
(MDPI, 2023-10-05) Smejkalová, Veronika; Šomplák, Radovan; Rosecký, Martin; Šramková, Kristína
Analysis of data is crucial in waste management to improve effective planning from both short- and long-term perspectives. Real-world data often presents anomalies, but in the waste management sector, anomaly detection is seldom performed. The main goal and contribution of this paper is a proposal of a complex machine learning framework for changepoint detection in a large number of short time series from waste management. In such a case, it is not possible to use only an expert-based approach due to the time-consuming nature of this process and subjectivity. The proposed framework consists of two steps: (1) outlier detection via outlier test for trend-adjusted data, and (2) changepoints are identified via comparison of linear model parameters. In order to use the proposed method, it is necessary to have a sufficient number of experts’ assessments of the presence of anomalies in time series. The proposed framework is demonstrated on waste management data from the Czech Republic. It is observed that certain waste categories in specific regions frequently exhibit changepoints. On the micro-regional level, approximately 31.1% of time series contain at least one outlier and 16.4% exhibit changepoints. Certain groups of waste are more prone to the occurrence of anomalies. The results indicate that even in the case of aggregated data, anomalies are not rare, and their presence should always be checked.
Using numerical dissipation rate and viscosity to assess turbulence-related data accuracy - Part 1: Experimental setup
(Wiley-VCH GmbH, 2023-08-22) Turek, Vojtěch; Jegla, Zdeněk; Dohnal, Miloslav; Reppich, Marcus
This is the first part of a two-part paper focusing on the assessment of accuracy of turbulence-related data from computational fluid dynamics (CFD) simulations using effective numerical dissipation rate and effective numerical viscosity. Setup of the CFD cases replicating a swirling pipe flow experiment from literature, for which turbulence-related data measured via laser Doppler anemometry (LDA) had been reported, is presented. The way effective numerical dissipation rate and effective numerical viscosity were obtained for each mesh cell is also discussed. The results of the study are presented in the second part of this series.

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