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Data reconciliation of energy processes
Nováček, Adam ; Kuba, Pavel (referee) ; Touš, Michal (advisor)
This thesis is focused on problem data reconciliation of measurements. The objective of this thesis was reconciled measured value from electric drum dryer to suit exactly to the mathematical model of drying. For solution was used nonlinear data reconciliation with constrained nonlinear optimization. The entire calculation is processed in programme MATLAB and outputs are graphs of reconciled values of measurement on dryer such as inlet and outlet temperature and humidity, differential pressure of exhaust moisture air, weight of laundry, atmospheric pressure and electric supply. Achieved solution can by characterized by an amount of evaporated water. Weight of wet and dry laundry are 27,7 kg a 17,7 kg. The calculated amount of evaporated water from measurements was almost 18,8 kg. With reconciled measurements it was 9,7 kg. Goals of the thesis were found more realistic values.
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Data reconciliation and gross error detection
Nováček, Adam ; Šomplák, Radovan (referee) ; Touš, Michal (advisor)
Operational data are used for control and optimization of a process in industrial and energy plants are used. Data provided from measurement are affected by errors arising from uncertainty of measurement (imprecision of measuring instruments). Data reconciliation provides us more precise variables which give us the opportunity to better optimize and achieve higher economic gains. The objective of this bachelor's thesis was to study the issue of data reconciliation of measurement and gross error detection in measurement variables. This work is divided into two parts. The first part is theoretical, describing measurement errors, solution methods for data reconciliation and statistical tests for gross error detection. The second part is a practical demonstration of data reconciliation on two examples. The results of reconciliation and the solution procedure are included. Complete procedure can be found in the Annex.
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Analysis of Interactions in Waste Management
Szásziová, Lenka ; Hájek, Jiří (referee) ; Hrabec,, Dušan (referee) ; Stehlík, Petr (advisor)
PhD thesis deals with the application of simulation, forecasting and optimization methods in the waste management. An introduction describes current state and outlook in the waste management in the Czech Republic. The following chapter analyzes the available data base in the field of the waste management in the Czech Republic, focusing on the specifics and problems such as variable availability of spatially and hierarchically structured, heterogeneous input data. The core work is the computational tool named Justine, which represents the balance system, ensuring consistency of values for the standalone and aggregated data, in terms of their composition and distribution in intended area and time. Development of the tool was motivated by the need to predict the production and composition of various types of waste. The application of the concept is shown in three case studies, focusing on the prognosis of hazardous waste, the forecast of production and composition of municipal solid waste and components of separated waste collection, and estimation of the waste with waste-to-energy potential, all in the Czech Republic. The outputs of the tool represent valuable inputs for the related optimization supply chain models, which are used e.g. for the design of new waste-to-energy facilities.
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ADVANCED REGRESSION MODELS
Rosecký, Martin ; Popela, Pavel (referee) ; Bednář, Josef (advisor)
This thesis summarizes latest findings about municipal solid waste (MSW) modelling. These are used to solve multivariable version of inverse prediction problem. It is not possible to solve such problem analytically, so heuristic framework using regression models and data reconciliation was developed. As a side product, models for MSW modelling using PCA (Principal Component Analysis) and LM (Linear Model) were created. These were compared with heuristic model called RF (Random Forest). Both of these models were also used for per capita MSW modelling. Theoretical parts about generalized linear models, data reconciliation and nonlinear programming are also included.
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Advanced Prognostic Models in Waste Management
Smejkalová, Veronika ; Procházka,, Vít (referee) ; Slavík,, Jan (referee) ; Pavlas, Martin (advisor)
The issued Circular economy package defines the measures for the transition from a linear economy to a circular economy. The specific targets are implemented in the legislation of the EU Member States. Waste production forecasts are key information for modifying existing infrastructure to allow a smooth transition to a circular economy. This work presents a universal approach to waste production forecasting using optimization models including data preparation, calculation and processing into a suitable form for users. The forecast emphasizes the preparatory phases and the clean-up of input data from anomalies. The modeling principle is based on trend modeling in historical data with subsequent correction to restore the links between territorial divisions and waste fractions. Forecast uncertainty is described by confidence intervals constructed using a bootstrap approach. The impact of specific measures on the form of waste management can be modeled using projection. The presented methodology is developed in general and is a suitable basis for strategic planning at the local, national and supranational levels.
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ADVANCED REGRESSION MODELS
Rosecký, Martin ; Popela, Pavel (referee) ; Bednář, Josef (advisor)
This thesis summarizes latest findings about municipal solid waste (MSW) modelling. These are used to solve multivariable version of inverse prediction problem. It is not possible to solve such problem analytically, so heuristic framework using regression models and data reconciliation was developed. As a side product, models for MSW modelling using PCA (Principal Component Analysis) and LM (Linear Model) were created. These were compared with heuristic model called RF (Random Forest). Both of these models were also used for per capita MSW modelling. Theoretical parts about generalized linear models, data reconciliation and nonlinear programming are also included.
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Analysis of Interactions in Waste Management
Szásziová, Lenka ; Hájek, Jiří (referee) ; Hrabec,, Dušan (referee) ; Stehlík, Petr (advisor)
PhD thesis deals with the application of simulation, forecasting and optimization methods in the waste management. An introduction describes current state and outlook in the waste management in the Czech Republic. The following chapter analyzes the available data base in the field of the waste management in the Czech Republic, focusing on the specifics and problems such as variable availability of spatially and hierarchically structured, heterogeneous input data. The core work is the computational tool named Justine, which represents the balance system, ensuring consistency of values for the standalone and aggregated data, in terms of their composition and distribution in intended area and time. Development of the tool was motivated by the need to predict the production and composition of various types of waste. The application of the concept is shown in three case studies, focusing on the prognosis of hazardous waste, the forecast of production and composition of municipal solid waste and components of separated waste collection, and estimation of the waste with waste-to-energy potential, all in the Czech Republic. The outputs of the tool represent valuable inputs for the related optimization supply chain models, which are used e.g. for the design of new waste-to-energy facilities.
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Data reconciliation of energy processes
Nováček, Adam ; Kuba, Pavel (referee) ; Touš, Michal (advisor)
This thesis is focused on problem data reconciliation of measurements. The objective of this thesis was reconciled measured value from electric drum dryer to suit exactly to the mathematical model of drying. For solution was used nonlinear data reconciliation with constrained nonlinear optimization. The entire calculation is processed in programme MATLAB and outputs are graphs of reconciled values of measurement on dryer such as inlet and outlet temperature and humidity, differential pressure of exhaust moisture air, weight of laundry, atmospheric pressure and electric supply. Achieved solution can by characterized by an amount of evaporated water. Weight of wet and dry laundry are 27,7 kg a 17,7 kg. The calculated amount of evaporated water from measurements was almost 18,8 kg. With reconciled measurements it was 9,7 kg. Goals of the thesis were found more realistic values.
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