Mathematical Model of Biomass Boiler for Control Purposes

Práce se zabývá vytvořením dynamického matematického modelu biomasového kotle jako regulované soustavy a praktickým využitím tohoto modelu. V úvodní části práce je představena problematika energetického využívání biomasy a popsán aktuální vývoj v oblasti automatického řízení biomasových kotlů středních výkonů (jednotky MW). Přesto, že je tématem práce tvorba matematického modelu pro účely řízení, pozornost je věnována také technologii kotlů a fyzikální podstatě dějů, které v nich probíhají. Tvorba modelu vychází nejenom z těchto důležitých poznatků, ale také z experimentálních dat získaných během měření v reálném provozu. Na základě získaných dat byly provedeny bilanční výpočty sloužící k upřesnění statických vlastností experimentální jednotky pro spalování biomasy. Ustřední část práce popisuje tvorbu dynamického matematického modelu, který vycházel právě z těchto bilančních výpočtů a dále z naměřených přechodových charakteristik systému. Sestavený dynamický model byl ověřen porovnáním s experimentálními daty pomocí simulací v programu Simulink. Model regulované soustavy je v další části práce doplněn modelem regulátoru a následnou simulací je ověřena platnost celého zapojení. Dále je proveden návrh nové struktury řízení, která s sebou přináší výrazné zlepšení kvality regulace. V závěru práce jsou uvedeny možnosti dalšího využití modelu kotle v teorii automatického řízení i průmyslové praxi.he thesis focuses on building of dynamic mathematical model of biomass boiler as a controlled system and the use of this model in practise. At the first part of the thesis the area of energy production using biomass is introduced and the current development at the area of the automatic control of biomass boilers with medium energy output (in units of MW) is described. Although the main topic of the thesis is the construction of model of biomass boiler for control purposes, thesis deals with technology of boilers and principles of its inner processes as well. Creation of the model comes out not only from these important findings, but also from experimental data collected during measurements in real operation. Heat and mass balance calculations were made according to these data and they serve to precise static properties of experimental unit for biomass combustion. Central part of the thesis presents development of the final model that resulted from balance calculations and from step responses of the system obtained by measuring. Built dynamic model is compared with experimental data through simulations in Simulink and verified. At the next part the model of controlled system is completed with control system and closed-loop control circuit is validated and verified by simulation. Then the design of new controller configuration, which improves the quality of control considerably, is presented. At the final part of the thesis, possibilities of other use of the model of boiler are given, both in control theory and in industrial practice.

Catalytic thermal degradation of Chlorella Vulgaris: Evolving deep neural networks for optimization

The aim of this study is to identify the optimum thermal conversion of Chlorella vulgaris with neuro-evolutionary approach. A Progressive Depth Swarm-Evolution (PDSE) neuro-evolutionary approach is proposed to model the Thermogravimetric analysis (TGA) data of catalytic thermal degradation of Chlorella vulgaris. Results showed that the proposed method can generate predictions which are more accurate compared to other conventional approaches (>90% lower in Root Mean Square Error (RMSE) and Mean Bias Error (MBE)). In addition, Simulated Annealing is proposed to determine the optimal operating conditions for microalgae conversion from multiple trained ANN. The predicted optimum conditions were reaction temperature of 900.0 °C, heating rate of 5.0 °C/min with the presence of HZSM-5 zeolite catalyst to obtain 88.3% of Chlorella vulgaris conversion

Catalytic thermal degradation of Chlorella Vulgaris: Evolving deep neural networks for optimization

The aim of this study is to identify the optimum thermal conversion of Chlorella vulgaris with neuro-evolutionary approach. A Progressive Depth Swarm-Evolution (PDSE) neuro-evolutionary approach is proposed to model the Thermogravimetric analysis (TGA) data of catalytic thermal degradation of Chlorella vulgaris. Results showed that the proposed method can generate predictions which are more accurate compared to other conventional approaches (>90% lower in Root Mean Square Error (RMSE) and Mean Bias Error (MBE)). In addition, Simulated Annealing is proposed to determine the optimal operating conditions for microalgae conversion from multiple trained ANN. The predicted optimum conditions were reaction temperature of 900.0 °C, heating rate of 5.0 °C/min with the presence of HZSM-5 zeolite catalyst to obtain 88.3% of Chlorella vulgaris conversion

A Novel Check-List Strategy to Evaluate the Potential of Operational Improvements in Wastewater Treatment Plants

With increasing demands for cleaning and purification of water, wastewater treatment plants (WWTP) require their most efficient operation. The operators are thus obliged to constantly review the efficiency of the processing units and technological equipment of WWTPs and seek opportunities for improvements. To increase the efficiency of particular equipment, the important parameters to be used for the intensification must be correctly selected. A common WWTP consists of different types of processing units, where the basic parameters can be changed to achieve the highest efficiency (i.e. maximum output with minimum energy consumption) in the WWTP. However, due to many possible technologies in the wastewater treatment process, the combinations of processing units can be complex. In such cases, the efficiency assessment can be misleading if only basic parameters were accessed. Moreover, single-unit intensification can potentially improve the efficiency of the unit itself, but cannot guarantee full process improvement. This can be due to negative causal effects in the downstream due to that unit intensification. This work reviews of key parameters at selected five WWTP equipment (inlet pump station, airlift pump, primary sedimentation tank, aeration chamber and mixing of anaerobic digester) to demonstrate the correct selection of all affected parameters for the efficiency assessment. In the context of the whole WWTP process, it is necessary to take into account several other parameters to evaluate the efficiency of the equipment. Finally, a methodology for assessing the significance of the identified parameters is proposed. This methodology is effectively applied and demonstrated to the WWTP case study

Rotary Kiln, a Unit on the Border of the Process and Energy Industry—Current State and Perspectives

A rotary kiln is a unique facility with widespread applications not only in the process industry, such as building-material production, but also in the energy sector. There is a lack of a more comprehensive review of this facility and its perspectives in the literature. This paper gives a semi-systematic review of current research. Main trends and solutions close to commercial applications are found and evaluated. The overlap between process and energy engineering brings the opportunity to find various uncommon applications. An example is a biogas plant digestate treatment using pyrolysis in the rotary kiln. Artificial intelligence also finds its role in rotary kiln control processes. The most significant trend within rotary kiln research is the waste-to-energy approach in terms of various waste utilization within the process industry or waste pyrolysis in terms of new alternative fuel production and material utilization. Results from this review could open new perspectives for further research, which should be focused on integrated solutions using a process approach. New, complex solutions consider both the operational (mass calculations) and the energy aspects (energy calculations) of the integration as a basis for the energy sustainability and low environmental impact of rotary kilns within industrial processes

Rotary Kiln, a Unit on the Border of the Process and Energy Industry—Current State and Perspectives

A rotary kiln is a unique facility with widespread applications not only in the process industry, such as building-material production, but also in the energy sector. There is a lack of a more comprehensive review of this facility and its perspectives in the literature. This paper gives a semi-systematic review of current research. Main trends and solutions close to commercial applications are found and evaluated. The overlap between process and energy engineering brings the opportunity to find various uncommon applications. An example is a biogas plant digestate treatment using pyrolysis in the rotary kiln. Artificial intelligence also finds its role in rotary kiln control processes. The most significant trend within rotary kiln research is the waste-to-energy approach in terms of various waste utilization within the process industry or waste pyrolysis in terms of new alternative fuel production and material utilization. Results from this review could open new perspectives for further research, which should be focused on integrated solutions using a process approach. New, complex solutions consider both the operational (mass calculations) and the energy aspects (energy calculations) of the integration as a basis for the energy sustainability and low environmental impact of rotary kilns within industrial processes