Jenö Kovács

Oxidant control and air-oxy switching concepts for CFB furnace operation

Abstract Oxy combustion in circulating fluidized bed (CFB) boilers was investigated in this paper. Oxy combustion is a carbon capture and storage technology, which uses oxygen and recirculated flue gas (RFG) instead of air as an oxidant. Air and oxy combustion were compared through physical considerations and simulations, focusing on process dynamics, transients and control. The oxidant specific heat capacity and density are elevated in oxy combustion, which leads to slower temperature dynamics. Flue gas recirculation introduces internal feedback dynamics to the process. The possibility to adjust the RFG and oxygen flows separately gives an additional degree of freedom for control. In the simulations, “direct” and “sequenced” switches between air- and oxy-firing were compared. Fast “direct” switches with simultaneous ramping of all inputs should be preferred due to the resulting smooth temperature responses. If these process input changes are unfeasible, the fuel should be altered after the gaseous flows (“sequenced” method).

Short term optimization of district heating network supply temperatures

The increasing challenges in district heating operational optimization are briefly discussed. The paper describes the first steps in a research project on minimization of short term operational costs in a full scale district heating system. Based on a test model describing a part of a real district heating network, and a chosen approximate dynamic programming technique, simulations are used to illustrate and validate the fundamentals of the modelling and optimization approaches. It is concluded that the considered methods provide an adequate set of tools for the design of optimal network loading. The project is currently continuing with building of a more realistic dynamic model of the full-scale energy network and its components.

Cascade generalized predictive controller: two in one

The paper presents a cascade generalized predictive controller. The cascade control task is performed by one predictive controller and the cascade feature is incorporated in a special predictor. Simulation results are presented comparing the performances of the proposed control algorithm to traditional cascade loops including two PI or two GPC controllers. The paper investigates the effects of noise filter on the robustness of the control loops in the cascade control structure. It shows, that with the proposed predictor it is possible to adjust independently the robustness of the inner and outer loops, meanwhile in the traditional cascade loop there are cross effects in this sense. Finally a real time application of the proposed algorithm is presented: the cascade GPC was tested in the oxygen control loop of an experimental fluidized bed boiler.

FUZZY CONTROL OF COMBUSTION WITH GENETIC LEARNING AUTOMATA

Abstract It is difficult to achieve effective control of time variable and nonlinear plants such a fluidized bed boiler. A method of designing a nonlinear fuzzy controller is presented. However, its early application relied on trial and error in selecting either the fuzzy membership functions or the fuzzy rules. This made it heavily dependent on expert knowledge, which may not always available. Hence, an adaptive fuzzy logic controller such as Adaptive Neuro-Fuzzy Inference System (ANFIS) removes this stringent requirement. This paper demonstrates the application of ANFIS a nonlinear Multi Input Single Output fuel feeding and combustion system and a fuzzy controller design for the system with optimization with Genetic Learning Automata (GLA). An ANFIS model has been developed to determine the exact amount of fuel fed to a combustion chamber. This property is impossible to measure directly, but it is required for improving combustion control. The control of the combustion base on two Takagi-Sugeno type controllers, which were optimized by GLA. The control system has been validated on experiment data obtained in a case-study power plant. The results have shown that the system is able to capture the nonlinear feature of the fuel feeding system.

Advanced control: Simulation Tools in Labview Environment

Abstract A simulation package developed for advanced control education is reported in this paper. The package is aimed to assists students in acquiring the knowledge and to serve as an easy-to-use demonstration tool for lecturing. The simulation blocks, developed in LabVIEW™ environment, are listed and the effectiveness of the simulation package is demonstrated in examples.

Integrated Optimisation and Control System to Reduce Flue Gas Emissions

Abstract The control of the fluidised bed boilers can be studied as a layered system, which contains two main layers. The long-term operation of the process is optimised in the upper layer and the stabilising control loops are in the lower layer. These two main layers can be connected in a direct or indirect way. At the optimisation level, the flue gas emissions have to be minimised and the thermal efficiency of a boiler has to be maximised. The optirnisation is impossible, if stabilising controllers do not work properly. Combustion power control (CPC) is used to stabilise burning.

Analysis and tuning of a CFB model using particle filtering

Abstract Analysis and tuning of a circulating fluidized bed (CFB) hot-loop model are considered. Selected model outputs are fitted to measured data by allowing a set of constant-valued parameters to be considered as time-varying. These include the reaction rate, several heat transfer coefficients, and fuel moisture. Estimates of parameter distributions are created using particle filters (PF). PF provide a Bayesian approach utilizing both the system model and measured data. An illustrative example is given using data and model for a full scale plant.

Indirect Model Reference Adaptive PIP Control

Abstract The paper presents an extension of the proportional-integral-plus (PIP) control using model reference techniques and indirect adaptation. Recursive least squares method is used to estimate the process parameters. The constant trace method is treating the covariance matrix. The identifiability conditions may not be satisfied for every PIP structure. The global convergence of the RLS and the stability of the controlled process are ensured. Simulation is carried out to demonstrate the control properties. Satisfactory control performance - convergence and stability - is achieved in both deterministic and stochastic cases.

Integration of concentrated solar power (CSP) and circulating fluidized bed (CFB) power plants – final results of the COMBO-CFB project

Hybridization of solar energy together with another energy source is an option to provide heat and power reliably on demand. Hybridization allows decreasing combustion related fuel consumption and emissions, assuring stable grid connection and cutting costs of concentrated solar power technology due to shared power production equipment. The research project “Integration of Concentrated Solar Power (CSP) and Circulating Fluidized Bed (CFB) Power Plants” (COMBO-CFB) has been carried out to investigate the technical possibilities and limitations of the concept. The main focus was on the effect of CSP integration on combustion dynamics and on the joint power cycle, and on the interactions of subsystems. The research provides new valuable experimental data and knowhow about dynamic behaviour of CFB combustion under boundary conditions of the hybrid system. Limiting factors for maximum solar share in different hybridization schemes and suggestions for enhancing the performance of the hybrid system are derived.

Circulating fluidized bed boiler state estimation with an unscented Kalman filter tool

The paper discusses the development of a state estimation tool for circulating fluidized bed (CFB) boiler dynamic hotloop models. Bayesian state estimation was used to determine inputs, states and time-variant parameters based on output observations. The goal was to apply advanced state estimation to the original nonlinear model and utilize it for reallife CFB applications. The main algorithm of the tool was the unscented Kalman filter (UKF), with an SIR particle filter as a backup solution. The implementation of the tool and the UKF algorithm were described. The tool was tested with two simulation cases. In the first case, fuel flows and an air leakage parameter were identified based on flue gas compositions for pilot oxy combustion measurements. In the second case, heat transfer coefficient and fuel moisture content values were estimated in an industrial boiler based on the dense bed furnace temperature and the flue gas O2 content. The results showed a good agreement between measurements and simulations, as well as a good computational performance for the UKF.