Development of a Solution for Start-up Optimization of a Thermal Power Plant

This thesis covers optimizing the first phase of the start-up of a thermal power plant using Nonlinear Model Predictive Control (NMPC) and state estimation using an Unscented Kalman Filter (UKF). The start-up has been optimized in regards to time and fuel usage. The thesis is done as a joint project between Vattenfall and Modelon. Both NMPC and UKF are nonlinear methods and require a model of the power plant. The model used in this thesis has been developed in the language Modelica in a previous master thesis and has been extended and improved upon during this thesis. The optimization and simulation of the model required by the NMPC and UKF was done within the framework of JModelica.org. Another, more detailed, model of the power plant, developed by Vattenfall, was originally planned to be used as the process to be controlled. State estimation using the UKF has been successful, with a maximum mean absolute error of 0.7 % when estimating the states of the detailed model in a reference startup. When using the NMPC to control the optimization model itself, the simulated start-up time is 70 minutes faster compared to a reference start-up using the detailed model. This is more than half the time of the first phase of the start-up. The total firing power, which relates to the fuel amount, is also considerably less, with the optimized value being about 40 % of that in the reference soft start with the detailed model. Due to difficulties in initializing the detailed model, it was not possible to run it online together with the NMPC and UKF. Running the NMPC and UKF together on the optimization model worked, but the NMPC failed to find an optimal trajectory 8 out of 10 iterations. The conclusion is that the start-up has potential for optimization, but requires more robust models to work with

Modelling and simulation of a coal-fired power plant for start-up optimisation

The increased impact from fluctuating energy sources like wind and photovoltaics significantly affects the operational regime of conventional power plants. In the near future, even former base load power plants such as the large-scale lignite plants in Germany will need to start and shut down to balance the electricity system. As frequent starts were not in the focus of optimisation in the past, an extensive potential can be expected to reduce start-up costs and environmental impacts. In order to investigate such optimisation potentials, a comprehensive dynamic simulation model has been developed including process components such as boiler and water-steam cycle but also the power plants control system along with start-up sequence control. After successfully reproducing a reference start of the power plant, the model has been used to identify restrictions for faster start-ups, less fuel consumption and less emission while keeping the thermal and mechanical stress, caused by higher ramp rates, within acceptable bounds

Behavioral Analysis of Dopaminergic Activation in Zebrafish and Rats Reveals Similar Phenotypes

Zebrafish is emerging as a complement to mammals in behavioral studies; however, there is a lack of comparative studies with rodents and humans to establish the zebrafish as a predictive translational model. Here we present a detailed phenotype evaluation of zebrafish larvae, measuring 300-3000 variables and analyzing them using multivariate analysis to identify the most important ones for further evaluations. The dopamine agonist apomorphine has previously been shown to have a complex U-shaped dose-response relationship in the variable distance traveled. In this study, we focused on breaking down distance traveled into more detailed behavioral phenotypes for both zebrafish and rats and identified in the multivariate analysis low and high dose phenotypes with characteristic behavioral features. Further analysis of single parameters also identified an increased activity at the lowest concentration indicative of a U-shaped dose-response. Apomorphine increased the distance of each swim movement (bout) at both high and low doses, but the underlying behavior of this increase is different; at high dose, both bout duration and frequency increased whereas bout max speed was higher at low dose. Larvae also displayed differences in place preference. The low dose phenotype spent more time in the center, indicative of an anxiolytic effect, while the high-dose phenotype had a wall preference. These dose-dependent effects corroborated findings in a parallel rat study and previous observations in humans. The translational value of pharmacological zebrafish studies was further evaluated by comparing the amino acid sequence of the dopamine receptors (D1-D4), between zebrafish, rats and humans. Humans and zebrafish share 100% of the amino acids in the binding site for D1 and D3 whereas D2 and D4 receptors share 85-95%. Molecular modeling of dopamine D2 and D4 receptors indicated that nonconserved amino acids have limited influence on important ligand-receptor interactions