Author ORCID Identifier

https://orcid.org/0000-0001-9482-4817

Semester

Spring

Date of Graduation

2023

Document Type

Dissertation

Degree Type

PhD

College

Statler College of Engineering and Mineral Resources

Department

Chemical and Biomedical Engineering

Committee Chair

Debangsu Bhattacharyya

Committee Member

Fernando V. Lima

Committee Member

Stephen E. Zitney

Committee Member

Anurag Srivastava

Committee Member

Benjamin Omell

Abstract

With the introduction of a larger portion of renewable sources of power coming onto the U.S. power grid in recent decades, the operational strategy of coal-fired power plants has changed significantly to focus more on flexibility in response to the changing energy market. This has naturally led to different operational challenges. Many of these challenges are focused on the boilers within these plants, as they are producing more emissions and experiencing increased damage during load-following, which in turn leads to increased costs from penalties for not achieving emission standards or maintenance costs as boilers accumulate damage from the cycling behavior. This work aims to address these two issues.

For the study of the response of emission control units while cycling, a transient model of the selective catalytic reduction (SCR) unit was developed. The multi-scale model is isothermal and distributed along the length of the reactor to allow for determination of the axial reactor profile. The SCR model contains kinetic reaction rates for the reduction of nitric oxide as well as the oxidation of ammonia and considers internal and external mass transfer limitations. The mass transfer limitations are of particular importance as the SCR unit exhibits significant time delay due to the adsorption of ammonia onto the catalyst surface, which blunts the immediate impact of rapid changes in load but makes control of the SCR more difficult. The combination of kinetic and mass transfer considerations is the main contribution of this model. The SCR unit model was also validated against industrial data to ensure the dynamics are properly accounted for, which is another significant contribution of the SCR unit work.

The boiler itself is, though, is the main focus of the work presented here. A high-fidelity, steady-state model of a supercritical pulverized coal-fired (SCPC) boiler was developed; the model is based on first principles, is spatially distributed, and uses a rigorous property model to adequately account for the properties of supercritical steam, which can be highly nonlinear. To aid in the simulation of boilers of various configurations, the model has been developed modularly, with sub-models for common boiler components. As part of this work, the model was used to perform data reconciliation and parameter estimation to validate the model against industrial data.

The steady-state boiler model was then expanded into a transient model with full consideration of all the necessary information to monitor stresses at any location within the boiler. This includes the calculation of the transient thermal profiles of the tubes for all boiler components, which are often not measured – or are unmeasurable – in industrial settings due to the harsh boiler operating conditions. In addition, the model can capture the transition between two-phase and one-phase flow, as SCPC boilers frequently transition through the critical point during load-following operation. The transient model was also used for data reconciliation and parameter estimation and was validated against industrial data.

As part of the data reconciliation for the transient boiler model, a data reconciliation approach was be developed to reduce the size of large-scale reconciliation problems. The method developed focused on the implementation of bias terms for the reconciled variables, which can be estimated in place of the reconciled variables themselves. Combined with an approach to define a functional approximation of the reconciliation problem that can be more simply optimized to generate initial points for the bias terms, this approach can significantly improve the tractability of many such large-scale problems.

To address the issue of boiler damage during load-following, a boiler health model was developed based on the calculation of stresses at locations of interest within the boiler, such as the boiler tubes or steam headers. Using the health model, damage indicators were calculated, leading to a quantification of the damage incurred during cycling operation. This health model was leveraged for a full-boiler health monitoring framework to assist in online decision-making during load-following. The primary contribution was the development of prognostic capabilities that can predict the remaining useful life (RUL) of key locations under uncertainty in both the material properties and operational trajectory of the SCPC boiler. Such capabilities enable condition-based maintenance, thus improving boiler reliability and availability. Case studies are presented for various operational scenarios to demonstrate these capabilities.

Embargo Reason

Publication Pending

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