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ENCIT 2020
18th Brazilian Congress of Thermal Sciences and Engineering
DESIGN OF EXPERIMENTS APPLIED ON A 360 MW POWER PLANT IN OPERATION: SURROGATE MODELING APPROACH
Submission Author:
Lara Werncke Vieira , RS
Co-Authors:
Lara Werncke Vieira, Augusto Delavald Marques, Jéssica Duarte, Paulo Smith Schneider
Presenter: Lara Werncke Vieira
doi://10.26678/ABCM.ENCIT2020.CIT20-0544
Abstract
Steam generators are complex equipment and a proper operation depends on the identification of their most relevant parameters. The present paper presents an approach to select and rank the operational parameters of a subcritical steam generator of an actual 360 MW Brazilian power plant fueled by Colombian coal. The steam generator and its three coal mills are gathered on a single system whose controllable parameters are identified. Statistical tools like Design of Experiments (DoE) and Response Surface Methodology (RSM) are used to identify the model main controllable parameters and interactions to then rank them by order of importance. The surrogate model based on the commercial software is built to simulate the system efficiency with seven controllable input parameters: primary air flow, pulverized coal outlet temperature, speed of the dynamic classifier, stoichiometry, excess O2, secondary and primary air crossover duct pressure, ranked by descendent significance. The maximum relative deviation of that surrogate model compared to the software simulation is 0.0172. The operator's attention must be kept on the most influential parameters, respecting their rank and initializing the alterations for a new condition always for the controllable parameters with a high effect on the steam generator efficiency. Finally, controllable parameters must attain the best operating ranges propose. The recommended operational ranges and order of operation by significance allows a precision action in order to achieve a new, safe, stable, and more efficient condition.
Keywords
Box-Behnken Design, coal-fired power plant, Design of Experiment (DOE), Response Surface Methodology (RSM), Surrogate model
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