Accurate on-line plant and equipment performance evaluation is becoming critical in the power generation industry as operators seek to optimize their plants, particularly in competitive power markets. The analysis accuracy of an on-line performance monitoring system is directly dependent on the quality of the input data and usually suffers because installed plant sensors are not high-precision instruments. The inherent measurement uncertainties can be overcome by using a readily available heat balance program in combination with a least square solver. This data reconciliation system will provide the performance evaluation system with data that better reflects the plant’s current operating point, thus improving the performance evaluation system’s output and allowing for better plant optimization. Additionally, the reconciliation system can identify broken, biased or highly noisy sensors. These improvements can be obtained without installing additional precision sensors or putting unreasonable efforts into sensor calibration.
Summary. PARSIM, a one-dimensional simulation tool for dynamic reactions in porous particles is presented. Several features are included in the package (DustyGas-Model, sorption effects, evaporation, condensation, diffusion through a product layer, pore models, ... ). As an example the drying process of a solid wood particle is simulated and results are presented. The discretization of the space derivatives is achieved by the method of Orhogonal Colloction on Finite Elements which proved to give higher accuracy compared to the method of Finite Differences which is optionally provide by P ARSIM. LIMEX is used as integrator in time direction. Even complex reaction systems (pyrolysis, desulphurization, ... ) can be simulated easily by P ARSIM.
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