(492e) Dynamic Optimization of the Operational Trajectory of a Supercritical Pulverized Coal-Fired Boiler Under Load-Following with Consideration of Boiler Health

Despite the increasing penetration of renewable sources of energy onto the U.S. power grid, coal-fired power plants remain a major source of electric power in the United States. Thus, the flexible operation of these coal-based power plants, such as supercritical pulverized coal-fired (SCPC) plants, in response to the frequent disruptions caused by intermittent renewables is an important challenge facing the power generation industry. In particular, the off-design operational paths these SCPC plants follow as they cycle their load can have considerable impact on long-term boiler health, which increases the likelihood of boiler failures and unplanned shutdowns, thereby increasing operations and maintenance costs.

SCPC power plants operate at higher temperatures and pressures than subcritical pulverized coal power plants, therefore the metal tubes in SCPC boilers are thicker and subject to more creep and fatigue damage. Cumulative damage depends on the current state of the boiler tubes as well as the temperature of the tubes and rate of change of their through-wall temperature profiles. However, the outer (gas-side) and inner (steam-side) wall temperatures are rarely measured in SCPC boilers due to the severity of the operating conditions, particularly at the inner tube wall, and the through-wall profiles are unmeasurable. In view of these challenges, a first-principles dynamic model of the SCPC boiler can be a useful tool to predict damage during cycling operation but needs to take into account the tube conditions, including external fouling present due to ash deposition or slagging and internal oxide scaling due to reactions between the tube metal and steam. In addition, the model needs to take into account the thermomechanical stress profiles of the entire boiler to ascertain the optimal load transition during load-following that minimizes the damage done to the boiler while still maintaining a satisfactory heat rate (efficiency).

For simulating SCPC boilers, it is common for first-principles process models to employ a lumped-parameter (0D) approach to increase the computational efficiency[1], [2]. However, this type of approach does not fully capture the local dynamics within the boiler as it fails to account for the high nonlinearities in the steam properties, especially near the critical point, which can greatly influence the stresses experienced along the boiler. Some computational fluid dynamics (CFD) models are available that can adequately capture the variation in the steam properties[3] and even account for the impact of ash deposition or scaling on the tubes, but the dynamics of through-wall temperature profiles are often neglected[4], [5]. The distributed-parameter (2-3D) CFD models are computationally very expensive and therefore cannot be used for online optimization for estimating the optimal operating conditions during load-following. In contrast, lumped-parameter process models can be solved within desired time but often lack the resolution necessary to adequately estimate the stresses experienced by the boiler [6–8]. To the best of our knowledge, there is not a distributed-parameter process model of all components of an SCPC boiler that has been used to investigate the stress profile of the tubes during load-following considering fouling on both the inside and outsides of the tubes.

In this work, a detailed distributed-parameter (1D) dynamic SCPC boiler model is developed based on fundamental mass and energy balances using rigorous properties model for steam [9]. The model can account for the drastic property changes that can occur on the steam side as the boiler transitions from supercritical to subcritical operation and vice versa as the load drops and increases, respectively. With full consideration of the tube thermal profiles and models to account for fouling build-up on the outsides of the tubes, such as ash deposition and slagging, as well as the insides of the tubes, such as oxide scaling, the model is able to simulate the stress profile of the entire boiler under various conditions during load transitions.

Dynamic optimization of the operating conditions using the detailed distributed-parameter boiler model with the thermomechanical stress model is challenging to solve within the desired time. First-order updates for the decision variables can be rapidly computed starting with the nominal condition. However, external fouling and internal scaling are highly uncertain, localized, and time-varying, thus the first-order updates are suboptimal. Here, we propose a temporal and spatial scale decomposition strategy for optimization [10] along with a sensitivity-based approach that can greatly reduce the size and complexity of the original optimization problem. The dynamic optimization algorithm is evaluated by considering various load-following scenarios with various extents of fouling uncertainty to determine the operational trajectory of the boiler that maintains an adequate heat rate while minimizing the damage done to the boiler.

References

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