Optimal Process Operations in Fast-Changing Electricity Markets: Framework for Scheduling with Low-Order Dynamic Models and an Air Separation Application

Design and Multiobjective Dynamic Optimization of Superheaters for Load-Following Operation in Pulverized Coal Power Plants

Pulverized coal power plants are increasingly participating in aggressive load-following markets, therefore necessitating the design and optimization of primary superheaters for flexible operations. These superheaters play a critical role in maintaining the final steam temperature of the steam turbine, but their high operating temperatures and pressures make them prone to failure. This study focuses on the optimal design of future-generation primary superheaters for a fast load-following operation. To achieve this, a detailed first-principles model of a primary superheater is developed along with submodels for stress and fatigue damage. Two single-objective optimization problems are solved: one for minimizing metal mass as a measure of capital cost and another for minimizing pressure drop on the steam side as a measure of operating cost. Since these objective functions conflict, a multiobjective optimization problem is executed using a weighted metric methodology. Results from these optimization studies show that the base case design can violate stress constraints during the aggressive load-following operation. However, by optimizing the design variables, it is possible to not only satisfy tight stress constraints but also achieve the desired number of allowable cycles and adhere to the steam outlet temperature constraint. In addition, the optimized design reduces either the metal mass or the steam-side pressure drop compared to that of the base case design. Importantly, this approach is not limited to primary superheaters alone but can also be applied to similar high-temperature heat exchangers in other applications.

Process Control and Energy Efficiency

We review the impact of control systems and strategies on the energy efficiency of chemical processes. We show that, in many ways, good control performance is a necessary but not sufficient condition for energy efficiency. The direct effect of process control on energy efficiency is manyfold: Reducing output variability allows for operating chemical plants closer to their limits, where the energy/economic optima typically lie. Further, good control enables novel, transient operating strategies, such as conversion smoothing and demand response. Indirectly, control systems are key to the implementation and operation of more energy-efficient plant designs, as dictated by the process integration and intensification paradigms. These conclusions are supported with references to numerous examples from the literature.