Abstract
The current flexibility of the energy market requires operating steam turbines that have challenging operation requirements such as variable steam conditions and higher number of startups. This article proposes an advanced control system based on the Nonlinear Model Predictive Control (NMPC) technique, which allows to speed up the start-up of steam turbines and increase the energy produced while maintaining rotor stress as a constraint variable. A soft sensor for the online calculation of rotor stress is presented together with the steam turbine control logic. Then, we present how the computational cost of the controller was contained by reducing the order of the formulation of the optimization problem, adjusting the scheduling of the optimizer routine, and tuning the parameters of the controller itself. The performance of the control system has been compared with respect to the PI Controller architecture fed by the soft sensor results and with standard pre-calculated curves. The control architecture was evaluated in a simulation exploiting actual data from a Concentrated Solar Power Plant. The NMPC technique shows an increase in performance, with respect to the custom PI control application, and encouraging results.
Highlights
Extensive simulation studies have been performed, through which the performance of the proposed Nonlinear Model Predictive Control (NMPC) approach has been compared to the selected benchmark based on the PI Controller as well as to a second benchmark based on the standard procedures for power startup, based on pre-calculated load curves
In order to assess the performances of the PI based controller, it is important to verify the sensitivity of this kind of controller to a possible mistuning of its gain parameters
The NMPC approach includes a detailed thermodynamical model of the machine that allows to identify with a great accuracy the thermal behavior of its rotor, in particular focusing on the equivalent stress
Summary
In the current energy market, renewable sources and flexible power plants are increasingly exploited in order to meet the energy demand of increasingly connected cities [1], where smart grids are going to become a consolidated reality [2,3] In this context, the design of new power plants must aim at increasing the level of flexibility, with a resulting multitude of challenges in terms of degradation of the components, restrictions related to the environmental impact, and required level of workforce specialization. The design of new power plants must aim at increasing the level of flexibility, with a resulting multitude of challenges in terms of degradation of the components, restrictions related to the environmental impact, and required level of workforce specialization For these reasons, the design of Steam Turbines (STs) nowadays must take into account frequent discontinuous operations. Last but not least is the effectiveness of the control action on processes that work in almost stable operating points, in which the performances achievable through a PID controller are usually quite satisfactory
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