In this paper, a model predictive controller based on a generator model for prediction purposes is proposed to replace a standard generator controller with a stabilizer of a power system. Such a local controller utilizes an input-output model of the system taking into consideration not only a generator voltage $U_g$ but also an additional, auxiliary signal (e.g., $\alpha$, $P_g$, or ${\omega }_g$). This additional piece of information allows for taking oscillations into account that occur in the system and minimizing their impact on the overall system performance. Parameters of models used by the controller are obtained on the basis of the introduced black-box models both for a turbine and a synchronous generator, parameters of which are estimated in an on line fashion using a RLS method. The aim of this paper is to compare the behavior of the classical generator control system with a power system stabilizer and a model predictive control with an additional feedback signal. The novelty of the paper is related to the use of the predictive controller instead of the classical controller/stabilizer system and its possibility of stabilizing the power system. Contrary to the solutions found in the literature, which are commonly-based on a fuzzy logic approach, the authors propose the use of an adaptive model predictive controller, which takes advantage of the knowledge concerning the plant in the form of a model and adapts itself to the operating point of the system using the model parameters estimation mechanism. Moreover, the adaptive predictive controller, unlike other solutions, automatically adjusts signal levels to changes in the plant. The proposed solution is able to calculate the best control signal regardless of whether these changes of the plant are caused by a change in the operating point, or resulting from operation, e.g., wear of mechanical parts.

The paper discusses the problem of cooperation between multiple model predictive control (MPC) systems. This approach aims at improving the control quality in electrical energy generation and forms the next step in a series of publications by the authors focusing on the optimization and control of electric power systems. Cooperation and cooperative object concepts in relation to a multi MPC system are defined and a cooperative control solution for a nuclear power plant’s turbine generator set is proposed. The aim of enabling information exchange between the controllers is to improve the performance of power generation. Presented and discussed simulation tests include various variants of information exchange between the turbine and synchronous generator MPC controllers of the nuclear power plant.

This paper discusses the proper selection and interpretation of aggregated control performance indices values mirroring the quality of electrical energy generation by a turbine-generator set cooperating with a power system. Typically, a set of basic/classical and individual indices is used in energy engineering to ensure the mirroring feature and is related to voltage, frequency and active or reactive power deviations from their nominal values desired in the power system. In this paper, aggregated indices based on the sum of weighted integral indices are proposed, verified and built based on the well-known indices originating from control theory. These include an integral of the squared error (ISE) and an integral of the squared error multiplied by time (ITSE), applicable whenever an in-depth analysis and evaluation of various control strategies of the generation system is to be performed. In the reported research, the computer simulation tests verified their effectiveness in assessing the generated electricity on the example of a turbine-generator set controlled using a predictive control technology as well as applicability, proven by numerous simulation results to take various and different in nature requirements into account efficiently, in the form of a single aggregated index.

This paper discusses the issue of optimizing the communication between the components of a cooperating control system formed by a pair of MPC controllers of a nuclear power plant turbine set using online recursive least squares identification. It is proposed to use event-triggered communication, i.e., sending information only at selected time instants, as opposed to the standard approach where communication is triggered by time (time-triggered approach). The aim of this paper is to propose a change in the method of information exchange in the case of asynchronous communication between control system components and to prove its suitability for the selected application. Resignation from continuous communication in favor of sending information only at selected moments allows the load on the communication network to be reduced by approximately 90% while maintaining the quality of control.