In this study, a multi‐objective predictive control strategy is presented for the stability improvement of a power system in the presence of wind farms and STATCOM. The main contribution of this study is in the multi‐objective consideration for controlling the active and reactive powers of the rotor‐side converter in each of the induction generators, controlling the voltage of the synchronous generators’ excitation system, and designing the damping controller of STATCOM using the predictive strategy. To reduce the computational burden, and to accurately choose the input paths into the predictive control, the Laguerre functions are used. Also, for reducing the sampling time in the selection of large prediction horizons, the exponential data weighting has been employed. The simulation results were evaluated using MATLAB software in the field of time and frequency under different scenarios. Moreover, the obtained results of each domain are compared using the two techniques of the predictive strategy, i.e. the classic model, Laguerre functions, and also the conventional proportional integral controller. The comparison of these three methods reveals that the functional predictive control outfits the two other controllers in damping of the oscillations.

The present article aims to improve the small signal stability in a large-scale network using model predictive control (MPC). The predictive strategy is based on the Laguerre function so as to reduce computational time in MPC and increase precise detection of control signals. This strategy is implemented in such a way to control the active and reactive power on rotor-side converter (RSC) and increase RSC yield in the presence of uncertainties through application of appropriate switching to inverter. Therefore, static synchronous compensator is used in a way that the reactive power is compensated and by designing a damping controller the interarea oscillations will be reduced in New England large-scale system. The simulation results were evaluated using MATLAB software in the field of time and frequency under different scenarios. Moreover, the proposed method was compared with conventional MPC and proportional-integral controller while its superiority to stabilize and reduce the computational time is clearly shown.

The main objective of this study is to increase the power system oscillation damping in the presence of wind farms using flexible alternating current transmission systems (FACTS) devices and predictive control. The desired design is conducted to coordinate static synchronous compensator–static synchronous series compensator and rotor side converter in doubly‐fed induction generator (DFIG). This design is done to compensate for the DFIG reactive power and increase power system oscillation damping in the presence of uncertainties in the wind turbine. The method proposed for coordinated design was based on the network predictive control (NPC) so that it could improve damping, and compensate for the time delays in sending wide area signals. In fact, NPC is based on generalised predictive control (GPC) which has the ability to compensate for time delays using model identification method. Using MATLAB software, the simulation results were conducted on a 16‐machine and 69‐bus power system under different scenarios; and the ability of NPC is well proven compared with GPC and the classic method of wide area controller.

This paper aims to present an optimization method for the best bus selection (BBS) in the large‐scale power systems in order to send the input signals to the damping controllers. In this regard, a submodular function is first defined to calculate the distance between the unstable vectors of the system and the controllability Gramian leading to find a set of buses for installation of the damping controllers. Based on the results obtained from the BBS approach, the number of candidate buses will be increased to deal with the inter‐area oscillations by introducing an event‐triggered based auxiliary scheme. According to the candidate buses and the power system operating condition, the most critical buses of the candidate set is allowed to participate as the input signals of damping controllers to reduce the inter‐area oscillations. The proposed algorithm is implemented on an interconnected large power system in the presence of wind and solar farms. These renewable energy resources are connected to the power system through the multi‐terminal DC network, so that their power products can be damped and injected into the power grid by designing the damping controllers. The simulations have been analysed using MATLAB software under different scenarios.

The main aim of this paper is to improve dynamic performance of a multi‐terminal DC (MTDC) grid in a wind‐integrated AC power system through DC voltage control. The proposed approach is based on design of robust H _∞ controller and loop shaping along with mutual quality decomposition method (MQDM). For extracting transfer function of the plant, model of Master‐Slave control system is converted to standard feedback control system. Then, based on the obtained difference between singular‐value curves of the main open‐loop system and the proposed method, the weighting functions of robust H _∞ controller are selected. In the next step, by using the MQDM technique, the transfer function ofthe system in state‐space form is evaluated to extract gain of the robust controller. For practicality of the conducted approach, singular‐value order reduction Hankel algorithm along with frequency response analysis have been used for designing the gain of the robust controller. The developed method has been implemented on the MTDC converter in the wind farm side to control the voltage of DC grid. The simulations are accomplished in MATLAB, where by considering different uncertainties in the DC grid, wind unit, and the AC grid, robustness of the proposed approach has been clearly demonstrated.