Adaptive Event-Triggered Model Predictive Load Frequency Control for Power Systems

Adaptive event‐triggering mechanism‐based N‐step predictive load frequency control for power systems with cyber attack

“…It illustrates that the proposed control method can keep the system frequency steady in the standard range in spite of various conditions, which also satisfies the goal of this article. The results of frequency deviation shown in Figure 5 show that, in the face of continuous disturbance and destruction of deception attack, the method proposed in this article has a faster response than that in Reference 40, and still ensures that the frequency is maintained within a certain range. Figure 9 represents the control input.…”

“…First, N‐step strategy under different N $$$ \left(\mathrm{N}=2,4,6\right) $$$ are carried out to illustrate the performance affected by the change of switch horizon. Second, in order to demonstrate the superiority of the N‐step predictive LFC for network‐based power systems with deception attack proposed in this article, a comparison is made between this article and the observer‐based MPC method in Reference 40. In Reference 40, an AET observer‐based output feedback MPC control method is proposed to study the load frequency control problem of hybrid power systems including thermal power and photovoltaic power, while this article addresses an AET N‐step dynamic output feedback MPC strategy which shows improved control performance since more degrees of freedom has been introduced.…”

“…Figure 3 depicts the results of two AET parameters $$$ {\lambda}_k^1 $$$ and $$$ {\lambda}_k^2 $$$, which is dynamically adjusted and represents two smaller values compared to the initial ones. Figure 4 plots the threshold of $$$ {\lambda}_k $$$ under observer‐based OFMPC in Reference 40. State responses in different situations are shown in Figures 5–8.…”

Type‐2 fuzzy‐based adaptively predictive controlled variable frequency transformer coordinated to SMES for improved load frequency control

“…An adaptive-network-based fuzzy-inference system (ANFIS) and multiple models are used by the authors of [20] to offer an adaptive generalised predictive control approach for non-linear discrete temporal systems with uncertain zero dynamics. For the purpose of load frequency regulation, authors in [21] have introduced an adaptive event triggered model predictive controller. The simulations reveal that the suggested control technique outperforms the conventional model predictive controller.…”

“…In [20,30], a fuzzy-based governor limiter and APC were both used to regulate an automated model of a power system. In [21,31], authors have suggested the use of an ANFIS controller for LFC of an interrelated power system. Type-1 fuzzy-based APC has been presented by the authors of [32] for the LFC.…”