Designing an adaptive type-2 fuzzy logic system load frequency control for a nonlinear time-delay power system

In this paper, a combination of type-2 fuzzy logic system (T2FLS) and a conventional feedback controller (CFC) has been designed for the load frequency control (LFC) of a nonlinear time-delay power system. In this approach, the T2FLS controller which is designed to overcome the uncertainties and nonlinearites of the controlled system is in the feedforward path and the CFC which plays an important role in the transient state is in the feedback path. A Lyapunov–Krasovskii functional has been used to ensure the stability of the system and the parameter adjustment laws for the T2FLS controller are derived using this functional. In this training method, the effect of delay has been considered in tuning the T2FLS controller parameters and thus the performance of the system has been improved. The T2FLS controller is used due to its ability to effectively model uncertainties, which may exist in the rules and data measured by the sensors. To illustrate the effectiveness of the proposed method, a two-area nonlinear time-delay power system has been used and compared with the controller that uses the gradient-descend (GD) algorithm to tune the T2FLS controller parameters.     

Application of type-2 fuzzy logic system for load frequency control using feedback error learning approaches

In this paper, the type-2 fuzzy logic system (T2FLS) controller using the feedback error learning (FEL) strategy has been proposed for load frequency control (LFC) in the restructure power system. The original FEL strategy consists of an intelligent feedforward controller (INFC) (i.e. artificial neural network (ANN)) and the conventional feedback controller (CFC). The CFC acting as a general feedback controller to guarantee the stability of the system plays a crucial role in the transient state. The INFC is adopted in forward path to take over the control problem in the steady state. In this work, to improve the performance of the FEL strategy, the T2FLS is adopted instead of ANN in the INFC part due to its ability to model uncertainties, which may exist in the rules and measured data of sensors more effectively. The proposed FEL controller has been compared with a type-1 fuzzy logic system (T1FLS) – based FEL controller and the proportional, integral and derivative (PID) controller to highlight the effectiveness of the proposed method.     

Secure distributed optimal frequency regulation of power grid with time‐varying voltages under cyberattack

The distributed optimal frequency regulation of power grid containing plenty of distributed renewable energy resources is highly dependent on the communication network. However, the utilization of a communication network makes the power grid vulnerable to cyberattacks, which could deteriorate the control performance and even cause the failure of a control task. To address this problem, this paper investigates the secure distributed optimal frequency regulation of power grid under cyberattack. The stealthy deceptive cyberattack model is constructed, and its perniciousness on optimal frequency regulation is analyzed. A novel type of secure distributed optimal frequency regulation is developed by introducing a secure‐based communication network to improve the resilience against cyberattack. It is proved theoretically that the secure regulation can restore the frequency deviation of each area to zero and minimize the total generation cost to retain the economic efficiency even under cyberattack. Simulation result shows the effectiveness of the proposed method.