DC microgrid fault‐tolerant control using state‐dependent Riccati equation techniques

Abstract

An attempt is made to design a fault-tolerant control system using a nonlinear technique, called the state-dependent Riccati equation (SDRE) method. The proposed mechanism consists of a master controller, an observer-based fault detection and isolation system, and three emergency controllers, designed using the SDRE methods. The master controller, as a suboptimal nonlinear regulator, is designed to return DC microgrid (MG) to its desired equilibrium point in normal operation condition. On the other hand, an SDRE observer is designed to establish a unified framework for fault detection and isolation in the DC MG. Indeed, in the case of unexpected fault occurrence, the proposed mechanism can isolate the faulty DG, and then, the emergency controllers are triggered immediately to stabilize the MG. Simulation results indicate that the proposed method is so useful to achieve the control objectives and online protection of the considered MG.

Accurate voltage regulation for a DC microgrid using nonlinear state feedback controller

“…• Partial state feedback design capability • Reducing the requirement for additional sensors • Cost-effective To be more precise, partial state feedback capability is a merit of the proposed nonlinear state feedback controller over the nonlinear controller presented in [29]. Notably, this point has not been discussed in [32].…”

“…The research papers mentioned earlier explored different versions of the droop method in their studies. However, alternative solutions utilizing advanced/nonlinear control techniques, including passivity-based design, feedback linearization, Lyapunov method, robust control, optimal control methods (like state-dependent Riccati equation [SDRE]) and linear parametervarying (LPV) systems and so on, have been investigated to meet primary control requirements within hierarchical control structures and address various aspects in DC MGs [22][23][24][25][26][27][28][29][30][31].…”

Integrated nonlinear suboptimal control‐and‐estimator based on the state‐dependent differential Riccati equation approach

“…Subsequently, to implement the SDDRE estimator, all dynamic parameters and state variables should be obtained firstly, as a function of estimated parameters being used in estimator dynamic equations. State estimation vector is included of two parts: the angular position and velocity are determined by the measurement system and estimated by the proposed estimator that it is presented by Equation (23).…”

“…Nasiri et al 22 proposed an observer‐based robust (OBR) controller that was applied to two highly nonlinear, coupled and large robotic systems. Batmani et al 23 proposed the SDRE observer as a unified framework for fault detection and isolation in the DC microgrid.…”

Intelligent aided decision-making method for power grid outage maintenance plan based on machine learning

“…It is necessary to arrange and develop uninterrupted maintenance plans through reasonable and effective means to improve maintenance quality and efficiency, reduce power outages and losses, and ensure the efficient and safe operation of the power grid [2]. The development of uninterrupted maintenance plans for distribution networks needs to be carried out without affecting user electricity consumption, arranged within a reasonable time period, and transferred as much as possible to ensure the safety of the power grid [3]. Therefore, based on machine learning, this article designs an effective intelligent decision-making method for power grid outage maintenance planning to improve the stability of the power system.…”