-In this paper, a novel and robust Power System Stabilizer (PSS) is proposed as an effective approach to improve stability in electric power systems. The dynamic performance of proposed PSS has been thoroughly compared with Conventional PSS (CPSS). Both the Real Coded Genetic Algorithm (RCGA) and Particle Swarm Optimization (PSO) techniques are applied to optimum tune the parameter of both the proposed PSS and CPSS in order to damp-out power system oscillations. Due to the high sufficiency of both the RCGA and PSO techniques to solve the very non-linear objective, they have been employed for solution of the optimization problem. In order to verify the dynamic performance of these devices, different conditions of disturbance are taken into account in Single Machine Infinite Bus (SMIB) power system. Moreover, to ensure the robustness of proposed PSS in damping the power system multi-mode oscillations, a Multi Machine (MM) power system under various disturbances are considered as a test system. The results of nonlinear simulation strongly suggest that the proposed PSS significantly enhances the power system dynamic stability in both of the SMIB and MM power system as compared to CPSS.
In this paper, Power System Stabilizer (PSS) and Automatic Voltage Regulator (AVR) are coordinated to improve the transient stability of generator in power system. Coordinated design problem of AVR and PSS is formulated as an optimization problem. Particle Swarm Optimization (PSO) technique is an advanced robust search method by the swarming or cooperative behavior of biological populations mechanism. The performance of PSO has been certified in solution of highly non-linear objectives. Thus, PSO technique has been employed to optimize the parameters of PSS and AVR in order to reduce the power system oscillations during the load changing conditions in single-machine, infinite-bus power system. The results of nonlinear simulation suggest that, by coordinated design of AVR and PSS based on PSO technique power system oscillations are exceptionally damped. Correspondingly, it's shown that power system stability is superiorly enhanced than the uncoordinated designed of the PSS and the AVR controllers.
Summary
One of the main challenges in front of the inventors and researchers to compensate the power quality problems is the existence of an efficient and reliable electric energy source for dynamic voltage restorer (DVR). Recent advances in the technologies of lithium‐battery (LB) and super‐capacitor (SC) have made them possible to be used as hybrid energy storage system (HESS) for DC‐power supply of DVR. But then, a robust and efficient controller must be essentially designed to compensate the intricate correlation between system components, unknown nonlinearities, parameter uncertainties related to the HESS. Hence, fractional‐order super‐twisting sliding mode control (FOSTSMC) is proposed for LB/SC‐HESS to smoothly and accurately smoothly track the current reference and control the DC‐link voltage of the asymmetric half‐cascaded multilevel inverter of DVR during different compensation conditions. As the primary controller, FOSTSMC has compensated the unknown nonlinear parts and parameter uncertainties related to LB/SC‐HESS through the real‐time disturbance estimation using sliding mode state and disturbance observer (SMSDO). Both the battery current and DC‐link voltage due to the physical measurability are chosen to design the control scheme based on the proposed FOSTSMC. The proposed controller has been compared with the proportional integral derivative and the sliding mode control under different probable scenarios to evaluate and validate its observability and controllability. To better present the effects of FOSTSMC, AHCMLI, and HESS‐based DVR, they have been quantified as follows:
Three real‐time stability benchmarks that is, overshoot, undershoot and settling time are respectively attained for FOSTSMC: 0.6, 0.4, and 0.03; for sliding mode control: 1.1, 0.7 and 0.019; for proportional integral derivative: 0.9, 2, and 0.117. That is to say, FOSTSMC can smoothly and accurately track the current reference and control the DC‐link voltage during different compensation conditions as compared with other controllers.
Asymmetric half‐cascaded multilevel inverter can provide 33 steps with consideration of 12 unidirectional switches, whereas binary, trinary, and other multilevel structures can provide less than 27 steps with consideration of 12 switches.
The quasi‐AC voltage synthesizer‐based DVR can completely and accurately compensate the voltage sag and swell with THD of 2.12 and 2.35, respectively. The THD of mal‐compensation voltage sag and swell using the conventional DVR are respectively 11.57 and 13.86.
In this paper, the concept of smart materials has been engaged in order to control and abate the vibrations of non-linear beams. In the meantime, flexural vibration of viscoelastic has been taken into account aimed at reinforcing the carbon nanotube beams. This theory has applied the viscoelastic model to draw out the classical viscoelastic Kelvin–Voigt model. Likewise, the Hamilton’s principle has been employed to derive the non-linear differential equations of beam’s motion as for the piezoelectric patches and also the multiple scales method has been engaged in order to solve the non-linear equation of system motion. A fuzzy controller has been desirably arranged in the piezoelectric actuator/sensor loop to reduce the forced vibrations for any arbitrary stimulation. Due to majestic efficiency of the Bees Algorithm (BA) in the solution of many different engineering problems, it has been engaged for this work. To ensure and confirm the robustness of the proposed approach, three different conditions of forced stimulation have been taken into account for the studied system. In all, the non-linear simulation results unveil the robust performance of the proposed approach based on the BA technique in the damping of the system’s vibrations.
The doubly fed induction generator (DFIG)-based wind turbine as a nonlinear, compound, and multivariable time-varying system encompasses several uncertainties especially unfamiliar disturbances and unmodeled dynamics. The design of a high-performance and reliable controller for this system is regarded as a complex task. In this paper, an effective and roust fractional-order sliding mode controller (FOSMC) has been designed to accurately regulate the active and reactive power of DFIG. FOSMC has overcome the system uncertainties and abated the chattering amplitude. Since tuning the FOSMC is a challenging assignment, the application of a multi-objective optimization algorithm can efficiently and precisely solve the design problem. In this regard, non-dominated sorting multi-objective gray wolf optimizer (MOGWO) is taken into account to optimally adjust the FOSMC. In a word, the simulation results have definitively validated robustness of MOGWO-based FOSMC in order to accurately track DFIG's active and reactive power.
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