Optimal design of interconnected multimachine power system with power system stabilizers (PSSs) enduring critical conditions is a challenging assignment due to several nonlinear dynamic device and components associated to the system. In this research, the effective application and performance assessment of genetic algorithm (GA), particle swarm optimization (PSO) and a new metaheuristic-based farmland fertility algorithm (FFA) search algorithm for

In this paper, a novel metaheuristic optimization algorithm inspired by General Relativity Theory (GRT) is presented. In this method that we named General Relativity Search Algorithm (GRSA), a population of particles is considered in a space free from all external non-gravitational fields and propel toward a position with least action. Based on GRT, particles have conserved masses and move along geodesic trajectories in a curved space. Step length and step direction for updating the particles are separately computed using particles velocity and geodesics, respectively. Velocity of particles is obtained by their energy–momentums. According to physical action principle, a population of particles goes to the position with minimum action. By inspiring this physical principle, GRSA will lead variables of an optimization problem move toward the optimal point. Performance of the proposed optimization algorithm is investigated by using several standard test functions and optimal Power System Stabilizers (PSSs) design in a multi-machine power system as a real-world application. Numerical simulations results demonstrate the efficiency, robustness and convergence speed of GRSA in solving various problems.

An asymptotically stable controller for solid-state transformers (SSTs) based on Lyapunov direct stability (LDS) method is presented in this study. The proposed controller has four control objectives for the SST application, which includes unity power factor at medium-voltage AC (VAC) side of the SST, constant DC-link voltage and constant output voltage magnitude and frequency at low-VAC side of the SST. To fulfil the above-mentioned objectives four control laws are derived from the Lyapunov function, directly. The proposed LDS-based controller is simulated using MATLAB/Simulink software. The obtained results indicate the fast and superior dynamic characteristics of the proposed controller. The LDS-based controller is comprehensive and can be adopted for the SST applications.

Summary Simple implementation, robust response, good dynamic, and steady‐state performances are empowering direct power control (DPC) as an accepted control method in power electronic converters. One of the key converters are active front‐end rectifiers that are used in many applications. In this paper, type‐2 neuro‐fuzzy controller based DPC (T2NFC‐DPC) is designed for active front‐end rectifier. T2NFC uses an upper and lower bounds for membership functions and provides a better tool for defining uncertain systems and also neural networks help to improve the speed of convergence in tracking the reference signals. In the proposed method, error and change of error are used to train T2NFC‐DPC. The effectiveness of the proposed method is validated using experimental model. An experimental setup is developed using dSPACE 1104 control board in order to show the applicability of the proposed method. Experimental results show that T2NFC‐DPC outperforms against conventional proportional‐integral DPC (PI‐DPC) method.

In this research, an effective application and performance assessment of the Neuro-Fuzzy Controller (NFC) damping controller is designed to replace a single machine infinite bus (SMIB) power system stabilizer (PSS), and coordinated multi PSSs in large interconnected power systems are presented. The limitation of the conventional PSSs on SMIB and interconnected multi-machine test power systems are exposed and disclosed by the proposed NFC stabilizer. The NFC is a nonlinear robust controller which does not require a mathematical model of the test power system to be controlled, unlike the conventional PSSs’ damping controller. The Proposed NFC is designed to improve the stability of SMIB, an interconnected IEEE 3-machine, 9-bus power system, and an interconnected two-area 10-machine system of 39-bus New England IEEE test power system under multiple operating conditions. The proposed NFC damping controller performance is compared with the conventional PSS damping controller to confirm the capability of the proposed stabilizer and realize an improved system stability enhancement. The conventional PSSs’ design problem is transformed into an optimization problem where an eigenvalue-based objective function is developed and applied to design the SMIB-PSS and the interconnected multi-machine PSSs. The time-domain phasor simulation was done in the SIMULINK domain, and the simulation results show that the transient responses of the system rise time, settling time, peak time, and peak magnitude were all impressively improved by an acceptable amount for all the test system with the proposed NFC stabilizer. Thus, the NFC was able to effectively control the LFOs and produce an enhanced performance compared to the conventional PSS damping controller. Similarly, the result validates the effectiveness of the proposed NFC damping controller for LFO control, which demonstrates more robustness and efficiency than the classical PSS damping controller. Therefore, the application and performance of the NFC has appeared as a promising method and can be considered as a remarkable method for the optimal design damping stabilizer for small and large power systems.

Dual-Active-Bridge (DAB) converters are able to step up/down DC voltage in a wide range by adopting medium frequency transformer (MFT) for isolating and converting voltage level. Increase in switching frequency of Si IGBTs reduces the MFT size instead it intensifies the semiconductor switching losses which leads to increase in the heatsink size. In this paper variation of heatsink volume versus frequency is compared versus MFT. MFT and heatsink volume of a 5 kW 600 to 400 V DAB converter are optimized. Obtained results show that variation of switching frequency in range 1-10 kHz increases the size of optimal heatsink by 3 times, i.e

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