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In regard to the present-day electrical power scenario, this article reports a power generation control of restructured hybrid power system with a multi-source combination of solar-thermal, geothermal, electric vehicle (EV), and conventional thermal system. Involvements of renewables and EVs in an electrical grid system with appropriate system non-linearities make the power system complex and a practical one. Such a system needs a robust controller to function optimally. In view of this, several controllers are examined for system dynamics. Performance comparison reveals the novel disturbance rejection-based fractional-order–proportional–integral–derivative (DR-foPID) as an optimal controller. Furthermore, the impact of energy storage devices (ESD) such as redox flow battery (RFB) for system dynamics enhancement are explored. To obtain the optimal performance of the linked restructured power system, the secondary controller gains and other parameters are optimized using a powerful biogeography-based krill herd (BBKH) optimization technique. The results indicate that with the proposed controller, a 38% reduction in response undershoot, a 13% reduction in overshoot, and a 8.3% reduction in settling time are exhibited. Moreover, the objective function (error) values for the proposed controller reduce to 95% with respect to other controllers. The effect of renewables and EVs on system stability is also studied. Moreover, the proposed secondary DR-foPID controller is also examined on a three-area hybrid regulated power system. Sensibility evaluation related to different alterations in nominal system parameters verifies the strength of the DR-foPID controller. [ABSTRACT FROM AUTHOR]

Wind power with low or no greenhouse gas emissions has been highly prevalent over the last decade. Modern renewable energy systems rely heavily on power electronic devices such as multilevel converters (MLC) to integrate renewables into the grid or provide electricity to islanding loads. These converters' power electronic switches have a high failure rate (approximately 34 percent). As a result, the reliability evaluation of these converters is vital. Most research has focused on developing a fault-tolerant, efficient and cost-effective topology that reduces components. Still, the reliability of these topologies has received relatively little attention. This paper studies the effect of voltage stress on three-level Active Neutral Point Clamped (ANPC) multilevel inverter reliability. The series redundancy is introduced in ANPC using redundant outer switches, making ANPC a fault-tolerant topology. The reliability of this fault-tolerant topology is compared with the fault-intolerant ANPC. The voltage stress factor is calculated for fault intolerant and proposed fault-tolerant ANPC topologies. Because of the reduced stress on the switches and redundant configuration of the outer switches, the proposed fault-tolerant ANPC is more reliable. The fault-tolerant topology proposed in this paper has the lowest voltage stress factor, resulting in better reliability. [ABSTRACT FROM AUTHOR]

This article reports a relay algorithm based protection of static var compensator (SVC) based compensated transmission line utilizing artificial neural networks (ANN). The sequentially involved four artificial neural networks (ANNs) are used. The first ANN detects fault and the second ANN classifies it as either a ground or a phase fault. The faulted phases are then detected using ground fault ANN or phase fault ANN, depending on the situation. A transmission line (100 km, 230 kV, 50Hz) is simulated with SVC at the midpoint using a sampling frequency of 1 kHz in PSCAD/EMTDC. The sequence current ratios are used in fast protection algorithm with 100% accuracy in 4 milliseconds and identify them as phase or ground faults in 8 milliseconds. Finally, the identification of the faulted phase/phases requires just 13 milliseconds. Further, the number of thyristor-switched capacitors (TSC) in SVC depends on several factors such as thyristor valve, reactive power output, and electrical network type. However, the effect of the number of TSCs on the SVC reliability and criticality is not found in the existing literature. The reliability of SVC is increased is reported in this work by varying the number of TSC branches. The observations found increase of 15.47% in the SVC reliability by increasing TSC branches from one to three. In this way, the number of TSC branches in SVC can be optimized to increase the system's reliability with minimum cost. [ABSTRACT FROM AUTHOR]