Investigation and validation of PV fed reduced switch asymmetric multilevel inverter using optimization based selective harmonic elimination technique

Pulse width modulation for Selective Harmonics Elimination (SHE) is mostly employed in the reduction of lower order harmonics. The PV system in this research provides input voltage to the reduced switch 31-level inverter, which is based on the Artificial Bee Colony algorithm. With a high gain DC-DC single-ended primary-inductor converter (SEPIC), the PV panel output voltage is kept constant. The Grey wolf optimization algorithm (GWO) approach is used to get the most power out PV scheme. Multi Carrier modulation, a high-frequency modulation technology, is also used in this novel design of the inverter to reduce upper order harmonics. The suggested Artificial Bee Colony (ABC) algorithm, harmonics is compared to a SHE technique based on a genetic algorithm. The hardware findings were confirmed using DSPIC30F2010 controller simulation, and the recommended system was validated using Matlab simulation

Showdown : Perspectives on the Southwest

Includes brief descriptions of five exhibitions gathering 66 artists from the Southwestern United States. Biographical notes

Application of Flower Pollination Algorithm for Solving Complex Large-Scale Power System Restoration Problem Using PDFF Controllers

Automatic Generation Control (AGC) in modern power systems is getting complex, due to intermittency in the output power of multiple sources along with considerable digressions in the loads and system parameters. To address this problem, this paper proposes an approach to calculate Power System Restoration Indices (PSRI) of a 2-area thermal-hydro restructured power system. This study also highlights the necessary ancillary service requirements for the system under a deregulated environment to cater to large-scale power failures and entire system outages. An abrupt change in consumer load demands and disturbances in any control region (area) of a multiarea (interrelated) system causes severe fluctuations in frequency and interarea power exchanges. However, simple Proportional and Integral (PI) controllers are most prevalent in the literature to effectively resolve AGC issues, while its integral gain is smaller due to the larger overshoot in transient performance. Therefore, an attempt has been made with a novel control strategy, known as the pseudoderivative feedforward with feedback (PDFF) controller, is developed to keep the interarea power exchanges and the frequency to the specified limits after load changes. A PDFF controller is designed and implemented using the flower pollination algorithm (FPA) to obtain optimal dynamic performance for different types of potential power flows in a restructured power system under investigation. The proposed PDFF controller localizes the zero at an optimal place that reduces the rise time of the step-response to reduce the excessive overshoot and gives much better dynamic performances as compared to the PI control structure. The Integral Square Error (ISE) is considered as a performance criterion to derive the optimized gain of the PDFF control structure using FPA. Different PSRI are computed based on the transient response of the 2-area deregulated multisource system and different restoration measures to be taken are also discussed. The simulation results clearly show that the proposed approach is very powerful in decreasing the frequency and tie-power digressions under different load perturbations

An Extensive Critique on Smart Grid Technologies: Recent Advancements, Key Challenges, and Future Directions

Given the various aspects of climate change and the growing demand for energy, energy efficiency and environmental protection have become major concerns worldwide. If not taken care of, energy demand will become unmanageable due to technological growth in cities and nations. The solution to the global energy crisis could be an advanced two-way digital power flow system that is capable of self-healing, interoperability, and predicting conditions under various uncertainties and is equipped with cyber protections against malicious attacks. The smart grid enables the integration of renewable energy sources such as solar, wind, and energy storage into the grid. Therefore, the perception of the smart grid and the weight given to it by researchers and policymakers are of utmost importance. In this paper, the studies of many researchers on smart grids are examined in detail. Based on the literature review, various principles of smart grids, the development of smart grids, functionality of smart grids, technologies of smart grids with their characteristics, communication of smart grids, problems in the implementation of smart grids, and possible future studies proposed by various researchers have been presented

Analysis of isolated phase windings and permanent magnet assists high energy efficient hybrid‐reluctance motor for electric vehicle

Abstract This article describes the electromagnetic analysis of high efficient hybrid motor, which comprises the salient features of switched reluctance motor (SRM) and spoke‐type brushless DC motor. The main objective is to develop a motor with a high‐power density and winding faulty capability. Furthermore, this research article extends in the manner to increase the power density of the motor through the sensitivity analysis on rotor geometry by replacing the rotating part of SRM and adopting the rotor of spoke type brushless DC motor, originating the hybrid motor with the high‐power density and enhanced efficiency. To ensure the winding fault capability, a SRM‐based stator winding is adopted. Then, the modelling process for hybrid motor 48 V, 1500 RPM, 2 kW, and 12.7 Nm are detail in both analytical and finite element methods. The electromagnetic analysis is carried out to estimate the torque characteristics and flux pattern of the proposed motor. Furthermore, the proposed motor is analysed with the selection of laminating core material among M 27 24 Ga, 36F155, 46F165, 47F165, M 420 50D, and arnon 7. This infers 36F155 material assists proposed motor has high‐performance characteristics. The vibration frequencies are investigated in modal aspects to estimate the natural frequencies of vibrations. These analyses are validated among analytical and finite element results under no‐load conditions

Machine learning based load prediction in smart‐grid under different contract scenario

Abstract Many progressed information scientific strategies, particularly Artificial Intelligence (AI) and profound learning methods, have been proposed and tracked down wide applications in our general public. This proposition creates information driven arrangements by utilizing the most recent profound learning and AI innovation, including outfit learning, meta‐learning and move learning, for energy the executives framework issues. Genuine world datasets are tried on proposed models contrasted and best in class plans, which exhibit the predominant presentation of the proposed model. In this proposition, the engineering of the Smart Grid testbed is additionally planned and created by using ML calculations and true remote correspondence frameworks to such an extent that constant plan necessities of Smart Grid testbed is met by this reconfigurable system with stacking of full convention in medium access control (MAC) and physical layers (PHY). The proposed engineering has the reconfiguration property in view of the organization of remote correspondence and trend setting innovations of Information and communication technologies (ICT) which incorporates Artificial Intelligence (AI) calculation. The fundamental plan objectives of the Smart Grid testbed is to make it simple to construct, reconfigure and scale to address the framework level prerequisites and to address the ongoing necessities

Smart Fault Monitoring and Normalizing of a Power Distribution System Using IoT

Conventional outage management practices in distribution systems are tedious and complex due to the long time taken to locate the fault. Emerging smart technologies and various cloud services offered could be utilized and integrated into the power industry to enhance the overall process, especially in the fault monitoring and normalizing fields in distribution systems. This paper introduces smart fault monitoring and normalizing technologies in distribution systems by using one of the most popular cloud service platforms, the Microsoft Azure Internet of Things (IoT) Hub, together with some of the related services. A hardware prototype was constructed based on part of a real underground distribution system network, and the fault monitoring and normalizing techniques were integrated to form a system. Such a system with IoT integration effectively reduces the power outage experienced by customers in the healthy section of the faulted feeder from approximately 1 h to less than 5 min and is able to improve the System Average Interruption Duration Index (SAIDI) and System Average Interruption Frequency Index (SAIFI) in electric utility companies significantly

Investigation and validation of PV fed reduced switch asymmetric multilevel inverter using optimization based selective harmonic elimination technique

Pulse width modulation for Selective Harmonics Elimination (SHE) is mostly employed in the reduction of lower order harmonics. The PV system in this research provides input voltage to the reduced switch 31-level inverter, which is based on the Artificial Bee Colony algorithm. With a high gain DC-DC single-ended primary-inductor converter (SEPIC), the PV panel output voltage is kept constant. The Grey wolf optimization algorithm (GWO) approach is used to get the most power out PV scheme. Multi Carrier modulation, a high-frequency modulation technology, is also used in this novel design of the inverter to reduce upper order harmonics. The suggested Artificial Bee Colony (ABC) algorithm, harmonics is compared to a SHE technique based on a genetic algorithm. The hardware findings were confirmed using DSPIC30F2010 controller simulation, and the recommended system was validated using Matlab simulation

Inner Resonance and Outer Current Based Control Strategy for Inductive Power Transfer System Used in Wireless Charging for Electric Vehicles

The wireless charging for electric vehicle is getting popular due to the absence of sophisticated cable connection and associated issues with the actuators in field for connected charging. The major challenges in inductive power transfer (IPT) systems are the control of the resonance converter and synchronisation in communications with the vehicle and power supply. In IPT system, the dynamic nature of load as well as system demands extra care for the existing charging architectures. This work proposes a unique control algorithm to charge the Li-ion battery under coupling coefficient and load variations. The developed control algorithm is validated in MATLAB simscape platform. Further, the control logic is validated using the Texas C2000 Delfino controller in 1 kW IPT system. The developed control logic would ensure proper frequency of operation as well as the constant voltage and constant current control