Volume 7 Issue 3 July-September 2019
LOSS MINIMIZATION CONTROL OF THREE PHASE ASYNCHRONOUS MACHINE [pp 01-03]
Aftab Ahmed Ansari, Akansha Mercy Steele , Dr. K.T. Chaturvedi
Abstract: Induction motor drives are commonly used for applications with vast variations in mechanical load for torques under nominal values. The most ideal scheme for induction motor drive design should include drive loss reduction, or efficiency improvement, proportional to load torque such that optimal performance of drive is not affected. Induction motors have good efficiencies when operating at full load. However, at lower than rated loads, which is a condition that many machines experience for significant portion of their service life, the efficiency ….
ROLE OF GENETIC ALGORITHM IN CONGESTION MANAGEMENT: A REVIEW [pp 04-08]
Ashish Vijayvargiya
Abstract: Congestion management is a major challenge in front of system operators particularly in deregulated system. Now a day’s power system is undergoing the process of deregulation everywhere to fulfill the increased demand, by inducing competition in electricity market and for the better utilization of distributed generating units. Various conventional and latest optimization techniques like nonlinear programming (NLP), dynamic programming (DP), ….
ROLE OF DYNAMIC VOLTAGE RESTORER IN POWER QUALITY – A REVIEW [pp 09-12]
Balwant Barkhaniya, Madhu Upadhyay
Abstract: Dynamic Voltage Restorer (DVR) is a modern and key custom power device to maintain the power quality. The DVR is a series compensator implemented to mitigate voltage sags and swell and to restore load voltage to its rated value. The Dynamic Voltage Restorer (DVR) is of high dynamic response, flexible and efficient solution to voltage sag and swell problem …
ARTIFICIAL INTELLIGENCE WITH SAFE AND SECURE DEEP LEARNING ARCHITECTURES [pp 13-18]
Harshal Shah
Abstract: Deep learning has emerged as a fundamental aspect of artificial intelligence (AI), fueling progress in fields such as computer vision, natural language processing, and self-driving systems. Nonetheless, as these models gain more power, the importance of safety and security becomes essential. This article examines the architectural advancements in deep learning focused on guaranteeing the safe and secure implementation of AI systems. It examines recent advancements in adversarial training, robust optimization, and model interpretability to combat vulnerabilities like adversarial assaults and data contamination. Adversarial training methods, which consist of training models to endure designed….