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Delhi, India

Maharaja Surajmal Institute of Technology is located at C-4, Janakpuri in New Delhi, India. It has a campus spread over 8 acres of land. It is the engineering branch of the Maharaja Surajmal Institute and is among top 5 colleges of IPU. The college is affiliated with Guru Gobind Singh Indraprastha University. Wikipedia.

Arya Y.,Maharaja Surajmal Institute of Technology | Kumar N.,Delhi Technological University
Electric Power Components and Systems

In this study, fuzzy gain scheduling controllers are proposed for automatic generation control of interconnected electrical power systems. Primarily, the study is done for automatic generation control of a two-area non-reheat thermal power system, and the parameters of fuzzy gain scheduling controllers are optimized by a genetic algorithm. Simulation results show the performance of fuzzy gain scheduling controllers is superior compared to the optimal and controllers based upon the gravitational search, the bacteria foraging optimization, and the hybrid bacteria foraging optimization–particle swarm optimization algorithms for an identical power system. The proposed approach is further protracted to a two-area reheat thermal system; the benefits of the fuzzy gain scheduling approach are demonstrated over optimal, conventional proportional-integral, and genetic algorithm-based integral controllers. Next, a multi-source multi-area hydro thermal system is considered, and the superiority of fuzzy gain scheduling controllers is established by comparing the results to the genetic algorithm and best claimed hybrid firefly algorithm–pattern search technique-based controllers. Finally, the effectiveness of the proposed approach is established for a two-area restructured reheat thermal power system. The simulation results indicate that the proposed fuzzy gain scheduling controllers work efficiently and provide better dynamic performance without being redesigned for separate systems. 2016 Copyright © Taylor & Francis Group, LLC Source

Rao M.,Maharaja Surajmal Institute of Technology | Singh N.,Gautam Buddha University
Smart Innovation, Systems and Technologies

Mobile Ad Hoc Networks (MANETs) are a self-configuring network of mobile nodes characterized by multi hops and forming a dynamic wireless topology. Efficient routing protocols are the backbone of MANETs and enable the network to support various Quality of Service (QoS) parameters. Most of the routing protocols like Ad Hoc On Demand Distance Vector (AODV) send packets via a single route. However, failure of this single route results in decline of performance of MANETs. Providing a single backup route does not solve the problem completely as the failure of the backup route again leads to lower QoS parameters. This paper proposes AODV routing protocol with nth backup route (AODV nthBR) that provides source node with more than one back up routes in case of a link failure. The proposed scheme results in better throughput, improved packet delivery fraction and lesser end to end delay. © Springer International Publishing Switzerland 2014. Source

Sharma J.,Jawaharlal Nehru University | Sharma S.C.,Delhi Technological University | Jain V.K.,Jawaharlal Nehru University | Gahlot A.,Maharaja Surajmal Institute of Technology
Physics of Plasmas

A gyrating ion beam propagating through a magnetized plasma cylinder containing K positive ions, electrons, and S F 6 - negative ions drives electrostatic lower hybrid waves to instability via Cyclotron interaction. Numerical calculations of the unstable mode frequencies and growth rates of both the unstable positive ion and negative ion modes have been carried out for the existing negative ion plasma parameters. It is found that the unstable mode frequencies of both the modes increase, with the relative density of negative ions. In addition, the growth rates of both the unstable modes also increases with relative density of negative ions. Moreover, the growth rates of both the unstable modes scale as the one-third power of the beam density. The frequencies of both the unstable modes also increase with the magnetic fields. The real part of the unstable wave frequency increases as almost the square root of the beam energy. © 2013 American Institute of Physics. Source

Arya Y.,Maharaja Surajmal Institute of Technology | Kumar N.,Delhi Technological University
International Journal of Electrical Power and Energy Systems

This paper proposes the automatic generation control (AGC) of an interconnected multi-area multi-source hydrothermal power system under deregulated environment. The two equal control areas with hydro and thermal generating power sources are interconnected via AC/DC parallel links. The optimal proportional integral (PI) regulators are designed for the proposed power system to simulate all power market transactions which are possible in a restructured power system. The concept of DISCO participation matrix (DPM) is harnessed to simulate the transactions. Eigenvalue study is conducted to assess the effect of AC/DC parallel links on system performance. The study is also conducted, considering appropriate generation rate constraints (GRCs) for thermal and hydro generating sources. Further, the dynamic responses of the proposed multi-source hydrothermal power system are compared with single-source thermal-thermal power system and it has been ascertained that the responses of proposed power system are sluggish with large overshoots and settling times. Finally, the study is extended to frame and implement optimal PI regulators for the first time for the AGC of a conventional two-area non-reheat thermal power system with governor dead-band nonlinearity. The superiority of the optimal PI regulators has been established by comparing the results with recently published best claimed craziness based particle swarm optimization (CRAZYPSO) and hybrid bacterial foraging optimization algorithm-particle swarm optimization (hBFOA-PSO) algorithms based PI controller tuned for the same interconnected power system. © 2015 Elsevier Ltd. All rights reserved. Source

Goel S.,Maharaja Surajmal Institute of Technology
2014 International Conference on Data Mining and Intelligent Computing, ICDMIC 2014

The growing need of finding efficient solutions to various optimization problems has motivated computer researchers to search for varied problem-solving methods. Nature has greatly inspired and motivated us in finding solutions to various optimization problems. Swarm Intelligence is a result of one such motivation where nature based swarm behavior of many social organisms like bees, bacteria, fireflies, cockroaches, mosquitoes is used for finding solutions to optimization problems. This paper introduces a new bio-Inspired optimization approach, namely, Pigeon Optimization Algorithm(POA) in the field of Swarm Intelligence. POA is based on the swarming behavior of passenger pigeons. The grouping and searching behavior of a flight of pigeons is used for finding the optimization solution to a given problem. The proposed algorithm demonstrates its suitability in finding the shortest path from a given source. The results obtained are compared and verified using Dijkstra's Algorithm. It has been found that the above algorithm has the potential and hence, can be used for solving different optimization problems in future. © 2014 IEEE. Source

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