Unit commitment has been solved with many techniques viz., genetic algorithms evolution ary programming, simulated annealing, optimization and tab along with the combination of dynamic programming. This paper proposes Particle swarm Optimization combined with Lagrange Relaxation method (LR) for solving Unit Commitment (UC). The results from the test samples are compared with those obtained by Particle swarm optimization for solving unit commitment, Genetic algorithm and LR. The shortcoming of branch-and-bound is the exponential growth in the execution time with the size of UC problem. The integer and mixed integer methods adopt linear programming technique to solve and check for an integer solution. These methods have only been applied to small UC problems and have required major assumptions which limit the solution space. Lagrange relaxation for UC problem was superior to dynamic programming due to its faster computational time. However, it suffers from numerical convergence and solution quality problems. Furthermore, solution quality of LR depends on the method to update Lagrange multipliers. This paper proposes a new hybrid method for solving UC problem. The proposed method is developed in such way that a particle swarm optimization technique is applied to update Lagrange multipliers and improves the performance of LR method. To illustrate the effective of the proposed method, it is tested and compared to the conventional LR [69], GA [69], and HPSO [79] on 4 units test system and 10 units test system, respectively.

1. International Conference on Systems, Science, Control, Communication, Engineering and Technology 18
International Conference on Systems, Science, Control, Communication, Engineering and
Technology 2017 [ICSSCCET 2017]
ISBN 978-81-933235-0-2 VOL 01
Website icssccet.org eMail icssccet@asdf.res.in
Received 10 – January – 2017 Accepted 28 - January – 2017
Article ID ICSSCCET035 eAID ICSSCCET.2017.035
Unit Commitment with Lagrange Relaxation Using
Particle Swarm Optimization
JBV Subrahmanyam1
, Dhasharatha G2
, Kranthi Kumar V3
, Sankar Babu P4
1,4
Professor, 2,3
Asst. Professor, Department of EEE, TKR Engineering College Hyderabad, India
Abstract: Unit commitment has been solved with many techniques viz., genetic algorithms evolution ary programming, simulated annealing,
optimization and tab along with the combination of dynamic programming. This paper proposes Particle swarm Optimization combined with Lagrange
Relaxation method (LR) for solving Unit Commitment (UC). The results from the test samples are compared with those obtained by Particle swarm
optimization for solving unit commitment, Genetic algorithm and LR. The shortcoming of branch-and-bound is the exponential growth in the execution
time with the size of UC problem. The integer and mixed integer methods adopt linear programming technique to solve and check for an integer
solution. These methods have only been applied to small UC problems and have required major assumptions which limit the solution space. Lagrange
relaxation for UC problem was superior to dynamic programming due to its faster computational time. However, it suffers from numerical convergence
and solution quality problems. Furthermore, solution quality of LR depends on the method to update Lagrange multipliers. This paper proposes a new
hybrid method for solving UC problem. The proposed method is developed in such way that a particle swarm optimization technique is applied to
update Lagrange multipliers and improves the performance of LR method. To illustrate the effective of the proposed method, it is tested and compared to
the conventional LR [69], GA [69], and HPSO [79] on 4 units test system and 10 units test system, respectively.
ISBN 978-81-933235-0-2 VOL 01
Website icssccet.org eMail icssccet@asdf.res.in
Received 10 – January – 2017 Accepted 28 - January – 2017
Article ID ICSSCCET036 eAID ICSSCCET.2017.036
Performance Analysis of Multi-walled Carbon Nanotube
Bundle Interconnects
Deepthi1
, Aravind2
, Shivaprasanna3
1,2,3
Department of ECE, TKR Engineering College, Hyderabad, India
Abstract: In this paper frequency and stability responses have been acquired at longer interconnect lengths for multi-walled carbon nanotube bundle
(MCB). The performance of MCB interconnect is analysed using driver interconnect load while interconnect length increases stability increased. In order
to illustrate the modelling of MCB interconnect to analyse frequency, ABCD matrix has been implemented. Further, it is noticed that the cut-off
frequency of MCB interconnects is 20.1GHz for an interconnect length of 2mm. The results are validated with HSPICE simulations.
This paper is prepared exclusively for International Conference on Systems, Science, Control, Communication, Engineering and Technology 2017 [ICSSCCET
2017] which is published by ASDF International, Registered in London, United Kingdom under the directions of the Editor-in-Chief Dr JBV Subrahmanyam and
Editors Dr. Daniel James, Dr. Kokula Krishna Hari Kunasekaran and Dr. Saikishore Elangovan. Permission to make digital or hard copies of part or all of this work
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