Proceedings of the International Conference on Artificial Intelligence Techniques for Electrical Engineering Systems (AITEES 2022)

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Implementation of Adaptive PSODV to Improved Benders Decomposition Based Unit Commitment

Authors
M. Ramu1, *, L. Ravi Srinivas2, S. Tara Kalyani3
1Department of EECE, GITAM University, Visakhapatnam, India
2Department of EEE, Seshadri Rao Gudlavalleru Engineering College, Gudlavalleru, India
3Department of EEE, JNTUH, Hyderabad, India
*Corresponding author. Email: ramugitam@gmail.com
Corresponding Author
M. Ramu
Available Online 5 December 2022.
DOI
10.2991/978-94-6463-074-9_8How to use a DOI?
Keywords
Unit Commitment; Improved Benders Decomposition; Lagrangian multipliers; adaptive Particle swarm optimization
Abstract

This paper aims at the latest approach for solving the security-constrained unit commitment problem (UCP) dependent on Improved Benders Decomposition (IBD) to Adaptive Particle swarm optimization with differentially perturbed velocity (APSODV). The proposed IBD determines the optimal unit commitment schedule which includes minimum up/downtime and spinning reserve constraints. APSODV algorithm initializes and updates the Lagrangian multipliers and improves the solution fineness. The accomplishment of the suggested technique is at first examined on a 10-unit system and extended to 100-unit with a 24-h horizon. The results specify that an effective and strong solution for UC can be attained from the proposed technique.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Artificial Intelligence Techniques for Electrical Engineering Systems (AITEES 2022)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
5 December 2022
ISBN
10.2991/978-94-6463-074-9_8
ISSN
2589-4919
DOI
10.2991/978-94-6463-074-9_8How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - M. Ramu
AU  - L. Ravi Srinivas
AU  - S. Tara Kalyani
PY  - 2022
DA  - 2022/12/05
TI  - Implementation of Adaptive PSODV to Improved Benders Decomposition Based Unit Commitment
BT  - Proceedings of the International Conference on Artificial Intelligence Techniques for Electrical Engineering Systems (AITEES 2022)
PB  - Atlantis Press
SP  - 72
EP  - 82
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-074-9_8
DO  - 10.2991/978-94-6463-074-9_8
ID  - Ramu2022
ER  -