Optimal rescheduling of real power generation for congestion management using teaching-learning-based optimization algorithm

Bibliographic Details
Title: Optimal rescheduling of real power generation for congestion management using teaching-learning-based optimization algorithm
Authors: Sumit Verma, Subhodip Saha, V. Mukherjee
Source: Journal of Electrical Systems and Information Technology, Vol 5, Iss 3, Pp 889-907 (2018)
Publisher Information: SpringerOpen, 2018.
Publication Year: 2018
Collection: LCC:Electrical engineering. Electronics. Nuclear engineering
LCC:Information technology
Subject Terms: Electrical engineering. Electronics. Nuclear engineering, TK1-9971, Information technology, T58.5-58.64
More Details: This paper proposes teaching-learning-based optimization (TLBO) algorithm for congestion management (CM) in a pool based electricity market. Congestion is a principal problem that an independent system operator faces in post deregulated era. The aim of employing TLBO algorithm is to effectively relieve congestion in the line with minimum deviation in initial generation and, hence, congestion cost. Various security constraints such as load bus voltage and line loading are taken into account while dealing with this problem. Inspired by teaching–learning process of classroom, TLBO algorithm is a recent population based algorithm which does not require any algorithm specific control parameters unlike other algorithms. It only requires common control parameters like population size and number of generation. In this paper, the proposed TLBO algorithm is applied on modified IEEE 30- and 57-bus test power system for the solution of CM problem. The results obtained are compared to those reported in the recent state-of-the-art literature. The efficacy of the TLBO algorithm for obtaining higher quality solution is also established. Keywords: Congestion management, Deregulation, Independent system operator (ISO), Optimal power flow, Price bids, Teaching-learning-based optimization (TLBO)
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2314-7172
Relation: http://www.sciencedirect.com/science/article/pii/S2314717216301143; https://doaj.org/toc/2314-7172
DOI: 10.1016/j.jesit.2016.12.008
Access URL: https://doaj.org/article/5979fa4a36ee4aca8fef6de59984ef87
Accession Number: edsdoj.5979fa4a36ee4aca8fef6de59984ef87
Database: Directory of Open Access Journals
More Details
ISSN:23147172
DOI:10.1016/j.jesit.2016.12.008
Published in:Journal of Electrical Systems and Information Technology
Language:English