Volume 13, Issue 1 (March 2017)                   IJEEE 2017, 13(1): 32-46 | Back to browse issues page


XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Moradi A R, Alinejad-Beromi Y, Kiani K. Locating of Series FACTS Devices for Multi-Objective Congestion Management Using Components of Nodal Prices. IJEEE 2017; 13 (1) :32-46
URL: http://ijeee.iust.ac.ir/article-1-1025-en.html
Abstract:   (5121 Views)

Congestion and overloading for lines are the main problems in the exploitation of power grids. The consequences of these problems in deregulated systems can be mentioned as sudden jumps in prices in some parts of the power system, lead to an increase in market power and reduction of competition in it. FACTS devices are efficient, powerful and economical tools in controlling power flows through transmission lines that play a fundamental role in congestion management. However, after removing congestion, power systems due to targeting security restrictions may be managed with a lower voltage or transient stability rather than before removing. Thus, power system stability should be considered within the construction of congestion management. In this paper, a multi-objective structure is presented for congestion management that simultaneously optimizes goals such as total operating cost, voltage and transient security. In order to achieve the desired goals, locating and sizing of series FACTS devices are done with using components of nodal prices and the newly developed grey wolf optimizer (GWO) algorithm, respectively. In order to evaluate reliability of mentioned approaches, a simulation is done on the 39-bus New England network.

Full-Text [PDF 972 kb]   (1869 Downloads)    
Type of Study: Research Paper | Subject: HVDC and FACTS
Received: 2016/11/24 | Revised: 2017/08/23 | Accepted: 2017/04/08

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Creative Commons License
© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.