A FIS-GA combined approach for transmission congestion management in restructured power system
by Saswati Kumari Behera; Nalin Kant Mohanty
International Journal of Mathematical Modelling and Numerical Optimisation (IJMMNO), Vol. 7, No. 3/4, 2016

Abstract: A power system under goes frequent changes due to disturbances. If the power system survives after the disturbance it will be operating in a new steady state, in which one or more transmission lines may be over loaded. The over loading of the transmission line can be eliminated by generator rescheduling and/or load shedding. This paper proposes fuzzy inference system (FIS)-based algorithm for overload indication in transmission line. The system parameters such as line overload factor (OF) and transmission congestion distribution factors (TCDFs) are given as the FIS input. The output from the FIS indicates whether the line is overloaded or not. Then generator rescheduling/load shedding is done to relief the congested line. The effectiveness of the congestion clusters method for CM is discussed by formulating two objective functions. Rescheduling of generation is formulated as an optimisation problem with the objective of obtaining minimum cost and proposed objective of achieving minimum real power loss. Attractive features of genetic algorithm (GA) are used for solving the formulated problem with the objectives considered separately. The effectiveness of the proposed approach has been tested for 5 bus system, 30 bus systems in MATLAB environment.

Online publication date: Mon, 30-Jan-2017

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Mathematical Modelling and Numerical Optimisation (IJMMNO):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com