A hybrid LR-secant method-invasive weed optimisation for profit-based unit commitment
by A.V.V. Sudhakar; Chandram Karri; A. Jaya Laxmi
International Journal of Power and Energy Conversion (IJPEC), Vol. 9, No. 1, 2018

Abstract: This paper proposes a hybrid Lagrangian relaxation (LR)-secant method-invasive weed optimisation (IWO) for solving profit-based unit commitment (PBUC) problem. The PBUC problem is one of the important optimisation problems in deregulation. The objective of generation companies (GENCOs) in deregulated environment is to schedule the generating units for maximising the profit. Three stages are involved in the suggested method. The unit commitment problem is solved by Lagrangian relaxation (LR) for a given forecasted power demand, reserve and electricity price by incorporating various constraints, then optimal output powers for committed units are determined by secant method and finally IWO is applied to update the Lagrangian multipliers based on the duality gap between the primal cost and duality cost. It has been tested for various test cases such as 3 units, 10 units and 20 units system to prove the applicability of the proposed method. Simulation results have been compared with existing methods available in the literature. A comparison of the simulation results of the recommended method with the results of previous published methods shows that this method provides a qualitative solution.

Online publication date: Fri, 01-Dec-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 Power and Energy Conversion (IJPEC):
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