K. Lakshmi This email address is being protected from spambots. You need JavaScript enabled to view it.1 and S. Vasantharathna2

1Department of Electrical and Electronics Engineering, KSR College of Technology, Tiruchengode, India
2Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology, Coimbatore, India


 

Received: June 6, 2012
Accepted: June 3, 2014
Publication Date: September 1, 2014

Download Citation: ||https://doi.org/10.6180/jase.2014.17.3.08  


ABSTRACT


In a competitive environment, electric power generation companies (Genco’s) need a generation schedule, which maximizes the profit over the scheduling period, subject to all prevailing constraints such as power demand, market prices, etc. Here, the proposed artificial immune system (AIS) approach representing the objective function as deemed antigen and the optimal solutions obtained are given as deemed antibodies. If an antibody fits the antigen best, then this antibody is deemed the optimal solution. The convergence speed of artificial immune algorithm has been increased greatly by shortening the code length, which could be achieved by encoding of continuous operating time. Simulation results of an IEEE test system and an Indian utility system demonstrate the effective performance of the proposed technique. Also, the numerical results were compared with the conventional method of lagrange relaxation for reaching proper unit commitment in a day ahead competitive electricity markets.


Keywords: Price Based Unit Commitment, Artificial Immune Algorithm, Deregulated Power Markets, Lagrange Relaxation


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