Abstract- An important criterion in power system operation is to meet the power demand at minimum fuel cost using an optimal mix of different power plants. Moreover, in order to supply electric power to customers in a secured and economic manner, thermal unit commitment is considered to be one of the best available options. It is thus recognized that the optimal unit commitment of thermal systems results in a great saving for electric utilities. The unit commitment has been identified for this paper work. The complexity of the UC problems grows exponentially to the number of generating units especially by applying the deregulated rules in power system. Where in this environment the objective function is maximizing the profit while satisfying the regular unit commitment constrains with addition of new constrains such as bilateral and multilateral contracts. The formulation of unit commitment has been discussed and the solution is obtained by an algorithm based on Particle Swarm Optimization technique the proposed algorithm is implemented in MATLAB environment.
Kaddah, S., Elsehiemy, R., & Zaky, A. .. (2014). Solving Unit Commitment Problem in Regulated and Deregulated Power Systems Using Particle Swarm Algorithm. ERJ. Engineering Research Journal, 37(2), 165-177. doi: 10.21608/erjm.2014.66916
MLA
Sahar.S. Kaddah; Ragab.A. Elsehiemy; Alaa .A. Zaky. "Solving Unit Commitment Problem in Regulated and Deregulated Power Systems Using Particle Swarm Algorithm". ERJ. Engineering Research Journal, 37, 2, 2014, 165-177. doi: 10.21608/erjm.2014.66916
HARVARD
Kaddah, S., Elsehiemy, R., Zaky, A. .. (2014). 'Solving Unit Commitment Problem in Regulated and Deregulated Power Systems Using Particle Swarm Algorithm', ERJ. Engineering Research Journal, 37(2), pp. 165-177. doi: 10.21608/erjm.2014.66916
VANCOUVER
Kaddah, S., Elsehiemy, R., Zaky, A. .. Solving Unit Commitment Problem in Regulated and Deregulated Power Systems Using Particle Swarm Algorithm. ERJ. Engineering Research Journal, 2014; 37(2): 165-177. doi: 10.21608/erjm.2014.66916