Static Loadabilty Assessment Using Covariance Matrix Adapted Evolution Strategy

Abstract:

This paper discusses application of Covariance Matrix Adapted Evolution Strategy (CMAES) algorithm for maximizing loadability margin of power system. CMAES is a class of continuous evolutionary algorithm that generates new population members by sampling from a probability distribution that is constructed during the optimization process. IEEE 14 bus , 30 bus and 118 bus systems are considered for simulation purpose. For comparison of the results, primal dual interior point (PDIP), continuation power flow (CPF), Particle swarm optimization algorithms are considered. Statistical performance of CMAES algorithm reveals that even the mean value of maximum loadability is better than maximum loadability obtained in other methods. Even though CMAES takes higher computation time due to the determination of covariance matrix, only this algorithm gives maximum loadability margin.

• Periodical: Advanced Materials Research (Volume 651)
• Pages: 864-869
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.651.864
• Online since: January 2013
• Authors: S. Alamelu, S. Baskar, C.K. Babulal, S. Jeyadevi
• Keywords: CMAES, Evolutionary Algorithm (EA), Loadability Margin, Primal Dual Interior Point Algorithm

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