In this paper, the adaptive wind driven optimization (AWDO) algorithm is applied for solving the combined economic emission dispatch (CEED) problem. AWDO is one of the newest hybrid algorithms, which optimizes the selection of coefficients at each iteration, eliminating the need for tuning the coefficients. The evaluation of AWDO performances is carried out on the standard IEEE 30-bus test system with 6 generating units and with various cost curve natures. The results of AWDO use with the test system are compared against the results of use of 3 algorithms: the moth swarm algorithm, firefly algorithm, and hybrid particle swarm optimization and gravitational search algorithm, which were proposed in recent literature for solving this problem. The present paper shows that AWDO gives an accurate and effective solution of the CEED problem and outperforms the other tested algorithms.
Computational intelligence, heuristic algorithms, power generation dispatch, power system analysis com- puting, power engineering computing
JEVTIC, MILENA; JOVANOVIC, NENAD; and RADOSAVLJEVIC, JORDAN
"Solving a combined economic emission dispatch problem using adaptive wind driven optimization,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 26:
4, Article 6.
Available at: https://journals.tubitak.gov.tr/elektrik/vol26/iss4/6