Static economic dispatching method for power system employing group experience-based artificial bee colony algorithm
An artificial bee colony algorithm and power system technology, which is applied in the field of static economic dispatch of power systems based on the artificial bee colony algorithm based on group experience, can solve the problems of weak local optimization ability, slow convergence speed, and weak global search ability.
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[0098] In this embodiment, a total of 140 thermal power generation units are used, with a total load of 49342. For power supply parameters, see http: / / www3.ntu.edu.sg / home / epnsugan / , EABenchmarks / CECCompetitions / CEC11CompetitiononTestingEvolutionaryAlgorithmsonReal-worldNumericalOptimizationProblems / SoftwareinMatlab / Matlab / CEC_2011_Matlab / CEC_2011_Spl_Session / Probs_11_ELD_Package / ELDCodes / fn_ELD_140, the network loss in this embodiment is negligible.
[0099] The following table compares the optimization results of the three algorithms: particle swarm optimization, artificial bee colony algorithm, and artificial bee colony algorithm based on group experience:
[0100]
[0101] The invention improves the search strategies of the hired bees and the observed bees in the artificial bee colony algorithm, so that the hired bees can better balance the global search and local optimization, and the observed bees can focus on fine search. Compared with the standard particle swarm al...
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