A static economic dispatch method for power system based on artificial bee colony algorithm based on swarm experience
An artificial bee colony algorithm and power system technology, applied in the field of static economic dispatch of electric power system based on group experience artificial bee colony algorithm, can solve the problems of weak global search ability, slow convergence speed, fast convergence speed, etc., and achieve accelerated accuracy The optimization ability and convergence speed, the minimization of the total cost of power generation, and the effect of minimization of output
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[0098] In this embodiment, a total of 140 thermal power generating units are used, with a total load of 49342. For power parameters, see http: / / www3.ntu.edu.sg / home / epnsugan / , EA Benchmarks / CEC Competitions / CEC11Competition on Testing Evolutionary Algorithms on Real- world NumericalOptimization Problems / Software in Matlab / Matlab / CEC_2011_Matlab / CEC_2011_Spl_Session / Probs_11_ELD_Package / ELD Codes / 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 sw...
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