Control Strategy of Leveling Load Power Fluctuations Based on Fuzzy Neural Networks by Tuning Coefficients of Learning Rate with Genetic Algorithm

摘要

The effective usage of the power facilities can be realized by leveling the fluctuating active power and compensating the reactive power. The fuzzy and fuzzy neural network control strategy of superconducting mag- netic energy storages (SMES) was proposed for this purpose. The control results depend on the values of coefficients of learning rate in fuzzy neural networks. Therefore, it is desirable to obtain better control results by Tuning the coefficients of learning rate to their optimum Values.