Anadaptiveradialbasisfunctionneuralnetwork(RBFNN) controlofenergystoragesystem foroutputtrackingofa permanent magnet wind generator

Maejo International Journal of Science and Technology

Abu H. M. A. Rahim¹ 

[1] DepartmentofElectricalEngineering,KingFahdUniversityofPetroleumandMinerals, Dhahran, Saudi Arabia;

关键词: adaptive control;    energy storage control;    radial basis function neural network;    permanent magnet synchronous generator;    wind turbine;   

DOI  :  10.14456/mijst.2014.6

来源: DOAJ

【 摘 要 】

Theconvertersofapermanentmagnetsynchronousgeneratorhavetobe properlycontrolledtoachievemaximumtransferofenergyfromwind.Toachiev ethis goal,thisarticleemploysanenergystoragedeviceconsistingofanenergycapacitor interfaced through a voltage source converter which is operated through a smart adaptive radial basis function neural network (RBFNN) controller. The proposed adaptive strategy employsonlineneuralnetworktrainingasopposedtoconventionalprocedurerequiring offlinetrainingofalargedata-set.TheRBFNNcontrollerwastestedforvarious contingencies in the wind generator system. Th e adaptive onlinecontrollerisobserved to provideexcellentdampingprofilefollowinglowgridvoltageconditionsaswellasfor other large disturbances. The controlled converter DC capacitor voltage helpsmaintaina smooth flow of real and reactive power in the system.

【 授权许可】

Unknown