A predictive power control for wind energy

Sliding-mode Control for the Decoupled Power Control of Doubly-fed Induction Generator

“…To validate the simulation results, the SMC strategy is also applied to a DSP TMS320F2812 platform. The digital implementation of the controller are made by using an zero-order-holder discretization and delay is neglected due the fact the frequency of the system is slower than the frequency of the digital implementation [10].The rotor windings are fed by a three-phase voltage source inverter with with insulatedgate bipolar transistors (IGBTs) and the DFIG is driven by a DC motor. The rotor voltage commands are modulated by using symmetrical space vector PWM and the switching frequency is 5 kHz.…”

“…The proposed strategy uses the sliding mode controller and the stator-flux-oriented control to regulate the rotor currents and the active and reactive power based on (9) and (10).…”

“…The problems in using PI controllers are the tunning, the crosscoupling of DFIG terms and it's slow response in small hydroelectric station applications. To avoid the use of PIs, in [10] proposes controllers for field-oriented control (FOC) based on the dynamic modeling of the DFIG. However, this strategy presents a high computational cost and only simulation results was presented.…”

Communication systems for grid integration of renewable energy resources

“…Small scale wind farms can be integrated into power distribution networks to meet local demands. Because of high variability and intermittency, wind farm operations become a great challenge to power systems [4].…”

Impacto do Tamanho do Horizonte Deslizante para Controle Preditivo em Turbinas Eólicas Baseadas em DFIG

“…O Model Based Predictive Control (MBPC) é uma abordagem de controle que utiliza um modelo do sistema para calcular o comportamento futuro, obtendo-se uma lei de controle a partir dessa característica [12]. Na literatura existem diversas técnicas de controle preditivo aplicado ao DFIG, como controle preditivo generalizado, que usa a função de transferência como modelo [13], [14], MBPCs com modelos não lineares [15], [16], controle preditivo em tempo continuo [17], MBPC com matriz de conversão direta [18], MBPC com controle direto de potência [19], [20], finite control set MBPC [21] e com controle preditivo baseado no modelo em espaço de estados [22], [23]. Dentre os controladores preditivos, modelo em espaço de estados tem a vantagem de ter um baixo custo computacional, quando comparado os modelos não lineares, sua capacidade de lidar diretamente com as componentes de acoplamento e a componente relativa ao fluxo [22].…”