This paper proposes an optimized and coordinated model predictive control(MPC) scheme for doublyfed induction generators(DFIGs) with DC-based converter system to improve the efficiency and dynamic performance in DC gr...This paper proposes an optimized and coordinated model predictive control(MPC) scheme for doublyfed induction generators(DFIGs) with DC-based converter system to improve the efficiency and dynamic performance in DC grids. In this configuration, the stator and rotor of the DFIG are connected to the DC bus via voltage source converters, namely, a rotor side converter(RSC) and a stator side converter(SSC). Optimized trajectories for rotorflux and stator current are proposed to minimize Joule losses of the DFIG, which is particularly advantageous at low and moderate torque. The coordinated MPC scheme is applied to overcome the weaknesses of the field-oriented control technique in the rotor flux-oriented frame, which makes the rotor flux stable and the stator current track its reference closely and quickly. Lastly, simulations and experiments are carried out to validate the feasibility of the control scheme and to analyze the steady-state and dynamic performance of the DFIG.展开更多
First, a three-tier coordinated scheduling system consisting of a distribution network dispatch layer, a microgrid centralized control layer, and local control layer in the energy internet is proposed. The multi-time ...First, a three-tier coordinated scheduling system consisting of a distribution network dispatch layer, a microgrid centralized control layer, and local control layer in the energy internet is proposed. The multi-time scale optimal scheduling of the microgrid based on Model Predictive Control（MPC） is then studied, and the optimized genetic algorithm and the microgrid multi-time rolling optimization strategy are used to optimize the datahead scheduling phase and the intra-day optimization phase. Next, based on the three-tier coordinated scheduling architecture, the operation loss model of the distribution network is solved using the improved branch current forward-generation method and the genetic algorithm. The optimal scheduling of the distribution network layer is then completed. Finally, the simulation examples are used to compare and verify the validity of the method.展开更多
基金supported by National Natural Science Foundation of China(No.61473170)Key R&D Plan Project of Shandong Province,PRC(No.2016GSF115018)
文摘This paper proposes an optimized and coordinated model predictive control(MPC) scheme for doublyfed induction generators(DFIGs) with DC-based converter system to improve the efficiency and dynamic performance in DC grids. In this configuration, the stator and rotor of the DFIG are connected to the DC bus via voltage source converters, namely, a rotor side converter(RSC) and a stator side converter(SSC). Optimized trajectories for rotorflux and stator current are proposed to minimize Joule losses of the DFIG, which is particularly advantageous at low and moderate torque. The coordinated MPC scheme is applied to overcome the weaknesses of the field-oriented control technique in the rotor flux-oriented frame, which makes the rotor flux stable and the stator current track its reference closely and quickly. Lastly, simulations and experiments are carried out to validate the feasibility of the control scheme and to analyze the steady-state and dynamic performance of the DFIG.
基金supported by Beijing Municipal Science Technology commission research(No.Z171100000317003)
文摘First, a three-tier coordinated scheduling system consisting of a distribution network dispatch layer, a microgrid centralized control layer, and local control layer in the energy internet is proposed. The multi-time scale optimal scheduling of the microgrid based on Model Predictive Control（MPC） is then studied, and the optimized genetic algorithm and the microgrid multi-time rolling optimization strategy are used to optimize the datahead scheduling phase and the intra-day optimization phase. Next, based on the three-tier coordinated scheduling architecture, the operation loss model of the distribution network is solved using the improved branch current forward-generation method and the genetic algorithm. The optimal scheduling of the distribution network layer is then completed. Finally, the simulation examples are used to compare and verify the validity of the method.
