Nonlinear Adaptive Control of Doubly-fed Induction Generator for Variable Speed Wind Turbine

Doubly-fed induction generator wind turbines (DFIG-WTs) have been widely adopted by the current wind power generation systems (WPGSs) due to their cost-effective provision of a high efficiency energy conversion via variable speed operation. Most of the installed DFIG-WTs utilise vector control (VC) for the power control of DFIG. To cope with the increasing demand of integrating the large capacity of wind power into the current power grid, grid operators require that the WPGSs should ride through grid faults and support grid stability. However, VCs are not capable of providing satisfied fault ride-through capability as they are mainly derived based on the steady-state operation of the DFIG. On the other hand, the time-varying nonlinearities and disturbances existing in the DFIG-WTs are needed to be tackled so as to improve the energy conversion efficiency. This proposal will investigate an advanced nonlinear adaptive control algorithm for the DFIG-WT to improve the energy conversion efficiency, the fault-ride through capability and the support of grid stability. The proposed controller will adaptively compensate unknown and time-varying disturbances such as intermittent wind power inputs, the nonlinear dynamics of the DFIG-WT and the power grid. Without relying on an accurate system model, the developed controller will have a relative simpler control algorithm compared to other advanced control methods and can be implemented based on the current hardware used by the vector control method. Due to the wide usage of the DFIG-WTs in the current WPGSs and in the fast growing offshore wind farms, designing a novel controller and upgrading the current used VCs will have great practical importances and help the integration of large capacity of wind power into power grid.

To meet the EUs' 15% renewable energy target, the UK Government's Renewable Energy Strategy targets 30-40% of all UK energy coming from renewable sources by 2020. To achieve this target, mass-deployment of on shore and offshore wind farms will be required. Offshore wind farms have a huge potential to reduce carbon emissions, create economic prosperity and aid the shift to the Low Carbon economy, as well as increasing energy security of supply. The Government recently announced plans to open up the UK's seas to up to 33 GW of wind power capacity.

This project targets a better control system for wind turbines, specifically looking at Doubly Fed Induction Generator based Wind Turbines (DFIG-WTs), but the research outcomes can be applied across all wind turbines. DFIG-WTs are widely used in wind power generation because they can operate cost-effectively under variable speeds, and have high energy conversion efficiency and full controllability of active/reactive powers. However, the existing Vector Control algorithms cannot provide robust efficient energy conversion over the full range of operating points and satisfactory transient dynamic under grid faults, leading to reduced energy conversion efficiency and poor fault ride-through capability, which limit the penetration capability of large-scale wind power generation into the grid.

The novel nonlinear adaptive controllers developed in this project will benefit the wind power generation industry through increased the energy conversion efficiency and fault ride-though capability of wind turbines and reduced mechanical stresses of the drive train, leading to both reduced maintenance costs (particularly valuable to offshore wind farms installations where the maintenance is more difficult than the on-shore ones) and also to increase generation efficiency. These will reduce the cost of operation of wind turbines. The power grid operators and power distribution companies will be benefited through the increased reliability of wind power generation capability and improved resilience to grid faults, which will enable deeper penetration of wind generation capability into the power grid. Consumers in the UK and worldwide will be able to benefit because of the decreased cost and increased reliability of wind power generation, which will reduce the net cost to consumers of renewable energy (cost of electricity plus subsidies) and encourage the transition to low-carbon sources of energy.