Fast frequency control in low inertia electrical power systems using doubly fed induction generator

Abstract

Increased penetration of renewable energy sources in modern electrical power systems is contributing to a reduction in carbon emissions, thereby reducing the level of air pollution, climate change and finally supporting the quality of life on the Earth. In this context, energy conversion systems realised using wind turbine generators have been and are still the focus of extensive research on different system aspects, from planning, exploitation, monitoring, control and protection perspectives. However, connecting modern wind turbine generators to the main grid over converters can cause a number of consequences. One of them is reduction of system inertia. The reduction of system inertia imposes serious technical challenges in preserving system frequency stability. As it is known, inertia is one of the key factors determining the robustness of power systems against sudden active power imbalances caused by different types of frequency events. A reduction in synchronous power reserves further intensifies this problem by reducing the system ability to maintain the frequency within a permissible range following frequency events. Considering the effects of the integration of WECSs, enhancing the frequency support capability of wind turbines by emulating the behaviour of synchronous generators to some extent and participating in (fast) frequency control is needed. Wind turbines usually operate at the maximum power point tracking curve, and their active power can be temporarily increased by using synthetic inertia control for supporting system frequency. However, the support period cannot last long because the rotor speed of wind turbine will decrease to its minimum, which tiggers the rotor protection. In this context, the output of wind turbines reduces. Hence, another imbalance between generation and consumption occurs leading a secondary frequency dip. Sometimes, the magnitude of secondary frequency dip is even lower than the first frequency nadir caused by a frequency event. Motivated by solving the problem, this thesis is investigated from the perspectives of enhancing the power system frequency stability, improving the magnitude of secondary frequency dips, maintaining the DFIGs stable operation and increasing the annual profit of wind farms. Two novel controls are discussed at wind turbine level and wind farm level, respectively. The first control presented in this thesis is to design a novel frequency control for wind turbines that provides fast frequency support. A novel frequency control called dynamic-droop based control is proposed, which utilise as much as possible the available energy from wind turbines in a wind farm and at the same time to provide a smart, fast and reliable primary frequency response without imposing adverse impacts on the power system. The mitigation of secondary frequency dip can be achieved by employing a droop control based on the information of rate of change of frequency. In this way, the magnitude of power reduction brough by the termination of temporary energy reserves can be reduced, which results in a smaller secondary frequency dip and a more gradual power transition. Secondly, another novel frequency control scheme that consecutively utilises wind turbines working under various operating conditions is proposed. This control is proposed based on employing temporary and persistent energy reserve-based approaches, which enhances the frequency response in power systems with high penetration of converter interfaced generation. Also, it improves the frequency nadir, mitigates the secondary frequency dip, and prevent power systems from frequency collapse. In addition, this novel control also satisfies the anticipation of system operators based on functionality and economical requirements. In first two chapters, the introduction and a summary of power system stability are presented, which identifies the research direction of this thesis. In the chapter three and four, the created wind turbine models

Date of Award	1 Aug 2021
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Peter Crossley (Supervisor) & Victor Levi (Supervisor)