Wind Power Integration into Power Systems: Stability and Control Aspects

Power network operators are rapidly incorporating wind power generation into their power grids to meet the widely accepted carbon neutrality targets and facilitate the transition from conventional fossil-fuel energy sources to clean and low-carbon renewable energy sources. Complex stability issues, such as frequency, voltage, and oscillatory instability, are frequently reported in the power grids of many countries and regions (e.g., Germany, Denmark, Ireland, and South Australia) due to the substantially increased wind power generation. Control techniques, such as virtual/emulated inertia and damping controls, could be developed to address these stability issues, and additional devices, such as energy storage systems, can also be deployed to mitigate the adverse impact of high wind power generation on various system stability problems. Moreover, other wind power integration aspects, such as capacity planning and the short- and long-term forecasting of wind power generation, also require careful attention to ensure grid security and reliability. This book includes fourteen novel research articles published in this Energies Special Issue on Wind Power Integration into Power Systems: Stability and Control Aspects, with topics ranging from stability and control to system capacity planning and forecasting

Impact of Wind Generators in Power System Stability

Wind electricity is one of the quickest developing renewable resources of power. This rapid development is expected considering the environmental factors, but in terms of power system stability, it comes with a number of concerns. Generators play a vital role on stability for a particular capacity and design of a network. This paper investigated the overall performance of 3 foremost types of wind turbines via small signal stability analysis on IEEE 9 bus system. Simulations have been done and established that the generators dynamic model have significant impact on power system stability at different capacity of the generators

REVIEW ON SUB-SYNCHRONOUS OSCILLATIONS IN WIND FARMS: ANALYSIS METHOD, STUDY SYSTEM, AND DAMPING CONTROL

More and more attention on wind farm sub-synchronous oscillation (SSO) has been paid as many SSO incidents in wind farms have occurred. This paper presents an overview of recent SSO issues in wind farm from the perspective of control, including the analysis methods, the study system, and the SSO mitigation by damping control. Three major analysis methods, as well as different study systems for wind farm SSO study, are comprehensively reviewed. The adaptability and complexity of the methods and study systems are analysed, and an overall survey of recent SSO analysis is given. Among the wind farm SSO mitigation methods, the sub-synchronous damping controller (SSDC) is one of the most commonly used methods in practice. Its configuration and signal selection are introduced in this paper

Design and Control of Virtual Synchronous Machine Based Energy Systems

Conventionally, the operation and stability of power systems have been governed by the dynamics of large synchronous generators (SGs) which provide the inertial support required to maintain the resilience and stability of the power system. How-ever, the commitment of the UK to drive a zero-carbon economy is accelerating the integration of renewable energy sources (RESs) into the power system. Since the dynamics and operation of RESs differs from SGs, the large-scale integration of RESs will significantly impact the control and stability of the power system.This thesis focuses on the design of grid-friendly control algorithms termed virtual synchronous machines (VSMs), which mimic the desirable characteristics of SGs. Although several VSM topologies have been proposed in literature, most of them require further modifications before they can be integrated into the grid. Hence, a novel VSM algorithm for permanent magnet synchronous generator based wind turbines has been proposed in this thesis.The proposed VSM performs seamlessly in all operating modes and enables maxi-mum power point tracking in grid-connected operation (assuming strong grid), load following power generation in islanded mode and fault ride-through during faults. To ensure optimal performance of the VSM in all operating modes, a comprehensive stability analysis of the VSM was performed in the event of small and large per-turbations. The result of the analysis was used to establish design guidelines and operational limits of the VSM.This thesis further evaluates the impact of VSMs on the power systems low-frequency oscillations (LFOs). A detailed two-machine test-bed was developed to analyze the LFOs which exists when VSMs replace SGs. The characteristics of the LFO modes and the dominant states was comprehensively analyzed. The LFO modes which exists in an all-VSM grid was also analyzed. Further, the role of the power system stabilizers in an all-VSM grid was comprehensively evaluated. An IEEE benchmark two-area four-machine system was employed to validate the results of the small-signal analysis.The analysis and time-domain simulations in this thesis were performed in the MAT-LAB/SIMULINK environment

AN ADVANCED CONTROL OF GRID CONNECTED WIND TURBINE GENERATORS FOR ENHANCEMENT OF LOW-VOLTAGE RIDE-THROUGH CAPABILITY

Tohoku University斎藤浩海課

THE STABILITY ANALYSIS FOR WIND TURBINES WITH DOUBLY FED INDUCTION GENERATORS

The quickly increasing, widespread use of wind generation around the world reduces carbon emissions, decreases the effects of global warming, and lowers dependence on fossil fuels. However, the growing penetration of wind power requires more effort to maintain power systems stability. This dissertation focuses on developing a novel algorithm which dynamically optimizes the proportional-integral (PI) controllers of a doubly fed induction generator (DFIG) driven by a wind turbine to increase the transient performance based on small signal stability analysis. Firstly, the impact of wind generation is introduced. The stability of power systems with wind generation is described, including the different wind generator technologies, and the challenges in high wind penetration conditions. Secondly, the small signal stability analysis model of wind turbines with DFIG is developed, including detailed rotor/grid side converter models, and the interface with the power grid. Thirdly, Particle swarm optimization (PSO) is selected to off-line calculate the optimal parameters of DFIG PI gains to maximize the damping ratios of system eigenvalues in different wind speeds. Based on the historical data, the artificial neural networks (ANNs) are designed, trained, and have the ability to quickly forecast the optimal parameters. The ANN controllers are designed to dynamically adjust PI gains online. Finally, system studies have been provided for a single machine connected to an infinite bus system (SMIB), a single machine connected to a weak grid (SMWG), and a multi machine system (MMS), respectively. A detailed analysis for MMS with different wind penetration levels has been shown according to grid code. Moreover, voltage stability improvement and grid loss reduction in IEEE 34-bus distribution system, including WT-DFIG under unbalanced heavy loading conditions, are investigated. The simulation results show the algorithm can greatly reduce low frequency oscillations and improve transient performance of DFIGs system. It realizes off-line optimization of MMS, online forecasts the optimal PI gains, and adaptively adjusts PI gains. The results also provide some useful conclusions and explorations for wind generation design, operations, and connection to the power grid. Advisors: Sohrab Asgarpoor and Wei Qia