11.3 Multi-swing stability and long-term dynamics

Multi-swing instability in power systems can lead to catastrophic failures. It's characterized by growing oscillations in generator rotor angles after severe disturbances. Understanding this phenomenon is crucial for maintaining grid stability and preventing widespread blackouts.

Long-term dynamics play a key role in assessing multi-swing instability. Time-domain simulations help engineers analyze system behavior over extended periods, considering factors like generator control systems, load characteristics, and network topology. This knowledge enables better mitigation strategies and system design.

Multi-swing instability in power systems

Characteristics and occurrence of multi-swing instability

• Multi-swing instability is a type of power system instability characterized by oscillations of generator rotor angles that increase in magnitude over time, potentially leading to loss of synchronism
• Occurs when the power system is subjected to severe disturbances (faults, line tripping, or sudden load changes) and the system's damping is insufficient to suppress the resulting oscillations
• Influenced by various factors (generator inertia, excitation systems, power system stabilizers (PSS), and the strength of the transmission network)

Impact of multi-swing instability on long-term dynamics

• Sustained oscillations in generator rotor angles, power flows, and bus voltages
• Increased risk of cascading outages and blackouts due to the propagation of instability
• Difficulty in restoring the system to a stable operating point after the disturbance
• Requires detailed modeling and time-domain simulations to assess the long-term impact on system stability

Factors contributing to multi-swing instability

Generator control systems

• Generator excitation systems play a crucial role in multi-swing instability
  • High-gain automatic voltage regulators (AVRs) can improve transient stability but may lead to undamped oscillations and multi-swing instability if not properly tuned
  • Power system stabilizers (PSS) provide supplementary damping control to the excitation system, helping to mitigate multi-swing instability
• Governor control systems and prime mover characteristics influence multi-swing instability
  • Slow response of governors and prime movers can exacerbate oscillations and contribute to multi-swing instability
  • Steam turbine generators with large time constants and long boiler dynamics are more susceptible compared to fast-responding gas turbines or hydro units

Load characteristics and transmission network

• Load characteristics impact multi-swing instability
  • Constant power loads (induction motors or power electronic converters) can reduce the damping of power system oscillations and increase the risk of multi-swing instability
  • Voltage-dependent loads (lighting and heating loads) can provide a stabilizing effect by reducing their power consumption during voltage dips associated with oscillations
• Transmission network characteristics (line impedances, reactive power compensation, and FACTS devices) can influence the propagation and damping of multi-swing oscillations
• Strength of the transmission network, determined by factors such as line impedances and power transfer capabilities, affects the system's ability to withstand disturbances and maintain stability

Long-term dynamic behavior of power systems

Time-domain simulation for long-term dynamics

• Time-domain simulations analyze the long-term dynamic behavior of power systems, capturing the evolution of system variables over an extended period (typically several seconds to minutes)
• Require detailed models of generators, excitation systems, governors, prime movers, and loads to accurately represent the system's response to disturbances
• Key variables to monitor include generator rotor angles and speeds, bus voltages and frequency, active and reactive power flows, and status of protective relays and control actions

Interpreting simulation results and sensitivity analysis

• Interpreting long-term dynamic simulation results involves:
  • Identifying the onset and propagation of multi-swing instability
  • Assessing the effectiveness of control actions and protective schemes in mitigating instability
  • Evaluating the impact of instability on system voltages, frequency, and power flows
  • Determining the critical clearing time for faults and the stability margin of the system
• Sensitivity analysis using time-domain simulations identifies the critical parameters and operating conditions that influence multi-swing instability
• Helps prioritize mitigation strategies and optimize system design for long-term stability

Mitigation strategies for multi-swing instability

Generator control and transmission network reinforcement

• Proper tuning of generator excitation systems and power system stabilizers (PSS) is essential
  • Optimize AVR gains and time constants to provide adequate voltage regulation while maintaining system stability
  • Design and tune PSS to provide supplementary damping control over a wide range of operating conditions
• Implement fast-acting governor control systems and prime movers (gas turbines or energy storage systems) to improve the system's response to disturbances and reduce the risk of multi-swing instability
• Strengthen the transmission network to reduce the impedance between generators and loads, enhancing the system's ability to transfer power and damp oscillations
  • Upgrade transmission lines and transformers to increase their capacity and reduce their impedance
  • Install series capacitors or FACTS devices to improve power flow control and damping of oscillations

System protection and monitoring

• Employ load shedding schemes to disconnect non-critical loads during severe disturbances, reducing the stress on the system and preventing the propagation of instability
• Coordinate protective relays and control actions to ensure selective and timely isolation of faulted elements while maintaining the integrity of the remaining system
• Regularly monitor and assess the long-term stability of the power system using time-domain simulations and stability indices
  • Identify potential vulnerabilities and implement preventive measures
  • Update system models and parameters to reflect changes in the network and operating conditions