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Related Concept Videos

Types of Damping01:20

Types of Damping

If the amount of damping in a system is gradually increased, the period and frequency start to become affected because damping opposes, and hence slows, the back and forth motion (the net force is smaller in both directions). If there is a very large amount of damping, the system does not even oscillate; instead, it slowly moves toward equilibrium. In brief, an overdamped system moves slowly towards equilibrium, whereas an underdamped system moves quickly to equilibrium but will oscillate about...
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

Power flow problem analysis is fundamental for determining real and reactive power flows in network components, such as transmission lines, transformers, and loads. The power system's single-line diagram provides data on the bus, transmission line, and transformer. Each bus k in the system is characterized by four key variables: voltage magnitude Vk​, phase angle δk​, real power Pk​, and reactive power Qk​. Two of these four variables are inputs, while the power flow program computes the...
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
Damped Oscillations01:07

Damped Oscillations

In the real world, oscillations seldom follow true simple harmonic motion. A system that continues its motion indefinitely without losing its amplitude is termed undamped. However, friction of some sort usually dampens the motion, so it fades away or needs more force to continue. For example, a guitar string stops oscillating a few seconds after being plucked. Similarly, one must continually push a swing to keep a child swinging on a playground.
Although friction and other non-conservative...
Second Order systems II01:18

Second Order systems II

In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
If  ζ...

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Related Experiment Video

Updated: Jul 3, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

Direct heuristic dynamic programming for damping oscillations in a large power system.

Chao Lu1, Jennie Si, Xiaorong Xie

  • 1Department of Electrical Engineering, Tsinghua University, Beijing 100084, China. luchao@tsinghua.edu.cn

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
|July 18, 2008
PubMed
Summary

This study introduces direct heuristic dynamic programming (direct HDP) for power system stability control. This novel learning approach effectively manages network oscillations and enhances system stability under complex conditions.

Related Experiment Videos

Last Updated: Jul 3, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

Area of Science:

  • Electrical Engineering
  • Control Systems
  • Artificial Intelligence

Background:

  • Power systems face challenges with nonlinear coordinated control under uncertainty.
  • Low-frequency oscillations and coupling effects impact network stability.
  • Existing control methods may struggle with complex, large-scale power grids.

Purpose of the Study:

  • To apply a neural-network-based approximate dynamic programming method, direct heuristic dynamic programming (direct HDP), to large-scale power system stability control.
  • To formulate a controller learning objective function that addresses network-wide low-frequency oscillations considering nonlinearity, uncertainty, and coupling effects.
  • To develop and evaluate a novel learning control structure for power system applications.

Main Methods:

  • Implementation of direct heuristic dynamic programming (direct HDP), a learning and approximation-based approach.
  • Formulation of a controller learning objective function tailored for network-wide oscillation control.
  • Application and evaluation of the direct HDP in two distinct power system control scenarios.

Main Results:

  • A novel learning control structure based on direct HDP was developed.
  • The method demonstrated effective supplementary damping control for static var compensators.
  • A new solution was provided for large interconnected power network oscillation damping control, relevant to the China Southern Power Grid.

Conclusions:

  • Direct HDP offers a viable learning-based solution for complex power system stability control problems.
  • The proposed method effectively mitigates network-wide low-frequency oscillations.
  • The approach shows promise for enhancing the stability and control of large, interconnected power grids.