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相关概念视频

Open and closed-loop control systems01:17

Open and closed-loop control systems

746
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
746
Load-frequency control01:28

Load-frequency control

165
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
165
Multimachine Stability01:25

Multimachine Stability

158
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
158
Feedback control systems01:26

Feedback control systems

314
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
314
Control of Power Flow01:30

Control of Power Flow

269
There are several methods to control power flow in power systems:
269
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

192
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:
192

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相关实验视频

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一个有效的基于多个模型的非线性控制USC发电厂.

Chuanliang Cheng1, Chen Peng1, Xiangpeng Xie2

  • 1School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 201900, China.

ISA transactions
|February 4, 2024
PubMed
概括

本研究引入了一种用于超超临界 (USC) 发电厂的新型非线性控制方法. 综合方法提高了能源效率,确保快速和稳定的运行,即使在显著的负载变化.

关键词:
一般化的预测控制.人类学习优化算法内部模型控制的内部模型控制.长期短期记忆神经网络的神经网络超超临界单位是超超临界单位.

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科学领域:

  • 发电工程 发电工程 发电工程
  • 控制系统理论 控制系统理论
  • 人工智能在能源中的作用

背景情况:

  • 超超临界 (USC) 炉轮机组对于高效的发电非常重要.
  • 非线性和缓慢的动态响应是USC单元控制的重大挑战.
  • 优化USC单位的能源效率是电力行业的一个关键问题.

研究的目的:

  • 为USC炉轮机单元开发一个强大的非线性控制方法.
  • 解决USC系统中非线性和缓慢动态的挑战.
  • 提高发电厂的能源效率和运行稳定性.

主要方法:

  • 将内部模型控制 (IMC) 和通用预测控制 (GPC) 整合到一个统一的非线性控制框架中.
  • 使用长短期记忆 (LSTM) 神经网络来改善IMC组件的响应速度.
  • 在非线性GPC组件中使用复合加权人类学习优化 (CWHLO) 网络来实现高精度跟踪.

主要成果:

  • 基于LSTM的IMC显示了对设定点的快速趋同,显著提高了系统响应速度.
  • CWHLO-GPC实现了高精度的跟踪性能.
  • 在1000MW的USC发电厂进行的模拟证实了该方法在巨大的负载变化下提供快速和稳定的动态响应的能力.

结论:

  • 拟议的综合IMC-GPC非线性控制方法有效优化USC炉轮机单元的能源效率.
  • 这种新的方法成功地减轻了非线性和缓慢的动态,从而提高了运营性能.
  • 这种控制策略为提高大规模发电系统的稳定性和效率提供了一个有希望的解决方案.