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相关概念视频

Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

187
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:
187
The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

203
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...
203
Control of Power Flow01:30

Control of Power Flow

265
There are several methods to control power flow in power systems:
265
Load-frequency control01:28

Load-frequency control

157
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...
157
Multimachine Stability01:25

Multimachine Stability

151
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:
151
Power System Distribution01:25

Power System Distribution

235
Power system distribution involves delivering electrical energy from power plants to consumers through a network of transmission and distribution systems. The process begins at power plants, where energy from coal, gas, nuclear, water, and wind is converted into electrical energy. These plants use three-phase generators, typically rated between 50 to 1300 MVA, with terminal voltages ranging from a few kV to 20 kV, depending on the size and age of the units.
The transmission system is designed...
235

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相关实验视频

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模糊的分析层次为相互连接的电力系统基于过程的发电管理.

T Varshney1, A V Waghmare2, V P Singh2

  • 1Department of EECE, SSET, Sharda University, Greater Noida, Uttar Pradesh, 201310, India.

Scientific reports
|May 20, 2024
PubMed
概括

本研究介绍了一种模糊分析层次过程 (FAHP),以优化双区域电力系统中的自动发电控制 (AGC). 该方法有效地权衡子目标函数,以提高PID控制器的性能.

关键词:
在 AGC 中,AGC 是一个非常重要的组织.在 AHP AHP 中.模糊的 AHP 的 AHP.贾雅优化算法Jaya优化算法在PID控制器控制器中,PID控制器控制器电力系统 电力系统

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科学领域:

  • 电气工程 电气工程
  • 控制系统 控制系统
  • 优化技术 优化技术

背景情况:

  • 决策涉及复杂的属性评估和权重确定.
  • 在双区域电力系统 (2-APS) 中的自动发电控制 (AGC) 需要平衡多个目标.
  • 现有的方法可能无法充分处理AGC优化的多属性性质.

研究的目的:

  • 提出一个模糊的分析层次流程 (FAHP) 来确定AGC中子目标函数的权重.
  • 设计一个使用这些权重进行优化的比例-整数-导数 (PID) 控制器.
  • 评估与其他优化算法对比拟控制器的性能.

主要方法:

  • 利用FAHP,一种多属性决策 (MADM) 技术,对连接线功率波动,频率偏差和区域控制错误的积分时间绝对误差 (ITAE) 赋值权重.
  • 将FAHP衍生权重集成到用于PID控制器设计的单一目标功能中.
  • 采用了Jaya优化算法 (JOA) 来优化目标函数,并将其与Sine Cosine算法 (SCA),Luus-Jaakola算法 (LJA),Nelder-Mead简单算法 (NMSA),共生生物搜索算法 (SOSA) 和大象群群优化算法 (EHOA) 进行比较.

主要成果:

  • 基于Jaya优化算法 (JOA) 的PID控制器在各种负载条件下在自动发电控制中表现出有效的性能.
  • 实验数据和统计分析,包括弗里德曼等级测试,验证了基于JOA的控制器的优越性.
  • FAHP方法成功地将多个性能标准集成到一个单一的目标功能中,以优化控制器.

结论:

  • 提出的基于FAHP的方法为优化2-APS的AGC提供了一个有效的框架.
  • JOA是一个强大的优化算法,用于调整电源系统中的PID控制器.
  • 这项研究为电力系统稳定性和控制领域做出了宝贵的贡献.