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相关概念视频

Load-frequency control01:28

Load-frequency control

620
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...
620
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

589
The maximum power flow for lossy transmission lines is derived using ABCD parameters in phasor form. These parameters create a matrix relationship between the sending-end and receiving-end voltages and currents, allowing the determination of the receiving-end current. This relationship facilitates calculating the complex power delivered to the receiving end, from which real and reactive power components are derived.
589
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

726
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:
726
Turbine-Governor Control01:17

Turbine-Governor Control

929
Turbine-governor control is crucial for maintaining power system stability by balancing turbine mechanical power output with electrical load demand. This mechanism ensures that generator frequency and rotor speed are within acceptable limits during load variations. Turbine-generator units store kinetic energy due to their rotating masses; this energy is released to meet the load requirement when the load increases. The electrical torque of turbines rises to meet the demand, whereas the...
929
Generator Voltage Control01:21

Generator Voltage Control

626
Generator voltage control is crucial for maintaining the stable operation of synchronous generators and wind turbines. In older models, a DC generator driven by the rotor delivers DC power to the rotor's field winding, and the power is transferred through slip rings and brushes. In the latest models, static or brushless exciters are used. Static exciters rectify AC power from the generator terminals and then transfer the DC power directly to the rotor. Brushless exciters, on the other hand, use...
626
Power Factor Correction01:20

Power Factor Correction

483
The power transmission to a factory involves the transfer of apparent power, a combination of active and reactive power. The power factor measures how effectively electrical power is converted into useful work output. The ratio of the real power (KW) that does the work to the apparent power (KVA) supplied to the circuit.
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Updated: Jan 15, 2026

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通过基于Fick定律的需求优化来改善自主微电网中的负载频率控制.

Maloth Ramesh1, Anil Kumar Yadav2, Pawan Kumar Pathak3

  • 1Department of Electrical Engineering, Marwadi University, Rajkot, Gujarat, 360 003, India.

Scientific reports
|October 15, 2025
PubMed
概括

一个新的需求贡献负载频率控制 (LFC) 策略使用Fick's Law Optimization (FLO) 增强的PI-(1+DF) 控制器稳定了太阳能-风能自主微电网. 这种方法有效地管理复杂的动态和不确定性,以提高电网性能.

关键词:
需求贡献是对需求的贡献.菲克定律的优化法则.微电网系统是一个微电网系统.最佳负载频率控制的最佳负载频率控制PI-(1 + DF) 的控制器控制器.太阳能-风能系统的能源系统

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科学领域:

  • 电气工程 电气工程
  • 控制系统 控制系统
  • 可再生能源系统可再生能源系统

背景情况:

  • 集成太阳能和风能的自主微电网系统 (AMGS) 面临由于间歇性发电和复杂动态的频率稳定挑战.
  • 传统控制器在AMGS中扎着不确定性和非线性,比如总督死带 (GDB) 和生成速率约束 (GRC).
  • 需求侧资源,包括电动汽车 (EV),热 (HP) 和冷,为增强电网控制提供了潜力,但需要复杂的管理.

研究的目的:

  • 提出一种新的需求贡献负载频率控制 (LFC) 策略,用于基于太阳能风的AMGS的频率稳定.
  • 开发和优化一个PI-(1+DF) 控制器,使用菲克定律优化 (FLO) 的元启发技术.
  • 在现实的操作条件和参数不确定性下,根据最先进的算法评估控制器的性能.

主要方法:

  • 采用结构增强的比例整数控制器与一加衍生过器 (PI-(1+DF)) 的实现.
  • 控制器参数的优化使用受物理启发的Fick's Law Optimization (FLO) 的元启发算法.
  • 将可再生能源 (太阳能,风能),柴油发动机发电机 (DEG) 和灵活的需求侧贡献者以及非线性 (GDB,GRC) 纳入AMGS的建模.

主要成果:

  • 在结算时间和峰值超越方面,FLO优化的PI-(1+DF) 控制器显著超过现有算法 (MBA,SCA).
  • 在MATLAB/Simulink中的模拟显示了控制器在严重干扰期间在可接受的范围内保持频率偏差的有效性.
  • 用±50%的参数变化进行的强度测试证实了控制器的弹性,显示了最小的峰值超射 (例如0.02 Hz) 和低射 (例如-0.957 Hz).

结论:

  • 拟议的需求贡献的LFC策略,由FLO优化,为太阳能风AMGS提供了卓越的频率稳定.
  • PI-(1+DF) 控制器在具有显著参数变化的不确定的环境中表现出强大的性能和适应性.
  • 这种方法为增强可再生能源微电网的稳定性和可靠性提供了实用和有效的解决方案.