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相关概念视频

The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

803
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...
803
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

724
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:
724
Load-frequency control01:28

Load-frequency control

608
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...
608
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

581
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.
581
Power Factor Correction01:20

Power Factor Correction

477
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.
477
Control of Power Flow01:30

Control of Power Flow

665
There are several methods to control power flow in power systems:
665

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相关实验视频

Updated: Jan 12, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
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一个修改的加权平均算法,用于最佳的反应功率调度,考虑到不确定的负载和可再生电力.

Sulaiman Z Almutairi1, Mohamed Ebeed2, Ahmed T Hachemi3

  • 1Department of Electrical Engineering, College of Engineering, Prince Sattam Bin Abdulaziz University, Al Kharj, 16278, Saudi Arabia. s.almutairi@psau.edu.sa.

Scientific reports
|November 5, 2025
PubMed
概括
此摘要是机器生成的。

一个新的修改后加权平均算法 (MWAA) 有效地解决了最佳反应功率调度 (ORPD) 和随机ORPD (SORPD) 问题. 它通过优化可再生能源集成的反应电源流量来提高电力系统性能.

关键词:
在ORPD解决方案流程过程中.可再生能源是可再生的能源.统计分析 统计分析不确定性 不确定性权重平均算法算法 权重平均算法

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科学领域:

  • 电气工程 电气工程
  • 电力系统优化 电力系统优化
  • 计算智能是一种计算智能.

背景情况:

  • 最佳反应功率调度 (ORPD) 对于现代电力系统的效率至关重要.
  • 整合光伏 (PV) 和风力轮机 (WTs) 等可再生能源引入了不确定性.
  • 随机ORPD (SORPD) 解决了这些不确定性,以保持系统的稳定性和性能.

研究的目的:

  • 为解决ORPD和SORPD提出一个修改的加权平均算法 (MWAA).
  • 将MWAA应用于30总线IEEE系统,考虑PV和WT集成.
  • 为了最大限度地减少SORPD中预期的总功率损失 (TEPL) 和预期的总电压偏差 (TEVD).

主要方法:

  • 开发了MWAA,结合了健身距离平衡 (FDB),维布尔飞行和准对立式学习 (QOBL).
  • 在负载需求和可再生能源发电中的模拟不确定性使用正常/逻辑正常和韦布尔概率密度函数 (PDF).
  • 在标准基准函数和CEC-2019测试套件上验证了MWAA性能.

主要成果:

  • MWAA展示了强大的和具有竞争力的优化能力.
  • 该算法有效地解决了30总线IEEE系统上的ORPD和SORPD问题.
  • 对比分析显示,在准确性和收性方面,比现有最先进的方法表现优越.

结论:

  • 拟议的MWAA是一种高度有效的技术,用于在不确定性条件下实现最佳反应功率调度.
  • MWAA成功地整合了可再生能源,同时最大限度地减少了功耗损失和电压偏差.
  • 该算法为提高现代动力系统的性能和可靠性提供了重大进步.