Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

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
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

582
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.
582
The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

829
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...
829
Maximum Power Transfer01:16

Maximum Power Transfer

814
Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...
814
Conservation of AC Power01:15

Conservation of AC Power

648
The principle of power preservation is applicable to both ac and dc circuits. This principle, when applied to AC power, asserts that the complex, real, and reactive powers produced by the source are equal to the total complex, real, and reactive powers absorbed by the loads. When two load impedances are connected in parallel to an ac source V, the complex power provided by the source can be calculated using the relation
648
Control of Power Flow01:30

Control of Power Flow

667
There are several methods to control power flow in power systems:
667

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Hybrid deep learning model for multimodal vocal and lung signal analysis in health monitoring.

Scientific reports·2026
Same author

Correction: Performance improvement of DC motor control system using PID controller with Kookaburra and Red Panda optimization algorithm.

Scientific reports·2026
Same author

Analysis and Optimization of Secure Sliding Mode Observer-Based Control in Nonlinear Descriptor Systems Under Attacks.

IEEE transactions on cybernetics·2026
Same author

Hybrid attention based deep learning for forecasting boundary layer ozone using satellite derived profiles.

Ecotoxicology and environmental safety·2025
Same author

Improved fault-clearing strategy for large renewable energy systems using advanced optimization and FLC.

Scientific reports·2025
Same author

Finite-time event-triggered sliding mode control for fuzzy singular systems under cyber-attacks.

ISA transactions·2025

相关实验视频

Updated: Jan 13, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.4K

通过灰狼优化器使用Cuckoo优化算法,用于工程优化和可再生能源最佳功率流.

Rabeh Abbassi1, Pavel Trojovský2, Zulkefli Mansor3

  • 1Department of Electrical Engineering, College of Engineering, University of Ha'il, 81451, Hail, Saudi Arabia. r.abbassi@uoh.edu.sa.

Scientific reports
|October 29, 2025
PubMed
概括

一个新的混合元启发方法,COGWO,通过集成灰狼优化器 (GWO) 和古柯优化算法 (COA) 来增强电力系统优化. 这种方法提高了电力分配管理的弹性和效率,特别是在可再生能源方面.

关键词:
这就是COGWOWO.子优化算法 子优化算法工程优化优化工程优化灰狼优化器 灰狼优化器多目标的OPF多目标的OPF.可再生能源 (RES) 是一种可再生能源.

更多相关视频

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

2.1K
Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations
14:33

Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations

Published on: October 1, 2013

14.8K

相关实验视频

Last Updated: Jan 13, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
11:53

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

13.4K
Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

2.1K
Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations
14:33

Optimize Flue Gas Settings to Promote Microalgae Growth in Photobioreactors via Computer Simulations

Published on: October 1, 2013

14.8K

科学领域:

  • 电气工程 电气工程
  • 计算智能是一种计算智能.
  • 优化技术 优化技术

背景情况:

  • 最佳功率流 (OPF) 对于高效的电力分配管理至关重要.
  • 现有的优化技术面临复杂的电力系统和可再生能源整合的挑战.
  • 现代电网需要有弹性和高效的优化方法.

研究的目的:

  • 引入COGWO,一种混合的元启发方法,将GWO和COA结合起来,用于增强的OPF解决方案.
  • 根据标准工程问题和最先进的方法验证COGWO的性能.
  • 将COGWO应用于波动可再生能源的大型电力系统中的OPF问题.

主要方法:

  • 通过集成 Grey Wolf Optimizer (GWO) 和 Cuckoo 优化算法 (COA) 开发了 COGWO.
  • 在CEC2020基准问题上验证了COGWO,证明了卓越的性能.
  • 将COGWO应用于IEEE 30公交和118公交系统,考虑到可再生能源 (RES) 的波动.

主要成果:

  • 与GWO,COA和其他metaheuristics相比,COGWO实现了优越的融合质量和解决方案弹性.
  • 该方法有效地降低了燃料成本,功率损失,电压变化和排放.
  • 对于非凸和非光滑的优化函数,COGWO证明了勘探和利用之间的最佳平衡.

结论:

  • 对于大规模的电力系统优化,COGWO提供了一种计算效率高,灵活且有弹性的解决方案.
  • 混合方法显著提高了OPF的解决方案稳定性和融合速度.
  • COGWO是一种有前途的技术,用于管理集成可再生能源的现代电网.