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相关概念视频

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
The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

213
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...
213
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

111
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.
111
Multimachine Stability01:25

Multimachine Stability

153
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:
153
Control of Power Flow01:30

Control of Power Flow

269
There are several methods to control power flow in power systems:
269
Maximum Power Transfer01:16

Maximum Power Transfer

258
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...
258

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相关实验视频

Updated: Jul 1, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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使用增强的多目标Mayfly算法实现最佳的随机动力流.

Jianjun Zhu1, Yongquan Zhou1,2,3,4, Yuanfei Wei2,3

  • 1College of Artificial Intelligence, Guangxi University for Nationalities, Nanning, 530006, China.

Heliyon
|March 4, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种增强的多目标Mayfly算法 (NSMA-SF),以优化风能和太阳能等可再生能源的电力流量. 新方法有效地应对了将这些可变源整合到电力系统中的挑战.

关键词:
这是一种元启发式 (metaheuristic) 启发式.多目标的可能飞算法算法.可再生能源是可再生的能源.随机动力流的动力流量 随机动力流的动力流.

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科学领域:

  • 电气工程 电气工程
  • 优化理论 优化理论
  • 可再生能源系统可再生能源系统

背景情况:

  • 经典的多目标最佳功率流 (MOOPF) 传统上使用热发电机.
  • 对可再生能源的日益增长的需求需要MOOPF的解决方案,包括风能和太阳能光伏 (PV).
  • 预测间歇性可再生电力是一个重大挑战.

研究的目的:

  • 为了解决MOOPF的问题,集成风能和太阳能能源.
  • 开发一个强大的算法,能够处理可再生能源整合的复杂性.
  • 优化多个目标,包括燃料成本,排放,功率损失和电压偏差.

主要方法:

  • 威布尔概率分布函数 (PDF) 用于风力预测的应用.
  • 使用lognormal PDF进行太阳能可用性评估.
  • 实施一个增强的多目标Mayfly算法 (NSMA-SF),利用非主导排序和可行解决方案的优越性.

主要成果:

  • 该NSMA-SF算法已成功应用于修改的IEEE-30和标准IEEE-57总线测试系统.
  • 模拟结果表明该算法在解决可再生能源的MOOPF问题上的有效性.
  • 分析了性能,并与现有的MOOPF方法进行了比较.

结论:

  • 拟议的NSMA-SF算法提供了一种有效的方法,用于多目标的最佳功率流与风能和太阳能集成.
  • 该研究强调了准确的可再生电力预测对电网稳定的重要性.
  • 这些发现有助于推进智能电网技术和可再生能源管理.