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相关概念视频

Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

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On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
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The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

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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...
212
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

191
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:
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Calculation of Electric Flux01:25

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Consider the electric field of an oppositely charged, parallel-plate system and an imaginary box between those plates. Let the bottom face of the box be ABCD, and the top face be FGHK. The electric field between the plates is uniform and points from the positive plate toward the negative plate. The calculation of this field's flux through the box's various faces shows that the net flux through the box is zero. Why does the flux cancel out here?
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Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

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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.
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一个有效的基于数据表的太阳能光伏的参数估计技术.

K M Charu1,2, Padmanabh Thakur1, Nikita Rawat1

  • 1Department of Electrical Engineering, Graphic Era (Deemed to be University), Dehradun, 248002, Uttarakhand, India.

Scientific reports
|March 19, 2024
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种高效的太阳能光伏 (PV) 参数估计技术,使用制造商数据表. 使用粒子优化 (PSO) 开发的方法提供了精确而快速的光伏模型参数估计.

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科学领域:

  • 可再生能源可再生能源是可再生能源.
  • 电气工程 电气工程
  • 计算方法 计算方法

背景情况:

  • 精确的太阳能光伏 (PV) 模型参数估计对于性能分析和电网集成至关重要.
  • 现有的方法往往需要大量的数据或复杂的程序,这限制了它们的实际应用.

研究的目的:

  • 为太阳能光伏模型开发一种高效和精确的参数估计技术,仅使用制造商数据表信息.
  • 为了比较粒子集群优化 (PSO) 和和搜索 (HS) 对这个参数估计任务的性能.

主要方法:

  • 使用制造商数据表变量制定了一个非线性最小平方目标函数.
  • 应用了粒子集群优化 (PSO) 和和搜索 (HS) 算法来优化目标函数.
  • 性能指数,包括百分比最大功率偏差指数 (%MPDI) 和整体模型偏差指数 (OMDI),用于评估.

主要成果:

  • 使用PSO开发的技术在HS上表现出优异的性能,MPDI的%达到0.0214%,OMDI为0.213.
  • 对比分析显示,基于公共服务的方法比现有方法产生了较小的MPDI (0.0041%) 和OMDI (0.005%).
  • 该技术表现出快速收,仅在5秒内完成估计,并且需要最小的数据.

结论:

  • 拟议的参数估计技术,利用制造商数据表和PSO,是非常高效,准确和快速的.
  • 这种数据效率高的方法简化了获得精确太阳能光伏模型参数的过程,提高了它们的实际实用性.