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相关概念视频

Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

186
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.
186
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

303
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:
303
The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

348
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...
348
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

1.8K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.8K
Electrical Power01:07

Electrical Power

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Electric power is the product of current and voltage, represented in units of joules per second, or watts. For example, cars often have one or more auxiliary power outlets with which you can charge a cell phone or other electronic devices. These outlets may be rated at 20 amps and 12 volts, so that the circuit can deliver a maximum power of 240 watts. Consider a 25 Watt bulb and a 60 Watt bulb. The conversion of electrical energy produces heat and light, while the kinetic energy lost by the...
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Generation of Three-Phase Voltage01:21

Generation of Three-Phase Voltage

482
A three-phase AC generator has a rotor with a rotating magnet placed within the stator mounted with the stationary three-phase winding to generate three-phase voltages via mutual induction. These windings are evenly distributed around the inner circumference of the stator and are arranged 120 electrical degrees apart. Three-phase stator windings consist of three separate coils or groups of coils, known as phases, each connected in Y (star) configuration or Delta configuration.
As the rotor...
482

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相关实验视频

Updated: Sep 18, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
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一种基于遗传编程的组合方法,用于长期预测电力需求.

Hayat Ahmed Issa1, Hasan Hüseyin Çevik2, Ahmet Yilmaz3

  • 1Electrical & Electronics Engineering, Institute of Science, Selcuk University, Selcuklu, Konya, Türkiye.

PeerJ. Computer science
|June 26, 2025
PubMed
概括

这项研究提出了一种使用遗传编程预测埃塞俄比亚到2031年的电力消耗的新型组合方法. 该先进技术预计,到2031年,电力使用量将比2021年的水平增加三倍.

关键词:
整体方法组合方法.遗传算法 遗传算法 遗传算法这是基因编程.长期电力需求 长期电力需求粒子小群优化优化 粒子小群优化模拟的回火模拟

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科学领域:

  • 能源经济学 能源经济学
  • 计算智能是一种计算智能.
  • 预测科学 预测科学

背景情况:

  • 准确的长期电力消耗预测对于埃塞俄比亚的能源基础设施规划至关重要.
  • 现有的预测模型可能无法捕捉到埃塞俄比亚日益增长的能源需求的复杂动态.

研究的目的:

  • 开发和验证一种新的整体方法,用于长期预测埃塞俄比亚的电力消耗.
  • 预测到2031年的电力消费趋势.

主要方法:

  • 采用了两阶段的整体方法,将遗传算法 (GA),粒子群优化 (PSO) 和模拟化 (SA) 与回归模型 (线性,二次性,指数) 集成在一起.
  • 基因编程 (GP) 在第二阶段被用来改进初步预测,创建最终的预测模型.
  • 使用平均绝对百分比误差 (MAPE),平均平方误差 (MSE),根平均平方误差 (RMSE) 和R平方 (R2) 来评估性能.

主要成果:

  • 初步阶段取得了准确的预测,GA_Quadratic,PSO_Quadratic和SA_Quadratic的MAPE值分别为3.61%,3.63%和4.68%.
  • 基于遗传编程的最终组合模型实现了2.83%的优异MAPE.
  • 拟议的模型在所有评估的错误指标中超过了所有第一阶段方法.

结论:

  • 基于基因编程的新型组合方法为预测长期电力消耗提供了非常准确的方法.
  • 根据各种情景,埃塞俄比亚的电力消耗预计到2031年将比2021年的水平增加三倍.
  • 这种预测模型可以在埃塞俄比亚的战略能源规划和基础设施开发中发挥重要作用.