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相关概念视频

Wind Turbine Machine Models01:24

Wind Turbine Machine Models

122
In the growing field of wind energy, incorporating wind turbine models into transient stability analysis is essential. Induction and synchronous machines are the primary models used, with induction machines being prevalent due to their simplicity and reliability.
Induction machines interact through the rotating magnetic field generated by the stator and the rotor. The key parameter is slip, which is the difference between synchronous speed and rotor speed relative to synchronous speed. Slip is...
122
Turbine-Governor Control01:17

Turbine-Governor Control

203
Turbine-governor control is crucial for maintaining power system stability by balancing turbine mechanical power output with electrical load demand. This mechanism ensures that generator frequency and rotor speed are within acceptable limits during load variations. Turbine-generator units store kinetic energy due to their rotating masses; this energy is released to meet the load requirement when the load increases. The electrical torque of turbines rises to meet the demand, whereas the...
203
Design Example: Calculating Safe Diameter for Wind-Exposed Disc01:17

Design Example: Calculating Safe Diameter for Wind-Exposed Disc

55
Assessing safety in wind-exposed installations is crucial to preventing potential failures. This example explores the calculation and design adjustments needed to mount a circular disc on a building facade, where wind forces are a primary concern. A 4-meter diameter disc was initially designed as an aesthetic feature facing winds at a velocity of 25 meters per second, with an air density of 1.25 kilograms per cubic meter. Given these conditions, the drag force on the disc was determined using...
55
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

187
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:
187
The Swing Equation01:21

The Swing Equation

382
The Swing Equation is a fundamental tool in power system dynamics, especially for analyzing the behavior of generating units like three-phase synchronous generators. This equation emerges from applying Newton's second law to the rotor of a generator, encompassing factors such as inertia, angular acceleration, and the interplay between mechanical and electrical torques.
In a steady-state operation, the mechanical torque (Τm) supplied to the generator is balanced by the electrical torque...
382
Moment-of-Momentum Equation01:09

Moment-of-Momentum Equation

98
The moment-of-momentum equation is a critical tool for analyzing the torque produced by the rotating blades of a wind turbine. This equation is derived by applying Newton's second law to a fluid particle, which states that the rate of change of linear momentum is equal to the external force acting on the particle.
98

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Measurements of Waves in a Wind-wave Tank Under Steady and Time-varying Wind Forcing
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SDWPF:在大型轮机阵列上进行空间动态风电预测的数据集.

Jingbo Zhou1, Xinjiang Lu2, Yixiong Xiao2

  • 1Business Intelligence Lab, Baidu Research, Beijing, China. zhoujingbo@baidu.com.

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|June 19, 2024
PubMed
概括
此摘要是机器生成的。

一个新的空间动态风力发电预测 (SDWPF) 数据集通过包括轮机空间数据和动态因素来增强风力发电集成. 这有助于推进可再生能源电网管理.

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科学领域:

  • 可再生能源系统可再生能源系统
  • 数据科学数据科学数据科学
  • 电网整合 电网整合

背景情况:

  • 风力发电是一种清洁的可再生能源,由于其固有的变化性,它面临着电网整合的挑战.
  • 精确的风力发电预测 (WPF) 对于管理电网稳定性和最大限度地利用可再生能源至关重要.
  • 现有的WPF数据集的范围有限,缺乏针对单个轮机的详细空间和动态上下文信息.

研究的目的:

  • 引入空间动态风力发电预测 (SDWPF) 数据集,这是推动WPF研究的全面资源.
  • 为每个风力轮机提供详细的空间分布和动态上下文因素,解决先前数据集的局限性.
  • 促进风能预测分析和电网整合战略的改进.

主要方法:

  • 开发SDWPF数据集,包括发电,风速,轮机空间分布和动态上下文因素.
  • 在数据集中包括轮机特定的天气信息和内部运行状态.
  • 利用SDWPF数据集来主办ACM KDD Cup 2022数据挖掘比赛.

主要成果:

  • SDWPF数据集丰富了WPF研究的细粒度,多方面的数据.
  • 2022年ACM KDD杯,利用SDWPF,吸引了超过2400个全球团队,表明对新型预测解决方案的重大兴趣和潜力.
  • 数据集的全面性质支持更准确和更强大的风力发电预测模型.

结论:

  • SDWPF数据集代表了风力发电预测研究可用的资源的重大进步.
  • 成功的ACM KDD杯2022展示了数据集的价值和潜力,推动数据挖掘和可再生能源方面的创新.
  • 通过像SDWPF这样的数据集来增强WPF的能力,对于可靠地将风能集成到电网中至关重要.