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相关概念视频

Distribution Reliability and Automation01:25

Distribution Reliability and Automation

495
Distribution reliability in electrical power systems is critical for ensuring an uninterrupted power supply to consumers at minimal cost. According to IEEE Standard Terms, reliability is the probability that a device will function without failure over a specified time period or amount of usage. For electric power distribution, this translates to maintaining continuous power supply and addressing customer concerns over power outages. Several indices, as defined by IEEE Standard 1366-2012, are...
495
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

1.1K
Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
1.1K
Transformers in Distribution System01:27

Transformers in Distribution System

494
Transformers in distribution systems can be broadly categorized into distribution substation transformers and other distribution transformers. They are crucial for stepping down high transmission voltages to levels suitable for distribution and end-user applications.
Distribution substation transformers come in various ratings and typically use mineral oil for insulation and cooling. To prevent moisture and air from entering the oil, some transformers use an inert gas like nitrogen to fill the...
494
Current Growth And Decay In RL Circuits01:30

Current Growth And Decay In RL Circuits

4.5K
The current growth and decay in RL circuits can be understood by considering a series RL circuit consisting of a resistor, an inductor, a constant source of emf, and two switches. When the first switch is closed, the circuit is equivalent to a single-loop circuit consisting of a resistor and an inductor connected to a source of emf. In this case, the source of emf produces a current in the circuit. If there were no self-inductance in the circuit, the current would rise immediately to a steady...
4.5K
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

484
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
484
Reclosers and Fuses01:26

Reclosers and Fuses

452
Automatic circuit reclosers enhance the protection of distribution circuits by interrupting and auto-reclosing an AC circuit according to a preset sequence. They effectively manage temporary faults on overhead distribution lines, often caused by tree limbs or wildlife, by briefly disrupting service to improve overall reliability. However, contact with reclosers or energized broken conductors on the ground can pose serious hazards.
A comprehensive protection scheme for radial distribution...
452

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相关实验视频

Updated: Jan 14, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

1.0K

深度强化学习用于在线重新配置主动分销网络.

Guokai Hao, Yuanzheng Li, Yang Li

    IEEE transactions on neural networks and learning systems
    |October 23, 2025
    PubMed
    概括

    本研究介绍了一种在线-离线的深度强化学习 (DRL) 框架,用于主动配电网络重新配置 (ADNR),以管理可再生能源的波动. 这种新的方法通过提高DRL在实时操作中的性能来提高电网稳定性和可再生能源的整合.

    科学领域:

    • 电气工程 电气工程
    • 电力系统 电力系统
    • 人工智能的人工智能

    背景情况:

    • 在主动配电网络 (ADN) 中可再生能源 (RE) 的高透率引入了不确定性和可变性,影响了电网稳定性和效率.
    • 传统的深度强化学习 (DRL) 方法用于DNA重新配置 (ADNR) 通常依赖于历史数据,导致潜在的不匹配和未见的场景的挑战.

    研究的目的:

    • 开发一个先进的在线-离线DRL框架,以实现有效的在线DNAR.
    • 为了减轻RE不确定性和DNA的变化所带来的挑战.
    • 改进DRL算法对ADNR的一般化和实时性能.

    主要方法:

    • 制定了DNAR作为一个国家驱动的马尔科夫决策过程 (MDP),结合了DNA的操作特征.
    • 提出了一个国家驱动的近距离政策优化 (SD-PPO) 算法,以增强DRL泛化.
    • 引入了针对个性化的在线培训的优化行动近接政策优化 (OA-PPO) 算法.

    主要成果:

    • 拟议的在线-离线DRL框架有效地减少IEEE ADN系统中的功耗损失.
    • 通过改进的ADNR战略,可以实现更好的可再生能源适应.
    • 与传统的DRL和ADNR算法相比,表现出优越的计算性能.

    相关实验视频

    Last Updated: Jan 14, 2026

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    1.0K

    结论:

    • 新的在线-离线DRL框架为管理ADN中的RE波动提供了一个强大的解决方案.
    • SD-PPO 和 OA-PPO 算法显著提高了实时 ADNR 的 DRL 性能.
    • 该方法提供了一种计算高效和有效的方法来增强ADN的操作和控制.