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相关概念视频

Load-frequency control01:28

Load-frequency control

158
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
158
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

642
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...
642
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:
191
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

107
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.
107
Distribution Reliability and Automation01:25

Distribution Reliability and Automation

107
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...
107
Turbine-Governor Control01:17

Turbine-Governor Control

210
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...
210

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Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
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在分布式能源资源可变性下的微电网控制的数据驱动优化.

Akhilesh Mathur1, Ruchi Kumari1, V P Meena2,3

  • 1Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur, Rajasthan, 302017, India.

Scientific reports
|May 11, 2024
PubMed
概括

这项研究优化了混合微电网运行,使用基于优先级的成本函数和灰狼优化 (GWO). 该方法有效地管理成本效益的不确定性,可靠的能源在电网连接和独立模式.

关键词:
灰狼优化优化 灰狼优化贾雅算法 贾雅算法K - 平均集群化微电网就是一个微电网.蒙特卡洛模拟的蒙特卡洛模拟最佳的安排时间表.概率分布函数是一个概率分布函数.随机过程是一个随机过程.

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科学领域:

  • 电气工程 电气工程
  • 可再生能源系统可再生能源系统
  • 优化技术 优化技术

背景情况:

  • 智能电网受益于可再生能源的整合,以提高弹性和清洁电力.
  • 可再生能源的间歇性需要微电网的先进调度策略.
  • 用光伏 (PV),风能和可控制分布式发电机 (CDG) 优化混合系统对于连接到电网和独立运营至关重要.

研究的目的:

  • 为混合微电网开发基于优先级的成本优化功能.
  • 将间歇性参数的不确定性纳入调度方法.
  • 通过先进的优化来最大限度地降低微电网的整体运营成本.

主要方法:

  • 开发了一个基于优先级的成本优化功能,包括运营,排放,电池,电网能源交换和减负成本.
  • 蒙特卡洛模拟为不确定的参数生成了多个场景,然后使用k-means集群缩小了这些场景.
  • 使用灰狼优化 (GWO) 算法来最小化开发的成本函数,并在CIGRE测试网络上验证.

主要成果:

  • 在各种场景下,GWO算法在最大限度地降低微电网的成本函数方面表现出有效性.
  • 分配给子目标的不同优先级产生了不同的操作结果,展示了拟议方法的灵活性.
  • 在优化微电网的成本方面,GWO方法证明优于Jaya和粒子优化 (PSO) 算法.

结论:

  • 提出的基于优先级的成本优化战略有效地管理混合微电网的不确定性.
  • 灰狼优化算法为优化微电网运行提供了强大而高效的方法.
  • 该方法确保在连接到电网的和独立的微电网配置中提供可靠和成本效益的能源供应.