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相关概念视频

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

122
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
122
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

170
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
170
Multimachine Stability01:25

Multimachine Stability

180
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
180
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

131
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.
131
Conservation of Energy in Control Volume01:14

Conservation of Energy in Control Volume

858
Consider a turbine operating under steady-flow conditions. The control volume is drawn around the turbine, with fluid entering at one point and exiting at another. The turbine extracts energy from the fluid, which performs mechanical work (shaft work).
For steady flow systems, the time derivative of the stored energy becomes zero since there is no energy accumulation within the control volume. This simplifies the energy equation to:
858
Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model01:13

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

80
Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
80

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相关实验视频

Updated: Jul 15, 2025

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

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综合能源系统在多重稳定性条件下的双层优化模型.

Xiaobao Yu1, Wenjing Zhao1

  • 1School of Economics and Management, Shanghai University of Electric Power, Shanghai, China.

PloS one
|September 26, 2023
PubMed
概括
此摘要是机器生成的。

优化可再生能源系统可以降低成本,提高效率,尽管输出变化. 强大的双层编程和火虫算法解决了分布式能量输出和负载的不确定性.

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科学领域:

  • 可再生能源系统可再生能源系统
  • 优化理论 优化理论
  • 能源经济学 能源经济学

背景情况:

  • 可再生能源的整合受到输出不稳定性和随机性的阻碍.
  • 综合能源系统提高了效率,但面临着间歇性能源的挑战.
  • 分布式能源输出和负载的不确定性会影响系统的可靠性和成本.

研究的目的:

  • 为全面的能源系统开发一个强大的优化模型.
  • 解决分布式可再生能源输出和负载的不确定性.
  • 尽量减少系统运营成本,同时确保可靠性.

主要方法:

  • 制定一个包含强度的双层编程优化模型.
  • 利用火虫算法来解决复杂的优化问题.
  • 在不同分布式风力发电输出间隔下分析系统性能.

主要成果:

  • 优化不确定性大大降低了实际系统运营成本,最大降低14.43%.
  • 在特定的分布式风力发电输出范围 ([0,190]) 中,成本和消耗率之间的动态平衡是可以实现的.
  • 拟议的模型证明了强大的优化在管理可再生能源整合方面的有效性.

结论:

  • 强大的优化是减轻可再生能源不确定性的经济影响的可行策略.
  • 火算法为复杂的综合能源系统优化问题提供了有效的解决方案.
  • 实现成本和消费之间的平衡对于成功大规模部署可再生能源至关重要.