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Related Concept Videos

Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

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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:
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Power System Distribution01:25

Power System Distribution

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Power system distribution involves delivering electrical energy from power plants to consumers through a network of transmission and distribution systems. The process begins at power plants, where energy from coal, gas, nuclear, water, and wind is converted into electrical energy. These plants use three-phase generators, typically rated between 50 to 1300 MVA, with terminal voltages ranging from a few kV to 20 kV, depending on the size and age of the units.
The transmission system is designed...
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Secondary Distribution01:25

Secondary Distribution

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Secondary distribution systems provide electrical energy at the utilization voltage levels from distribution transformers to customer meters. Typical secondary voltages in the United States include 120/240 V for residential use, 208Y/120 V for residential and commercial use, and 480Y/277 V for industrial and high-rise commercial use.
In residential areas, 120/240 V single-phase, three-wire service is commonly used for lighting, outlets, and large appliances. Urban areas with high-density loads...
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The Power Flow Problem and Solution01:26

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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 power...
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Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

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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.
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Control of Power Flow01:30

Control of Power Flow

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There are several methods to control power flow in power systems:
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Related Experiment Video

Updated: Apr 22, 2026

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

Published on: December 15, 2023

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A comprehensive WSN-based approach to efficiently manage a Smart Grid.

Ruben Martinez-Sandoval1, Antonio-Javier Garcia-Sanchez2, Felipe Garcia-Sanchez1

  • 1Department of Information and Communication Technologies, Universidad Politécnica de Cartagena (UPCT), Campus Muralla del Mar, E-30202 Cartagena, Spain.

Sensors (Basel, Switzerland)
|October 14, 2014
PubMed
Summary

The SENSED-SG solution enhances Smart Grid (SG) performance using Wireless Sensor Networks (WSNs). It outperforms ZigBee in harsh conditions, offering a robust alternative for modern electrical grids.

Related Experiment Videos

Last Updated: Apr 22, 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

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Area of Science:

  • Electrical Engineering
  • Computer Science
  • Network Communications

Background:

  • The Smart Grid (SG) aims to improve electrical grid efficiency, reliability, and flexibility.
  • Wireless Sensor Networks (WSNs) are crucial for SG implementation due to their cost-effectiveness and collaborative nature.
  • Harsh radio conditions and inadequate WSN systems challenge current SG deployments.

Purpose of the Study:

  • To design and evaluate a comprehensive ad-hoc WSN-based solution for the Smart Grid (SENSED-SG).
  • To address performance limitations and challenges in existing WSN solutions for SG applications.
  • To demonstrate the superiority of SENSED-SG over conventional approaches like ZigBee.

Main Methods:

  • Development of a custom WSN solution (SENSED-SG) with optimized MAC, network, and application layers.
  • Extensive computer simulations and mathematical analysis for performance evaluation.
  • Validation through real-world test-beds in indoor (substation) and outdoor (T&D) SG environments.

Main Results:

  • SENSED-SG demonstrates superior performance compared to the ZigBee WSN approach in SG scenarios.
  • The solution effectively handles challenges posed by harsh radio propagation conditions.
  • Optimized layer implementations contribute to enhanced overall system performance.

Conclusions:

  • SENSED-SG is a highly suitable and performant WSN solution for Smart Grid applications.
  • The developed approach overcomes limitations of existing commercial solutions in challenging SG environments.
  • SENSED-SG offers a viable and improved alternative for future Smart Grid infrastructure.