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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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Maximum Power Flow and Line Loadability01:23

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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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The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

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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...
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A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
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Imagine a bucket of water. It contains many molecules, of the order of 1026 molecules. Thus, although it contains discrete elements (molecules) at the microscopic level, macroscopically, it can be considered continuous. Small volume elements of water, infinitesimal compared to the bulk of the bucket's volume, still contain many molecules. Under this framework, quantized matter is approximated as continuous for practical purposes.
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A battery is a galvanic cell that is used as a source of electrical power for specific applications. Modern batteries exist in a multitude of forms to accommodate various applications, from tiny button batteries such as those that power wristwatches to the very large batteries used to supply backup energy to municipal power grids. Some batteries are designed for single-use applications and cannot be recharged (primary cells), while others are based on conveniently reversible cell reactions that...
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Updated: May 11, 2025

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Multi-objective optimization framework for electric vehicle charging and discharging scheduling in distribution

Sahbi Boubaker1, Habib Kraiem2, Nejib Ghazouani3

  • 1Department of Computer and Network Engineering, College of Computer Science and Engineering, University of Jeddah, Jeddah, 21959, Saudi Arabia. sboubaker@uj.edu.sa.

Scientific Reports
|April 17, 2025
PubMed
Summary

Optimizing electric vehicle (EV) charging and discharging schedules using a vehicle-to-grid (V2G) approach enhances power system performance. This method reduces load demand and improves voltage profiles, benefiting EV users and aggregators.

Keywords:
Distribution network managementEVs charging schedulingMulti-Objective optimizationRed deer algorithm (RDA)Vehicle-to-Grid (V2G)

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Area of Science:

  • Electrical Engineering
  • Power Systems Engineering
  • Optimization Theory

Background:

  • Electric vehicles (EVs) present challenges for distribution networks due to unpredictable charging demands.
  • Integrating EVs requires sophisticated management strategies to maintain grid stability and efficiency.
  • Existing methods often struggle to balance user needs with grid capacity constraints.

Purpose of the Study:

  • To develop a multi-objective framework for optimizing EV charging and discharging schedules in power systems.
  • To enhance grid performance by reducing power loss and improving voltage profiles.
  • To satisfy EV user demands and state of charge (SoC) requirements.

Main Methods:

  • A multi-objective optimization framework incorporating a vehicle-to-grid (V2G) approach.
  • Linear weighted sum technique for objective prioritization.
  • Red Deer Algorithm (RDA), a metaheuristic swarm intelligence algorithm, for scheduling optimization.
  • Simulation on an IEEE 69-bus system with diverse EV models.

Main Results:

  • Significantly reduced average EV load demand without overloading the distribution network.
  • Improved voltage profiles across the distribution system.
  • Demonstrated effectiveness of the RDA for optimal EV charging and discharging timing.
  • Analysis of EV integration impact during peak and off-peak hours.

Conclusions:

  • The proposed EV schedule management method effectively balances EV demands with grid constraints.
  • V2G technology and optimized scheduling enhance power system efficiency and stability.
  • Drone integration offers potential for advanced grid energy management beyond power consumption.