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Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

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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...
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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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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 power...
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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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Multimachine Stability01:25

Multimachine Stability

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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.
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Load-frequency control01:28

Load-frequency control

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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...
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Related Experiment Video

Updated: Jul 7, 2026

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
09:04

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

Published on: June 1, 2022

A similarity-based predictive scheduling method for dynamic electric vehicle charging load management.

Khalil Gorgani Firouzjah1, Jamal Ghasemi2

  • 1Department of Electrical Engineering, Faculty of Engineering and Technology, University of Mazandaran, Babolsar, Iran. khalilgorgani@gmail.com.

Scientific Reports
|April 14, 2026
PubMed
Summary

This study introduces a data-driven energy management framework for electric vehicle (EV) charging stations. It optimizes charging to stabilize the grid, reduce peak demand, and ensure user needs are met efficiently.

Keywords:
Electric vehiclesLoad smoothingPredictive controlReal-time charging managementSimilarity-based prediction

Related Experiment Videos

Last Updated: Jul 7, 2026

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
09:04

A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump

Published on: June 1, 2022

Area of Science:

  • Electrical Engineering
  • Computer Science
  • Sustainable Energy

Background:

  • Managing energy demand from public electric vehicle (EV) charging stations presents challenges to distribution grid stability due to uncertain user demand.
  • Classical methods often struggle with real-time adjustments and user-specific charging requirements.

Purpose of the Study:

  • To develop a multi-stage, data-driven control framework for real-time energy management at public EV parking lots.
  • To achieve load profile smoothing, ensure user-defined charge levels at departure, and maintain grid stability.

Main Methods:

  • A three-layer algorithm integrating historical similarity-based prediction, dynamic predictive optimization using a genetic algorithm, and a final repair stage.
  • Stochastic scenario evaluations to ensure operational robustness.

Main Results:

  • Reduced peak-to-average ratio (PAR) through load shifting from peak to off-peak hours, demonstrating effective peak shaving and valley filling.
  • Limited maximum load ramp rate, preventing transformer stress.
  • Achieved a final state of charge (SoC) error below 0.1% for all EVs.
  • 35% reduction in charging pile occupancy with average processing times of a few seconds.

Conclusions:

  • The proposed framework offers a robust, real-time solution for EV charging energy management, enhancing network resilience.
  • Effectively balances grid stability with user demand, postponing infrastructure upgrade needs.
  • Demonstrates high convergence towards optimal solutions for energy management.