Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Maximum Power Flow and Line Loadability

Maximum Power Flow and Line Loadability

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.

Maximum Power Transfer

Maximum Power Transfer

Numerous practical applications within engineering disciplines, such as telecommunications, necessitate optimizing power delivery to a connected load. This pursuit, however, entails inherent internal losses, which can either equal or exceed the power supplied to the load. The Thevenin equivalent circuit is helpful in finding the maximum power a linear circuit can deliver to a load. It is assumed in this context that the load resistance can be adjusted.
By substituting the entire circuit with...

Fast Decoupled and DC Powerflow

Fast Decoupled and DC Powerflow

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:

Generator Voltage Control

Generator Voltage Control

Generator voltage control is crucial for maintaining the stable operation of synchronous generators and wind turbines. In older models, a DC generator driven by the rotor delivers DC power to the rotor's field winding, and the power is transferred through slip rings and brushes. In the latest models, static or brushless exciters are used. Static exciters rectify AC power from the generator terminals and then transfer the DC power directly to the rotor. Brushless exciters, on the other hand,...

Charging Conductors By Induction

Charging Conductors By Induction

The Earth is a good conductor of electricity, and it is so big that it can be considered an infinite source or sink of charges. It can easily exchange charges with any matter.
Generally, conductors like metals do not allow any excess charge to be present on them. Any excess charge added to metals easily flows away, for example, when a metal is placed on the Earth. This process is called earthing.
However, conductors can be charged by a process called induction. For example, consider charging a...

Generation of Three-Phase Voltage

Generation of Three-Phase Voltage

A three-phase AC generator has a rotor with a rotating magnet placed within the stator mounted with the stationary three-phase winding to generate three-phase voltages via mutual induction. These windings are evenly distributed around the inner circumference of the stator and are arranged 120 electrical degrees apart. Three-phase stator windings consist of three separate coils or groups of coils, known as phases, each connected in Y (star) configuration or Delta configuration.
As the rotor...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Memetic Salp Swarm Algorithm for economic load dispatch problems.

Scientific reports·2025

Same author

Parallel boosting neural network with mutual information for day-ahead solar irradiance forecasting.

Scientific reports·2025

Same author

Radar Signal Processing and Its Impact on Deep Learning-Driven Human Activity Recognition.

Sensors (Basel, Switzerland)·2025

Same author

Artificial intelligence enabled smart mask for speech recognition for future hearing devices.

Scientific reports·2024

Same author

A Privacy and Energy-Aware Federated Framework for Human Activity Recognition.

Sensors (Basel, Switzerland)·2023

Same author

DeepVision: Enhanced Drone Detection and Recognition in Visible Imagery through Deep Learning Networks.

Sensors (Basel, Switzerland)·2023

Search research articles

Related Experiment Video

Updated: Aug 5, 2025

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

A Two-Stage Multi-Agent EV Charging Coordination Scheme for Maximizing Grid Performance and Customer Satisfaction.

Adil Amin¹, Anzar Mahmood¹, Ahsan Raza Khan²

¹Department of Electrical Engineering, Mirpur University of Science & Technology (MUST), Mirpur 10250, Pakistan.

Sensors (Basel, Switzerland)

|March 30, 2023

Summary

Coordinated electric vehicle (EV) charging, managed by a multi-agent system, optimizes grid performance by reducing power losses and voltage deviations. This approach enhances customer satisfaction through minimized charging costs and wait times.

Keywords:

charging cost electric vehicles power loss voltage deviation waiting time

More Related Videos

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment

Published on: July 5, 2024

Related Experiment Videos

Last Updated: Aug 5, 2025

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment

Published on: July 5, 2024

Area of Science:

Electrical Engineering
Computer Science
Environmental Science

Background:

Growing electric vehicle (EV) adoption presents challenges to grid stability.
Managed EV integration can improve electrical network performance, reducing losses and voltage deviations.

Purpose of the Study:

To develop a two-stage, multi-agent system for coordinated EV charging scheduling.
To optimize power allocation and align charging for grid benefits and customer satisfaction.

Main Methods:

A two-stage approach using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA).
PSO at the Distribution Network Operator (DNO) level for power allocation.
GA at the EV aggregator level for charging alignment.

Main Results:

Minimized power losses and voltage deviations in the IEEE-33 bus network.
Achieved high customer satisfaction with reduced charging costs and waiting times.
Demonstrated effectiveness under Time of Use (ToU) and Real-Time Pricing (RTP) schemes.

Conclusions:

The proposed multi-agent scheme effectively manages EV charging for improved grid performance.
Coordinated charging enhances network stability and customer satisfaction simultaneously.
The method is robust under varying EV penetration levels and pricing strategies.