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

Search research articles

Related Experiment Video

Updated: May 20, 2026

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke

Published on: October 10, 2025

Radial basis function neural network application to power system restoration studies.

Iman Sadeghkhani¹, Abbas Ketabi, Rene Feuillet

¹Department of Electrical Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran. i.sadeghkhani@ec.iut.ac.ir

Computational Intelligence and Neuroscience

|July 14, 2012

Summary

This summary is machine-generated.

Related Concept Videos

Radial System Protection

Radial System Protection

Radial systems employ time-delay overcurrent relays to reduce load interruptions. When a fault occurs, the nearest breaker opens first, while upstream breakers remain closed due to longer delay settings. This approach ensures minimal disruption to the rest of the system.
In a radial system with a fault downstream of the third breaker, ideally, only the third breaker will open, isolating the fault and interrupting the load connected beyond it. The second breaker has a longer delay setting,...

The Power Flow Problem and Solution

The Power Flow Problem and Solution

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 flow program computes the...

Reclosers and Fuses

Reclosers and Fuses

Automatic circuit reclosers enhance the protection of distribution circuits by interrupting and auto-reclosing an AC circuit according to a preset sequence. They effectively manage temporary faults on overhead distribution lines, often caused by tree limbs or wildlife, by briefly disrupting service to improve overall reliability. However, contact with reclosers or energized broken conductors on the ground can pose serious hazards.
A comprehensive protection scheme for radial distribution...

Routh-Hurwitz Criterion I

Routh-Hurwitz Criterion I

Consider an electrical power grid, where stability is essential to prevent blackouts. The Routh-Hurwitz criterion is a valuable tool for assessing system stability under varying load conditions or faults. By analyzing the closed-loop transfer function, the Routh-Hurwitz criterion helps determine whether the system remains stable.
To apply the Routh-Hurwitz criterion, a Routh table is constructed. The table's rows are labeled with powers of the complex frequency variable s, starting from the...

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:

Multimachine Stability

Multimachine Stability

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:

You might also read

Related Articles

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

Sort by

Same author

Unintended tripping of healthy parallel lines during single-line-to-ground faults: field evidence and mitigation.

Scientific reports·2026

Same author

Cross-entropy based AC series arc fault detection for more electric aircrafts.

Scientific reports·2025

Same author

Resilient oscillator-based cyberattack detection for distributed secondary control of inverter-interfaced Islanded microgrids.

Scientific reports·2025

See all related articles

Transformer switching causes overvoltages that can damage equipment and delay power system restoration. A radial basis function neural network (RBFNN) accurately estimates these switching overvoltages, improving power system reliability.

Area of Science:

Electrical Engineering
Power Systems
Artificial Intelligence

Background:

Overvoltages during transformer switching pose a significant risk to power system equipment and restoration efforts.
Accurate prediction of these transient overvoltages is crucial for ensuring grid stability and reliability.

Purpose of the Study:

To develop and validate a novel method for accurately estimating transformer switching overvoltages.
To enhance the generalization capability of the proposed model for diverse operational scenarios.

Main Methods:

A radial basis function neural network (RBFNN) was developed to model transformer switching overvoltages.
Equivalent network parameters were incorporated as inputs to the RBFNN to improve generalization.
The RBFNN was trained using worst-case switching angles and remanent flux, then tested on typical system cases.

Related Experiment Videos

Last Updated: May 20, 2026

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke

Soft Pneumatic Robot Modulates Graph Theory Metrics of Brain Network for Hand Rehabilitation After Stroke

Published on: October 10, 2025

Main Results:

The proposed RBFNN demonstrated high accuracy in estimating the peak values of switching overvoltages.
The model accurately predicted the duration of the switching overvoltages.
Simulations on a partial New England 39-bus test system validated the technique's effectiveness.

Conclusions:

The developed RBFNN provides an accurate and reliable method for estimating transformer switching overvoltages.
This technique can significantly aid in power system restoration by mitigating potential equipment damage.
The incorporation of equivalent parameters enhances the model's robustness for practical applications.