Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

The Power Flow Problem and Solution01:26

The Power Flow Problem and Solution

776
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...
776
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

570
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.
570
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

705
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:
705
Maximum Power Transfer01:16

Maximum Power Transfer

789
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...
789
Control of Power Flow01:30

Control of Power Flow

650
There are several methods to control power flow in power systems:
650
Multimachine Stability01:25

Multimachine Stability

529
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:
529

You might also read

Related Articles

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

Sort by
Same author

Performance of pelican optimizer for energy losses minimization via optimal photovoltaic systems in distribution feeders.

PloS one·2025
Same author

An improved Kepler optimization algorithm for module parameter identification supporting PV power estimation.

Heliyon·2024
Same author

An innovative bio-inspired Aquila technique for efficient solution of combined power and heat economic dispatch problem.

Scientific reports·2024
Same author

A Fractional Order-Kepler Optimization Algorithm (FO-KOA) for single and double-diode parameters PV cell extraction.

Heliyon·2024
Same author

Kepler Algorithm for Large-Scale Systems of Economic Dispatch with Heat Optimization.

Biomimetics (Basel, Switzerland)·2023
Same author

A new adaptive MPPT technique using an improved INC algorithm supported by fuzzy self-tuning controller for a grid-linked photovoltaic system.

PloS one·2023

Related Experiment Video

Updated: Jan 7, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

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

Published on: February 14, 2025

974

Multidimensional Optimal Power Flow with Voltage Profile Enhancement in Electrical Systems via Honey Badger

Sultan Hassan Hakmi1, Hashim Alnami1, Badr M Al Faiya1

  • 1Department of Electrical and Electronics Engineering, Faculty of Engineering and Computer Science, Jazan University, Jizan 45142, Saudi Arabia.

Biomimetics (Basel, Switzerland)
|December 24, 2025
PubMed
Summary
This summary is machine-generated.

A new Honey Badger Optimization (HBO) algorithm effectively solves the Optimal Power Flow (OPF) problem in electrical grids. This novel method improves fuel cost and voltage stability, outperforming existing optimization techniques for modern power systems.

Keywords:
Optimal Power Flowelectrical power networkshoney badger algorithmvoltage profile enhancement

More Related Videos

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

2.0K
Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment
04:35

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

Published on: July 5, 2024

2.3K

Related Experiment Videos

Last Updated: Jan 7, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator
06:04

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

Published on: February 14, 2025

974
Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption
10:36

Author Spotlight: Optimization of Airflow Velocities in Battery Cooling Systems for Enhanced Thermal Performance and Reduced Energy Consumption

Published on: November 3, 2023

2.0K
Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment
04:35

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

Published on: July 5, 2024

2.3K

Area of Science:

  • Electrical Engineering
  • Computational Intelligence
  • Optimization Algorithms

Background:

  • The Optimal Power Flow (OPF) problem is crucial for efficient and reliable operation of modern electrical power systems.
  • Existing optimization methods like Particle Swarm Optimization (PSO) and Gray Wolf Optimization (GWO) have limitations in addressing complex OPF challenges.
  • Balancing economic objectives (fuel cost) and operational quality (voltage deviation) remains a significant challenge in power system management.

Purpose of the Study:

  • To introduce and evaluate a novel metaheuristic algorithm, Honey Badger Optimization (HBO), for solving the OPF problem.
  • To compare the performance of HBO against established algorithms like PSO and GWO in terms of fuel cost reduction and voltage deviation minimization.
  • To investigate the multi-objective capabilities of HBO for balancing competing economic and voltage quality objectives in power systems.

Main Methods:

  • Developed the Honey Badger Optimization (HBO) algorithm, inspired by honey badger foraging behavior, featuring distinct exploration and exploitation stages.
  • Formulated the OPF problem with objectives of fuel cost minimization and voltage deviation reduction, considering operational constraints.
  • Applied HBO to the IEEE 30-bus test system for single-objective and multi-objective optimization analyses.

Main Results:

  • HBO demonstrated superior performance in reducing fuel cost and enhancing voltage profiles compared to PSO and GWO.
  • Achieved significant improvements in voltage deviation, with HBO outperforming GWO by 38.5% and PSO by 22.78%.
  • Successfully generated a comprehensive Pareto front for multi-objective OPF, illustrating the trade-offs between fuel cost and voltage deviation.

Conclusions:

  • Honey Badger Optimization (HBO) is a highly effective and robust tool for solving complex OPF problems in electrical power systems.
  • HBO offers significant advantages over existing methods in improving system economics and voltage stability.
  • The multi-objective capability of HBO provides valuable insights for system operators to manage competing objectives and make informed decisions.