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

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

98
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
98
Open and closed-loop control systems01:17

Open and closed-loop control systems

652
Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
652
Conservation of Energy in Control Volume01:14

Conservation of Energy in Control Volume

542
Consider a turbine operating under steady-flow conditions. The control volume is drawn around the turbine, with fluid entering at one point and exiting at another. The turbine extracts energy from the fluid, which performs mechanical work (shaft work).
For steady flow systems, the time derivative of the stored energy becomes zero since there is no energy accumulation within the control volume. This simplifies the energy equation to:
542
Feedback control systems01:26

Feedback control systems

288
Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
288
Control Systems: Applications01:25

Control Systems: Applications

578
Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The...
578
Load-frequency control01:28

Load-frequency control

126
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...
126

You might also read

Related Articles

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

Sort by
Same author

FalsEye: proactive detection of false data injection attacks in smart grids using IceCube-optimised ensemble learning.

Scientific reports·2026
Same author

Cyber-resilient machine learning framework for accurate individual load forecasting and anomaly detection in smart grids.

Scientific reports·2025
Same author

Enhancing electric vehicle battery lifespan: integrating active balancing and machine learning for precise RUL estimation.

Scientific reports·2025
Same author

Optimal location of PMUs for full observability of power system using coronavirus herd immunity optimizer.

Heliyon·2024
Same author

Practical prototype for energy management system in smart microgrid considering uncertainties and energy theft.

Scientific reports·2023
Same author

Optimal allocation of multi-type FACTS devices for mitigating wind power spillage with enhancing voltage stability and social welfare.

Scientific reports·2023
Same journal

A tri-axis optomechanical accelerometer with plasmonic MIM waveguide and structural direction-dependent optical signatures.

Scientific reports·2026
Same journal

Holographic leaky-wave antennas with independently controlled multiple counter-rotating vortex beams.

Scientific reports·2026
Same journal

Differential associations of longitudinal hearing and vision trajectories with dementia and mild cognitive impairment in older adults.

Scientific reports·2026
Same journal

Abdominal obesity and leisure-time sedentary behavior in relation to gastroesophageal reflux disease risk: a prospective cohort study from the UK Biobank.

Scientific reports·2026
Same journal

Effect of nitrogen-rich COF incorporation on the structure and separation performance of polyamide nanofiltration membranes.

Scientific reports·2026
Same journal

Withanolide A inhibits hIAPP aggregation: An In silico, biophysical, and drosophila-based In vivo validation.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Jun 7, 2025

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

252

Coordinated distributed model predictive control for multi energy carrier systems.

Magda I El-Afifi1,2, Abdelfattah A Eladl3, Magdi M El-Saadawi3

  • 1Electrical Eng. Deparment, Faculty of Engineering, Mansoura University, El-Mansoura, Egypt. magda_ibrahim@nilehi.edu.eg.

Scientific Reports
|November 12, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a distributed control system for dynamic energy hubs (EHs) to manage renewable energy integration. The proposed model predictive control strategy enhances stability and optimizes performance despite fluctuating energy demands and sources.

Keywords:
Combined heat and powerEnergy hubsHeat pumpModel predictive controlMulti-energy systems

More Related Videos

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

3.0K
Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.4K

Related Experiment Videos

Last Updated: Jun 7, 2025

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

252
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

3.0K
Interactive and Visualized Online Experimentation System for Engineering Education and Research
08:35

Interactive and Visualized Online Experimentation System for Engineering Education and Research

Published on: November 24, 2021

2.4K

Area of Science:

  • Energy Systems Engineering
  • Control Theory
  • Renewable Energy Integration

Background:

  • Energy hubs (EHs) are crucial for integrating renewable energy sources (RESs).
  • Stochastic RESs and fluctuating energy demands create challenges like voltage instability and complex energy management.
  • Dynamic response times of electrical and heat loads further complicate control systems.

Purpose of the Study:

  • To propose a distributed control system for dynamic energy hubs.
  • To address challenges in managing renewable energy sources and fluctuating demands.
  • To optimize the performance of multi-carrier energy systems.

Main Methods:

  • Development of a distributed control system for dynamic energy hubs.
  • Implementation of a distributed model predictive control (MPC) strategy.
  • Consideration of RESs, loads, and operational constraints within the multi-carrier system.

Main Results:

  • The proposed distributed MPC strategy effectively manages dynamic energy hubs.
  • Simulations demonstrate the system's capability to handle stochastic RESs and fluctuating demands.
  • Optimized system performance and stability were achieved in a benchmark system.

Conclusions:

  • The distributed control system offers a viable solution for integrating renewable energies into dynamic EHs.
  • Model predictive control is effective in optimizing energy hub operations under uncertain conditions.
  • The proposed strategy enhances the reliability and efficiency of energy systems with high RES penetration.