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

287
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...
287
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

253
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:
253
Maximum Power Flow and Line Loadability01:23

Maximum Power Flow and Line Loadability

153
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.
153
Power System Three-Phase Short Circuits01:21

Power System Three-Phase Short Circuits

126
Determining the subtransient fault current in a power system involves representing transformers by their leakage reactances, transmission lines by their equivalent series reactances, and synchronous machines as constant voltage sources behind their subtransient reactances. In this analysis, certain elements are excluded, such as winding resistances, series resistances, shunt admittances, delta-Y phase shifts, armature resistance, saturation, saliency, non-rotating impedance loads, and small...
126
Power System Distribution01:25

Power System Distribution

287
Power system distribution involves delivering electrical energy from power plants to consumers through a network of transmission and distribution systems. The process begins at power plants, where energy from coal, gas, nuclear, water, and wind is converted into electrical energy. These plants use three-phase generators, typically rated between 50 to 1300 MVA, with terminal voltages ranging from a few kV to 20 kV, depending on the size and age of the units.
The transmission system is designed...
287
Power in a Three-Phase Circuit01:15

Power in a Three-Phase Circuit

389
Three-phase systems have two configurations: the wye and delta. A star configuration can be three or four wires; in a delta configuration, the components are connected in a closed loop. Instantaneous power refers to the power value at a precise moment, and in a balanced three-phase system, it is constant. This is because the sum of the instantaneous powers in the three phases remains steady over time, despite individual fluctuations, due to the symmetry and phase relationship. The total...
389

You might also read

Related Articles

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

Sort by
Same author

Recycled Aggregates Influence on the Mechanical Properties of Cement Lime-Based Mortars Part II.

Materials (Basel, Switzerland)·2026
Same author

Multiyear Soil-Fruit Transfer Dynamics of Macro- and Trace Elements in Raspberry (<i>Rubus idaeus</i> L.) Under Field Conditions.

Plants (Basel, Switzerland)·2026
Same author

From Soil to Plate: Lithium and Other Trace Metals Uptake in Vegetables Under Variable Soil Conditions.

Toxics·2025
Same author

Antioxidant Potential and Volatile Aroma Profiling of Red Wines from the Tarnave Vineyard.

Molecules (Basel, Switzerland)·2025
Same author

Pesticide Surveillance in Fruits and Vegetables from Romanian Supply: A Data-Driven Approach.

Journal of xenobiotics·2025
Same author

Correction: Badea et al. New Trends in Separation Techniques of Lithium Isotopes: A Review of Chemical Separation Methods. <i>Materials</i> 2023, <i>16</i>, 3817.

Materials (Basel, Switzerland)·2025

Related Experiment Video

Updated: Aug 8, 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

563

Contributions to Power Grid System Analysis Based on Clustering Techniques.

Gheorghe Grigoraș1, Maria Simona Raboaca2,3,4, Catalin Dumitrescu5

  • 1Department of Power Engineering, "Gheorghe Asachi" Technical University of Iasi, 700050 Iasi, Romania.

Sensors (Basel, Switzerland)
|February 28, 2023
PubMed
Summary
This summary is machine-generated.

This study models consumer classification and load profiling for smart grids, enhancing electrical network efficiency. It simulates transformer and meter loads, crucial for modernizing power systems.

Keywords:
clustering techniquespattern clusteringpower distribution planningregression algorithmssmart grid

More Related Videos

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

596
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.0K

Related Experiment Videos

Last Updated: Aug 8, 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

563
Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

596
Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations
12:27

Large-scale Reconstructions and Independent, Unbiased Clustering Based on Morphological Metrics to Classify Neurons in Selective Populations

Published on: February 15, 2017

7.0K

Area of Science:

  • Electrical Engineering
  • Computer Science
  • Artificial Intelligence

Background:

  • Modernizing power systems is essential for integrating smart technologies.
  • Smart grids, smart metering, smart homes, and electric cars are interconnected concepts.
  • Advancements in AI, telecommunications, and computing infrastructure are key enablers.

Purpose of the Study:

  • To model consumer classification and load profiling in electrical power networks.
  • To evaluate the efficiency of clustering techniques for consumer profiling.
  • To simulate the load on distribution transformers and electricity meters.

Main Methods:

  • Development of models for consumer classification and load profiling.
  • Application and simulation of clustering techniques for data analysis.
  • Load flow simulation from medium-voltage/low-voltage transformers to meters.

Main Results:

  • Demonstrated effectiveness of clustering techniques in classifying consumers.
  • Provided insights into load profiling accuracy for smart grid applications.
  • Quantified load simulations for distribution network components.

Conclusions:

  • Accurate load profiling and consumer classification are vital for smart grid stability.
  • Clustering techniques offer an efficient approach to understanding consumer behavior.
  • The study provides a foundation for optimizing power distribution and management.