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Related Concept Videos

Design Example: Aggregate Gradation01:24

Design Example: Aggregate Gradation

The right type and quality of aggregates are crucial for concrete as they significantly influence its properties, mix proportions, and cost-effectiveness. If different sources are available for sand, the commonly used fine aggregate in concrete, the selection of sand is primarily based on its gradation.
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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.
Distributed Loads01:19

Distributed Loads

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Distributed Loads: Problem Solving

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Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations01:15

Determination of Multiple Dosing Parameters: Steady-State, Minimum and Maximum Concentrations

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Dynamic Equilibrium

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Related Experiment Videos

A baseline-oriented dynamic aggregation approach for demand-side heterogeneous controllable resources.

Yiwei Xiao1, Jingjie Huang1, Xiaoran Dai2

  • 1School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, 410114, China.

Scientific Reports
|July 7, 2026
PubMed
Summary
This summary is machine-generated.

Coordinating many diverse energy resources for demand response (DR) is difficult. This study introduces a dynamic aggregation method using load baselines to effectively group these resources for improved power system coordination.

Keywords:
Controllable resourcesDemand responseDynamic aggregationLoad baseline

Related Experiment Videos

Area of Science:

  • Electrical Engineering
  • Power Systems
  • Smart Grids

Background:

  • Demand response (DR) programs face challenges coordinating numerous geographically dispersed controllable resources.
  • Effective aggregation is crucial for integrating these resources into power systems.

Purpose of the Study:

  • To propose a dynamic aggregation method for heterogeneous controllable resources in power systems.
  • To improve the coordination and participation of demand-side resources in DR programs.

Main Methods:

  • Quantitative evaluation of resource response potential and generation of target load baselines.
  • Segmentation of load baselines into ramping, peak, and valley periods using edge-point detection.
  • Combined Analytic Hierarchy Process and Anti-entropy Weight Method (AHP-AWM) for dynamic indicator weighting.
  • Improved K-means algorithm for adaptive aggregation under multiple regulation scenarios.

Main Results:

  • The proposed framework successfully quantifies resource response potential and establishes dynamic load baselines.
  • The AHP-AWM method effectively determines dynamic indicator weights for diverse regulation needs.
  • The weighted K-means algorithm achieved adaptive aggregation of controllable resources.
  • Numerical simulations confirmed the framework's applicability and the distinct response characteristics of aggregated clusters.

Conclusions:

  • The dynamic aggregation method based on load baselines enhances the coordination of heterogeneous controllable resources.
  • The approach provides a flexible and effective solution for integrating demand-side resources into power systems for demand response.
  • The method demonstrates adaptability to various operating conditions and regulation requirements.