Back to Projects

Community Energy Management and Low-Carbon Operation in Changzhou

Research Projects · 2024

Past research project · Contributor

Overview

A community energy management research project in Changzhou, May–September 2024.

Background

Aggregators and residents interact in community energy use and carbon trading.

Problem

Analyze how these interactions affect peak-valley differences, user benefits and grid load regulation.

Solution

Model the aggregator–resident relationship as a leader-follower game and use an improved particle swarm algorithm for analysis.

Technology Stack

MATLAB
Leader-follower game
Carbon trading modeling
Improved particle swarm optimization

Implementation

Modeled community energy use and carbon trading mechanisms.
Applied the improved particle swarm algorithm to analyze peak-valley differences, user benefits and grid load regulation.

Result

The supplied CV documents the modeling and analysis during May–September 2024; it supplies no numerical outcome or formal completion label.

Gallery

Conceptual illustration for Community Energy Management and Low-Carbon Operation in Changzhou — AI-generated cover illustration. This is not a project screenshot or a research result.

Demo

No public demo is available for this entry.