Low-carbon and energy-saving control of central air-conditioning refrigeration station based on PSO-LM-BP algorithm

Due to the inertia of the operating environment, the central air conditioning refrigeration station has poor operating parameters, high daily power consumption, and limited low-carbon effects. This article proposes using the PSO-LM-BP algorithm for low-carbon and energy-saving control, setting goals and designing control structures, and optimizing operating parameters using the PSO-LM-BAP algorithm. The experiment showed that after optimization, the daily power consumption significantly decreased, with a maximum of only 135kW/h, demonstrating excellent energy-saving performance.

Authors

Institutions

Publication Details

Published
2025-07-24
DOI
https://doi.org/10.1117/12.3068506
Primary Topic
Refrigeration and Air Conditioning Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Low-carbon and energy-saving control of central air-conditioning refrigeration station based on PSO-LM-BP algorithm

Hongjie Wu, Zicheng Sun, T. Gu, Zheng Liu et al.
Refrigeration and Air Conditioning Technologies
article

Low-carbon and energy-saving control of central air-conditioning refrigeration station based on PSO-LM-BP algorithm

Hongjie Wu, Zicheng Sun, T. Gu, Zheng Liu, Jinming Huang
article en

Abstract

Due to the inertia of the operating environment, the central air conditioning refrigeration station has poor operating parameters, high daily power consumption, and limited low-carbon effects. This article proposes using the PSO-LM-BP algorithm for low-carbon and energy-saving control, setting goals and designing control structures, and optimizing operating parameters using the PSO-LM-BAP algorithm. The experiment showed that after optimization, the daily power consumption significantly decreased, with a maximum of only 135kW/h, demonstrating excellent energy-saving performance.

State Grid Corporation of China (China) (CN)
Affordable and clean energy
Openalex Percentile: Top 82%
Refrigeration and Air Conditioning Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Low-carbon and energy-saving control of central air-conditioning refrigeration station based on PSO-LM-BP algorithm — Hongjie Wu, Zicheng Sun, et al. · (2025) | TGRS Research Map | TGRS