Development, implementation and trial run of an energy management system based on artificial neural network (ANN) and particle swarm optimization (PSO) for air side system

Solution Development, implementation and trial run of an energy management system based on artificial neural network (ANN) and particle swarm optimization (PSO) for air side system
(REF : S-0213)
Features of Solutions
  • Modelling of the energy consumption of air side system by computer
  • An analysis system based on algorithms of artificial neural network and particle swarm optimization for analyzing the energy consumption data and developing energy saving strategy
  • Implementing trial run at Central Mail Centre (CMC)
  • Investigation on the feasibility of implementing the technology in Hong Kong
Matched Trial Project
  • A computer model of energy consumption of air side system
  • An algorithmic analysis system with machine learning
  • Energy saving strategy developed by the item (2) above
  • An implementation plan for trial at Central Mail Centre (CMC)
  • A report on the feasibility of implementing the technology in Hong Kong
Additional information Final Report on Research on Tseung Kwan O Hospital 18 JAN.pdf
Contact Information

Company: The University of Hong Kong

Address: EEE Department, Pokfulam Road

Name: Philip Pong

Position: Associate Professor

Tel: 28578491

Email: ppong@eee.hku.hk

Webpage: https://www.eee.hku.hk/~ppong

If you have interest in trial application of the I&T solutions, please click HERE.