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A decentralized, model-free, global optimization method for energy saving in heating, ventilation and air conditioning systems

Author(s):



Medium: journal article
Language(s): English
Published in: Building Services Engineering Research and Technology, , n. 4, v. 41
Page(s): 414-428
DOI: 10.1177/0143624419862707
Abstract:

To solve the challenges of high labour and maintenance cost while saving energy in engineering, a decentralized agent-based model-free global optimization method for heating, ventilation and air conditioning systems is proposed. In this novel optimization method, each updated smart equipment is connected according to the physical relationships, such that it can communicate and collaborate with adjacent nodes. Furthermore, to achieve the overall optimal operation of heating, ventilation and air conditioning systems, a decentralized evolutionary algorithm is developed. With the decentralized algorithm executed in all smart nodes in parallel with the feedback of sensor measurements instead of accurate device models, the system can achieve optimal coordination and avoid conflicts between correlated devices. The equivalence between the centralized and decentralized methods is proven. This method is confirmed to be effective through hardware testing based on actual engineering.

Practical application: The traditional optimization methods for heating, ventilation and air conditioning are based on a centralized structure with a series of deficiencies, such as high maintenance and labour costs, link congestion and operational lag. This study presents a novel decentralized structure constructed using basic physical relations and a model-free method that possesses the advantages of plug-and-play, rapid development, great flexibility and convenience for engineering implementation without having to build a central monitor. The case study results validate the efficiency and effectiveness of the proposed method.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1177/0143624419862707.
  • About this
    data sheet
  • Reference-ID
    10477134
  • Published on:
    18/11/2020
  • Last updated on:
    18/11/2020
 
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