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Artificial intelligence techniques for energy efficient H.V.A.C. system design.

Author(s) : DUTTA N. N., DAS T.

Summary

Artificial Intelligence (Artificial Neural Networks, Machine Learning Algorithms, Genetic Algorithms, Fuzzy Systems, etc.) has been part of our lives for many years now, and have proved to be quite useful in areas such as robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimisation and signal processing as they provide an alternate way to tackle complex and ill-defined problems. In this paper we discuss the application of Artificial Neural Networks (A.N.N.) for the improvement of indoor comfort with simultaneous energy conservation in buildings. Energy Conservation is one of the most sought out by scientists and engineers in any project. Heating, Ventilation and Air-Conditioning (H.V.A.C.) systems are one of the major sources of energy consumption in buildings and therefore, are ideal candidates for substantial reductions in energy demand. Significant advances have been made in the past decades on the application of Artificial Intelligence (A.I.) techniques for H.V.A.C. design, control, management, optimization, and fault detection and diagnosis. Here we use a multi-layered Neural Network model to estimate the heating and cooling loads of buildings for efficient H.V.A.C. system design. Errors reported in the model are well within the acceptable limits showing how A.I. may play an important role in conserving energy in buildings.

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Pages: 6

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Details

  • Original title: Artificial intelligence techniques for energy efficient H.V.A.C. system design.
  • Record ID : 30024775
  • Languages: English
  • Subject: Technology
  • Source: Proceedings of the International Conference on Emerging Technologies for Sustainable and Intelligent HVAC&R Systems, Kolkata, July 27-28 2018.
  • Publication date: 2018/07/27

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