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Data-driven modeling and optimization of thermal comfort and energy consumption using type-2 fuzzy method

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Abstract

In the research domain of intelligent buildings and smart home, modeling and optimization of the thermal comfort and energy consumption are important issues. This paper presents a type-2 fuzzy method based data-driven strategy for the modeling and optimization of thermal comfort words and energy consumption. First, we propose a methodology to convert the interval survey data on thermal comfort words to the interval type-2 fuzzy sets (IT2 FSs) which can reflect the inter-personal and intra-personal uncertainties contained in the intervals. This data-driven strategy includes three steps: survey data collection and pre-processing, ambiguity-preserved conversion of the survey intervals to their representative type-1 fuzzy sets (T1 FSs), IT2 FS modeling. Then, using the IT2 FS models of thermal comfort words as antecedent parts, an evolving type-2 fuzzy model is constructed to reflect the online observed energy consumption data. Finally, a multiobjective optimization model is presented to recommend a reasonable temperature range that can give comfortable feeling while reducing energy consumption. The proposed method can be used to realize comfortable but energy-saving environment in smart home or intelligent buildings.

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Acknowledgments

This work is supported by National Natural Science Foundation of China (61105077, 61074149, 61273149, and 61273326), and the Excellent Young and Middle-Aged Scientist Award Grant of Shandong Province of China (BS2012DX026).

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Authors and Affiliations

  1. School of Information and Electrical Engineering, Shandong Jianzhu University, Jinan, China

    Chengdong Li, Guiqing Zhang & Ming Wang

  2. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Jianqiang Yi

Authors
  1. Chengdong Li
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  2. Guiqing Zhang
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  3. Ming Wang
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  4. Jianqiang Yi
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Corresponding author

Correspondence to Chengdong Li.

Additional information

Communicated by C. Alippi, D. Zhao and D. Liu.

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Li, C., Zhang, G., Wang, M. et al. Data-driven modeling and optimization of thermal comfort and energy consumption using type-2 fuzzy method. Soft Comput 17, 2075–2088 (2013). https://doi.org/10.1007/s00500-013-1117-4

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  • DOI: https://doi.org/10.1007/s00500-013-1117-4

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