1056 / 2019-05-19 21:15:44
Prediction and Optimization on Energy Consumption of Data Center Based on Multi-layer Feedforward Neural Network
Air conditioning system,Energy Consumption Optimization,Error Back-Propagation,Multi-layer Feedforward Neural Network
Draft Accepted
Song Zhang / Northeast Electric Power Design Institute Co., Ltd.
Xin Ye / Northeast Electric Power Design Institute Co., Ltd.
Ying Ren / Northeast Electric Power Design Institute Co., Ltd.
The characteristics of energy consumption calculation are large amounts of equipments, high parameter coupling, non-linear calculation and complex modeling. Multi-layer feedforward neural network model is used to establish relations between the parameters of air conditioning system, computer equipments, power supply system and the energy consumption values. The error back-propagation algorithm based on gradient descent strategy is used to adjust connection weight and threshold of the neurons in hidden layers. Through the prediction of energy consumption with the variation of uncontrollable parameters, the adjustment of controllable parameters such as the temperature target value of air conditioner, the control mode of fresh air exchangers and humidifiers can obtain the target of energy consumption minimization.
Important Date
  • Conference Date

    Oct 21

    2019

    to

    Oct 24

    2019

  • Oct 13 2019

    Abstract Notification of Acceptance

  • Oct 13 2019

    Draft paper submission deadline

  • Oct 14 2019

    Draft Paper Acceptance Notification

  • Oct 24 2019

    Registration deadline

  • Oct 29 2019

    Final Paper Deadline

Organized By
Xi'an Jiaotong University
Contact Information