• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IFAC PapersOnLine >An Artificial Neural Network (ANN) model to predict the electric load profile for an HVAC system ?
【24h】

An Artificial Neural Network (ANN) model to predict the electric load profile for an HVAC system ?

机译：人工神经网络（ANN）模型来预测HVAC系统的电力负荷曲线 ？

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

A better management of the Heating, Ventilating and Air Conditioning (HVAC) systems and the integration of renewable energies are two ways to get a Net Zero Energy Buildings (NZEB). Thus, methods to predict the Electrical Load Demand (ELD) for the HVAC system are extremely important, to reach this goal. This paper describes the development and assessment of a fan-coil power demand predictive Artificial Neural Network (ANN) model for a characteristic laboratory inside a research centre located at Almería (Southeast of Spain). As the model is aimed to be used as part of advanced building energy control schemes, some specific requirements, as a trade off between accuracy and simplicity, have been considered. The main consideration for improving new thermal comfort control system is how to save energy without affect the users’ comfort. The performed experiments show a quick prediction with acceptable final results for a short-term prediction horizon using real data. Moreover, a detailed discussion of the obtained ANN model, which has been validated using real data saved from the research centre used as case-study, has been included.
机译：更好地管理供暖，通风和空调（HVAC）系统以及整合可再生能源是获得零能耗净建筑（NZEB）的两种方法。因此，预测用于HVAC系统的电气负载需求（ELD）的方法对于实现此目标非常重要。本文描述了位于西班牙东南部阿尔梅里亚的研究中心内部的特征实验室的风机线圈功率需求预测人工神经网络（ANN）模型的开发和评估。由于该模型旨在用作高级建筑能耗控制方案的一部分，因此已考虑了一些特定要求，以在准确性和简便性之间进行权衡。改进新型热舒适控制系统的主要考虑因素是如何在不影响用户舒适度的情况下节省能源。进行的实验显示了使用实际数据的短期预测范围的快速预测和可接受的最终结果。此外，还包括对所获得的ANN模型的详细讨论，该模型已使用从研究中心保存的真实数据作为案例研究进行了验证。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号