By Topic

A Simulation-Based Tool for Energy Efficient Building Design for a Class of Manufacturing Plants

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Hao Liu ; Center for Intelligent and Networked Systems (CFINS), Department of Automation, TNList Lab, Tsinghua University, Beijing, China ; Qianchuan Zhao ; Ningjian Huang ; Xiang Zhao

This paper explores energy efficient building design for manufacturing plants. Many efforts have been directed into the field of building design optimization concerning building energy performance, but most of the studies focus on residential buildings or public buildings. Very limited research results studying plants buildings have been reported. However, plants buildings have certain unique features that make the design problem more challenging. Furthermore, the approaches presented in the current publications could not guarantee the performance of their designs if the computation capacity is limited. This paper attempts to address these two issues. First, an EnergyPlus-integrated overall energy consumption estimation framework is developed for a class of manufacturing plants, where the environmental conditions would not affect the energy consumption of the production processes. Based on that, the building design problem for this type of manufacturing plants is formulated as a stochastic programming problem concerning uncertainties arising from the future weather conditions and energy prices, where seasonal production scheduling optimizing is incorporated when estimating the performance of building designs. Second, Ordinal Optimization (OO) method is introduced to solve the problem so as to quantitatively guarantee a high probability of finding satisfactory designs while reducing the computation burden. A numerical example is provided, showing our solution method performs effectively in finding a satisfactory design.

Published in:

IEEE Transactions on Automation Science and Engineering  (Volume:10 ,  Issue: 1 )