首页 | 本学科首页   官方微博 | 高级检索  
     


Energy demand management for process systems through production scheduling and control
Authors:Chudong Tong  Ahmet Palazoglu  Nael H El‐Farra  Xuefeng Yan
Affiliation:1. Faculty of Electrical Engineering and Computer Science, Ningbo University, Zhejiang 315211, P.R. China;2. Dept. of Chemical Engineering and Materials Science, University of California, Davis, One Shields Avenue, Davis, CA 95616;3. Dept. of Chemical Engineering and Materials Science, University of California, Davis, Davis, CA;4. Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai, P.R. China
Abstract:Demand response (DR) is an integral part of the Smart Grid paradigm, and has become the focus of growing research, development, and deployment in residential, commercial and industrial systems over the last few years. In process systems, energy demand management through production scheduling is an increasingly important tool that has the potential to provide significant economic and operational benefits by promoting the responsiveness of the process operation and its interactions with the utility providers. However, the dynamic behavior of the underlying process, especially during process transitions, is seldom taken into account as part of the DR problem formulation. Furthermore, the incorporation of energy constraints related to electricity pricing and energy resource availability presents an additional challenge. The goal of this study is to present a novel optimization formulation for energy demand management in process systems that accounts explicitly for transition behaviors and costs, subject to time‐sensitive electricity prices and uncertainties in renewable energy resources. The proposed formulation brings together production scheduling and closed‐loop control, and is realized through a real‐time or receding‐horizon optimization framework depending on the underlying operational scenarios. The dynamic formulation is cast as a mixed‐integer nonlinear programming problem based on a proposed discretization approach, and its merits are demonstrated using a simulated continuous stirred tank reactor where the energy required is assumed to be roughly proportional to the material flow. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3756–3769, 2015
Keywords:demand response  scheduling and control  electricity pricing  renewable energy
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号