"Just-For-Peak" Buffer Inventory for Peak Electricity Demand Reduction of Manufacturing Systems
Abstract
The reduction of the electricity demand during peak periods is considered a main objective of electricity load management. It can relieve the financial pressure of the investment on the capacity expansion for the power grid in the United States. Compared to a great deal of research on commercial and residential building sectors, few studies on the electricity demand reduction during peak periods for industrial manufacturing systems have been conducted due to the concern of system throughput variation and the complexity of modern manufacturing systems. This paper presents a novel "Just-for-Peak" buffer inventory methodology to reduce the electricity consumption without compromising system throughput during peak periods for typical manufacturing systems with multiple machines and buffers. Nonlinear Integer Programming (NIP) formulation is used to establish the mathematical model. The optimal buffer inventory management policies and corresponding load management actions for the whole system are identified by minimizing the holding cost of the "Just-for-Peak" buffer inventory and energy consumption cost under the system throughput constraint throughout the production horizon. A numerical case study based on an automotive assembly line is used to illustrate the effectiveness of the proposed method.
Recommended Citation
M. Fernandez et al., ""Just-For-Peak" Buffer Inventory for Peak Electricity Demand Reduction of Manufacturing Systems," International Journal of Production Economics, vol. 146, no. 1, pp. 178 - 184, Elsevier B.V., Nov 2013.
The definitive version is available at https://doi.org/10.1016/j.ijpe.2013.06.020
Department(s)
Engineering Management and Systems Engineering
Keywords and Phrases
Just-For-Peak Buffer Inventory; Energy Management; Peak Electricity Demand
International Standard Serial Number (ISSN)
0925-5273
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2013 Elsevier B.V., All rights reserved.
Publication Date
01 Nov 2013