Technical Brief

Scheduling of a Single Flow Shop for Minimal Energy Cost Under Real-Time Electricity Pricing

[+] Author and Article Information
Hao Zhang

School of Mechanical Engineering,
Purdue University,
West Lafayette, IN 47907
e-mail: zhang906@purdue.edu

Fu Zhao

School of Mechanical Engineering,
Purdue University,
West Lafayette, IN 47907
e-mail: fzhao@purdue.edu

John W. Sutherland

Fellow ASME
Division of Environmental and Ecological Engineering,
Purdue University,
West Lafayette, IN 47907
e-mail: jwsuther@purdue.edu

1Corresponding author.

Manuscript received November 22, 2014; final manuscript received July 5, 2016; published online August 15, 2016. Assoc. Editor: Dragan Djurdjanovic.

J. Manuf. Sci. Eng 139(1), 014502 (Aug 15, 2016) (5 pages) Paper No: MANU-14-1623; doi: 10.1115/1.4034275 History: Received November 22, 2014; Revised July 05, 2016

A time-indexed integer programing approach is developed to optimize the manufacturing schedule of a factory for minimal energy cost under real-time pricing (RTP) of electricity. The approach is demonstrated using a flow shop operating during different time periods (i.e., day shift, swing shift, and night shift) in a microgrid, which also serves residential and commercial users. Results show that electricity cost can be reduced by 6.2%, 12.3%, and 21.5% for the three time periods considered, respectively. Additionally, a 6.3% cost reduction can be achieved by the residential and commercial buildings through adopting energy-conscious control strategies in this specific case study example.

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Grahic Jump Location
Fig. 1

Supply curve and instantaneous demand of a power grid

Grahic Jump Location
Fig. 2

Power demand of the business-as-usual residential and commercial buildings

Grahic Jump Location
Fig. 3

Schedule of the business-as-usual manufacturing factory

Grahic Jump Location
Fig. 4

“Minimal electricity cost” schedules of the manufacturing factory

Grahic Jump Location
Fig. 5

Power demand of the residential and commercial buildings with cost-saving operation strategies




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