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Title: An integrated approach to microgrid sizing and flow shop scheduling via climate analytics
A variety of methods have been proposed to assist the integration of microgrid in flow shop systems with the goal of attaining eco-friendly operations. There is still a lack of integrated planning models in which renewable portfolio, microgrid capacity and production plan are jointly optimized under power demand and generation uncertainty. This paper aims to develop a two-stage, mixed-integer programming model to minimize the levelized cost of energy of a flow shop powered by onsite renewables. The first stage minimizes the annual energy use subject to a job throughput requirement. The second stage aims at sizing wind turbine, solar panels and battery units to meet the hourly electricity needs during a year. Climate analytics are employed to characterize the stochastic wind and solar capacity factor on an hourly basis. The model is tested in four locations with a wide range of climate conditions. Three managerial insights are derived from the numerical experiments. First, time-of-use tariff significantly stimulates the wind penetration in locations with medium or low wind speed. Second, regardless of the climate conditions, large-scale battery storage units are preferred under time-of-use rate but it is not the case under a net metering policy. Third, wind- and solar-based microgrid is more » scalable and capable of meeting short-term demand variation and long-term load growth with a stable energy cost rate. « less
Authors:
; ;
Award ID(s):
1704933
Publication Date:
NSF-PAR ID:
10296903
Journal Name:
Journal of cleaner production
Volume:
252
Page Range or eLocation-ID:
https://doi.org/10.1016/j.jclepro.2019.119829
ISSN:
0959-6526
Sponsoring Org:
National Science Foundation
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