Scheduling a storage-augmented discrete production facility under incentive-based demand response

被引:19
作者
Weitzel, Timm [1 ]
Glock, Christoph H. [1 ]
机构
[1] Tech Univ Darmstadt, Inst Prod & Supply Chain Management, Darmstadt, Germany
关键词
load reduction; flexible flow shop scheduling; flexibility; energy management; energy optimisation; demand response; incentive based program; ENERGY MANAGEMENT; SIDE MANAGEMENT; SYSTEMS; OPTIMIZATION; OPERATION; PRICE;
D O I
10.1080/00207543.2018.1475764
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Demand response (DR) is considered as one of the most important measures for balancing energy supply and demand in the smart grid paradigm. Incentive-based programs, one manifestation of DR, contribute to short-term system stability and prevent critical periods when system stability is at risk by enabling the system operator (SO) to directly change total energy demand. The fact that a third party would be empowered to interfere with internal operations is, however, also one of the major drawbacks of DR that prevents especially industrial consumers from participating with full capacity in such programs. This paper considers an alternative Incentive-based program with application to a discrete manufacturing facility where load reduction curves (LRCs) are generated a priori outlining the potential load reduction in the DR period. The SO uses the LRC to determine the desired level of load reduction for critical periods. To illustrate the generation of the LRC, this paper builds on a flexible flow shop (FFS) formulation for a discrete manufacturing facility and presents a model that includes multiple machine modes and product- and machine-specific energy consumption trajectories. Based on the FFS, a procedure is developed to generate the LRC. The paper also investigates the potential of including a battery energy storage system (BESS) into the production facility and illustrates the effects of the BESS on the LRC.
引用
收藏
页码:250 / 270
页数:21
相关论文
共 52 条
[1]   Demand-Side Bidding Strategy for Residential Energy Management in a Smart Grid Environment [J].
Adika, Christopher O. ;
Wang, Lingfeng .
IEEE TRANSACTIONS ON SMART GRID, 2014, 5 (04) :1724-1733
[2]   Demand response in smart electricity grids equipped with renewable energy sources: A review [J].
Aghaei, Jamshid ;
Alizadeh, Mohammad-Iman .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2013, 18 :64-72
[3]  
Agora Energiewende, 2017, SMART MARK DES DTSCH
[4]   A summary of demand response in electricity markets [J].
Albadi, M. H. ;
El-Saadany, E. F. .
ELECTRIC POWER SYSTEMS RESEARCH, 2008, 78 (11) :1989-1996
[5]  
[Anonymous], IEEE POW ENG SOC GEN
[6]  
[Anonymous], 2016, SCHEDULING THEORY AL, DOI DOI 10.1007/978-3-319-26580-3
[7]  
[Anonymous], ANN EN OUTL PROJ 204
[8]  
[Anonymous], 2016, KEY WORLD EN STAT
[9]   Peak load management in electrolytic process industries [J].
Babu, C. A. ;
Ashok, S. .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2008, 23 (02) :399-405
[10]   A review on lithium-ion battery ageing mechanisms and estimations for automotive applications [J].
Barre, Anthony ;
Deguilhem, Benjamin ;
Grolleau, Sebastien ;
Gerard, Mathias ;
Suard, Frederic ;
Riu, Delphine .
JOURNAL OF POWER SOURCES, 2013, 241 :680-689