Reference : Compensating Balancing Demand by Spatial Load Migration : The Case of Geographically ...
Scientific journals : Article
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/44506
Compensating Balancing Demand by Spatial Load Migration : The Case of Geographically Distributed Data Center
English
Thimmel, Markus [> >]
Fridgen, Gilbert mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) >]
Keller, Robert [> >]
Rövekamp, Patrick [> >]
2019
Energy Policy
130
1130--1142
Yes
[en] Distributed data centers; spatial load migration; balancing power compensation; economic potential; simulation-based case study; demand response
[en] The increasing share of renewables confronts existing power grids with a massive challenge, stemming from additional volatility to power grids introduced by renewable energy sources. This increases the demand for balancing mechanisms, which provide balancing power to ensure that power supply always meets with demand. However, the ability to provide cost-efficient and eco-friendly balancing power can vary significantly between locations. Fridgen et al. (2017) introduce an approach based on geographically distributed data centers, aiming at the spatial migration of balancing power demand between distant locations. Although their approach enables the migration of balancing demand to cost-efficient and/or eco-friendly balancing mechanisms, it will come up against limits if deployed on a global scale. In this paper, we extend Fridgen et al. (2017)’s approach by developing a model based on geographically distributed data centers, which not only enables the migration of balancing demand but also compensates for this migration when it is contradictory between different balancing power markets without burdening conventional balancing mechanisms. Using a simulation based on real-world data, we demonstrate the possibility to exploit the potential of compensation balancing demand offered by spatial load migration resulting in economic gains that will incentivize data center operators to apply our model.
http://hdl.handle.net/10993/44506
https://eref.uni-bayreuth.de/54945/

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