Article (Scientific journals)
Demand response through automated air conditioning in commercial buildings—a data-driven approach
Drasch, Benedict J.; Fridgen, Gilbert; Häfner, Lukas
2020In Business Research, 13 (3), p. 1491--1525
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Abstract :
[en] Building operation faces great challenges in electricity cost control as prices on electricity markets become increasingly volatile. Simultaneously, building operators could nowadays be empowered with information and communication technology that dynamically integrates relevant information sources, predicts future electricity prices and demand, and uses smart control to enable electricity cost savings. In particular, data-driven decision support systems would allow the utilization of temporal flexibilities in electricity consumption by shifting load to times of lower electricity prices. To contribute to this development, we propose a simple, general, and forward-looking demand response (DR) approach that can be part of future data-driven decision support systems in the domain of building electricity management. For the special use case of building air conditioning systems, our DR approach decides in periodic increments whether to exercise air conditioning in regard to future electricity prices and demand. The decision is made based on an ex-ante estimation by comparing the total expected electricity costs for all possible activation periods. For the prediction of future electricity prices, we draw on existing work and refine a prediction method for our purpose. To determine future electricity demand, we analyze historical data and derive data-driven dependencies. We embed the DR approach into a four-step framework and demonstrate its validity, utility and quality within an evaluation using real-world data from two public buildings in the US. Thereby, we address a real-world business case and find significant cost savings potential when using our DR approach.
Disciplines :
Computer science
Management information systems
Energy
Author, co-author :
Drasch, Benedict J.
Fridgen, Gilbert  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > FINATRAX
Häfner, Lukas
External co-authors :
yes
Language :
English
Title :
Demand response through automated air conditioning in commercial buildings—a data-driven approach
Publication date :
2020
Journal title :
Business Research
ISSN :
2198-2627
Publisher :
SpringerOpen, Switzerland
Volume :
13
Issue :
3
Pages :
1491--1525
Peer reviewed :
Peer Reviewed verified by ORBi
Focus Area :
Security, Reliability and Trust
Sustainable Development
FnR Project :
FNR13342933 - Paypal-fnr Pearl Chair In Digital Financial Services, 2019 (01/01/2020-31/12/2024) - Gilbert Fridgen
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