Authors:
Sebastian Thiem
1
;
Alexander Born
2
;
Vladimir Danov
2
;
Jochen Schäfer
2
and
Thomas Hamacher
3
Affiliations:
1
Siemens AG and Technische Universität München, Germany
;
2
Siemens AG, Germany
;
3
Technische Universität München, Germany
Keyword(s):
Multi Modal Energy Systems, Smart Grid, Cold Thermal Energy Storage, Ice Storage, Chilled Water Storage, Energy Management, Dynamic Programming, Optimal Control.
Related
Ontology
Subjects/Areas/Topics:
Energy and Economy
;
Energy Management Systems (EMS)
;
Energy-Aware Systems and Technologies
Abstract:
Smart management of cold thermal energy storages could help future sustainable energy systems drawing
large shares of electricity from renewable sources to balance fluctuating generation. This paper introduces a
model-based predictive control strategy for cold thermal energy storages. A novel ice storage model for
simulating and optimizing partial charge and discharge storage operation is developed and validated. The
optimization problem is solved using a Forward Dynamic Programming approach. A case study analysis for
a very hot and humid location (Miami) and a rather temperate climate (Los Angeles) and for each four
building types (apartment building, hospital, office, and school) reveals that total cost savings of up to 20%
compared to conventional control strategies are possible.