Peak Shaving in District Heating Utilizing Adaptive Predictive Control

District heating systems (DHS) are driven by the heat demands of their consumers, with higher demands giving a higher load on the heat production. While heat demands are human-dependent, they contain diurnal behaviors and weather dependencies. The diurnal behaviors contain periods with high demands...

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Bibliographic Details
Published inEnergies (Basel) Vol. 15; no. 22; p. 8555
Main Author Svensen, Jan Lorenz
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.11.2022
Subjects
adaptive control
Analysis
Clean energy
data-driven modeling
District heating
Diurnal
Energy consumption
Flow velocity
Heat
Heat exchangers
Heat pumps
Heat storage
Heating
Heating from central stations
Heating systems
Houses
Load
Load distribution
MPC
Peak load
Supply and demand
Denmark
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Summary:District heating systems (DHS) are driven by the heat demands of their consumers, with higher demands giving a higher load on the heat production. While heat demands are human-dependent, they contain diurnal behaviors and weather dependencies. The diurnal behaviors contain periods with high demands causing peak loads on the heat production, which is operationally costly. This is especially true for heat pumps, a solution for DHS to include green energy, as the cost depends directly on the needed temperature. This paper presents a formulation of adaptive model predictive control (MPC) for inducing peak shaving on the production load to handle the peak load problem by using the DHS distribution network as a heat storage. It also presents a simulator model to describe the DHS. The MPC was applied to data from a case study of the DHS in Brønderslev, Denmark, showing a peak reduction of around 8%.
ISSN:1996-1073
1996-1073
DOI:10.3390/en15228555