Optimization of Cooling Utility System with Continuous Self-Learning Performance Models

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F19%3APU134532" target="_blank" >RIV/00216305:26210/19:PU134532 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/1996-1073/12/10/1926" target="_blank" >https://www.mdpi.com/1996-1073/12/10/1926</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/en12101926" target="_blank" >10.3390/en12101926</a>

Result language

angličtina

Original language name

Optimization of Cooling Utility System with Continuous Self-Learning Performance Models

Original language description

Prerequisite for an efficient cooling energy system is the knowledge and optimal combination of different operating conditions of individual compression and free cooling chillers. The performance of cooling systems depends on their part-load performance and their condensing temperature, which are often not continuously measured. Recorded energy data remain unused, and manufacturers' data differ from the real performance. For this purpose, manufacturer and real data are combined and continuously adapted to form part-load chiller models. This study applied a predictive optimization algorithm to calculate the optimal operating conditions of multiple chillers. A sprinkler tank offers the opportunity to store cold-water for later utilization. This potential is used to show the load shifting potential of the cooling system by using a variable electricity price as an input variable to the optimization. The set points from the optimization have been continuously adjusted throughout a dynamic simulation. A case study of a plastic processing company evaluates different scenarios against the status quo. Applying an optimal chiller sequencing and charging strategy of a sprinkler tank leads to electrical energy savings of up to 43%. Purchasing electricity on the EPEX SPOT market leads to additional costs savings of up to 17%. The total energy savings highly depend on the weather conditions and the prediction horizon.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20402 - Chemical process engineering

Project

<a href="/en/project/EF15_003%2F0000456" target="_blank" >EF15_003/0000456: Sustainable Process Integration Laboratory (SPIL)</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

ENERGIES

ISSN

1996-1073

e-ISSN

—

Volume of the periodical

10

Issue of the periodical within the volume

12

Country of publishing house

CH - SWITZERLAND

Number of pages

10

Pages from-to

1926-1935

UT code for WoS article

000471016700105

EID of the result in the Scopus database

2-s2.0-85066779577