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Renewable and Sustainable Energy Reviews
Other literature type . Article . 2020
License: Elsevier TDM
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Article . 2020
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Virtual testbed for model predictive control development in district cooling systems

Authors: Zabala, Laura; Febres, Jesus; Sterling, Raymond; López, Susana; Keane, Marcus;

Virtual testbed for model predictive control development in district cooling systems

Abstract

Recently, with increasing cooling demands, district cooling has assumed an important role as it is more efficient than stand-alone cooling systems. District cooling reduces the environmental impact and promotes the use of renewable sources. Earlier studies to optimise the production plants of district cooling systems were focused primarily on plants with compressor chillers and thermal energy storage devices. Although absorption chillers are crucial for integrating renewable sources into these systems, very few studies have considered them from the cooling perspective. In this regard, this paper presents the progress and results of the implementation of a virtual testbed based on a digital twin of a district cooling production plant with both compressor and absorption chillers. The aim of this study, carried out within the framework of INDIGO, a European Union-funded project, was (i) to develop a reliable model that can be used in a model predictive controller and (ii) to simulate the plant using this controller. The production plant components, which included absorption and compressor chillers, as well as cooling towers, were built using the equation-based Modelica programming language, and were calibrated using information from the manufacturer, together with real operation data. The remainder of the plant was modelled in Python. To integrate the Modelica models into the Python environment, a combination of machine learning techniques and state-space representation models was used. With these techniques, models with a high computational speed were obtained, which were suitable for real-time applications. These models were then used to build a model predictive control for the production plant to minimise the primary energy usage. The improvements in the control and the resultant energy savings achieved were compared with a baseline case working on a standard cascade control. Energy savings up to 50% were obtained in the simulation-based experiments. The work leading to this research paper was out within the framework of the Project INDIGO, which had received funding from European Union's Horizon 2020 research and innovation programme, under grant agreement n° 696098. peer-reviewed

Country
Ireland
Subjects by Vocabulary

Microsoft Academic Graph classification: Chiller Primary energy Computer science Thermal energy storage Modelica Process engineering business.industry District cooling Renewable energy Model predictive control business Gas compressor

Keywords

POWER, DESIGN, PLANT, OPTIMIZATION, BUILDING ENERGY, Renewable Energy, Sustainability and the Environment, COMBINED HEAT, RENEWABLES, TECHNOLOGY INTEGRATION, OPERATION, COOLING SYSTEMS

60 references, page 1 of 6

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[2] International Energy Agency I. Tracking buildings. 2019. Paris.

[3] (IEA). IEA. The future of cooling. Opportunities for efficient air conditioning. 2018.

[4] Jakubcionis M, Carlsson J. Estimation of European Union residential sector space cooling potential. Energy Pol 2017;101:225-35. https://doi.org/10.1016/j. enpol.2016.11.047. [OpenAIRE]

[5] Gang W, Augenbroe G, Wang S, Fan C, Xiao F. An uncertainty-based design optimization method for district cooling systems. Energy 2016;102:516-27. https://doi.org/10.1016/j.energy.2016.02.107.

[6] IDEA. District cooling best practices guide. Westborough; 2008.

[7] Eveloy V, Ayou DS. Sustainable district cooling systems: status, challenges, and future opportunities, with emphasis on cooling-dominated regions. Energies 2019; 12:235. https://doi.org/10.3390/en12020235. [OpenAIRE]

[8] Rezaie B, Rosen MA. District heating and cooling: review of technology and potential enhancements. Appl Energy 2012;93:2-10. https://doi.org/10.1016/j. apenergy.2011.04.020.

[9] Eisentraut A, Adam B, International Energy Agency I. Heating without global warming. Featur Insight 2014:92.

[10] European Commission. An EU strategy on heating and cooling 2016, vol. 53; 2016. p. 1689-99. https://doi.org/10.1017/CBO9781107415324.004.

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  • citations
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    24
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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visibility
download
citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
OpenAIRE UsageCountsDownloads provided by UsageCounts
24
Top 10%
Average
Top 10%
165
156
Funded by
EC| INDIGO
Project
INDIGO
New generation of Intelligent Efficient District Cooling systems
  • Funder: European Commission (EC)
  • Project Code: 696098
  • Funding stream: H2020 | RIA
Validated by funder
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