A hierarchical framework for holistic optimization of the operations of district cooling systems

Chiam, Zhonglin; Easwaran, Arvind; Mouquet, David; Fazlollahi, Samira; Millás, Jaume V.

doi:10.1016/j.apenergy.2019.01.134

Cited by 41 publications

(14 citation statements)

References 21 publications

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“…The mathematical model of cooling load description is not given in the data driven method. Based on the input variables of historical data (e.g., heat source, environmental parameters and occupancy), the nonlinear dynamic model of cooling load under various disturbances is established by mixed integer linear program [ 41 ] and deep reinforcement learning [ 42 ].…”

Section: Operation Control Strategies For Hub Airport Terminalsmentioning

confidence: 99%

Strategical district cooling system operation in hub airport terminals, a research focusing on COVID-19 pandemic impact

Yan

Yang²,

He³

et al. 2022

Energy

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Section: Operation Control Strategies For Hub Airport Terminalsmentioning

confidence: 99%

Strategical district cooling system operation in hub airport terminals, a research focusing on COVID-19 pandemic impact

Yan

Yang²,

He³

et al. 2022

Energy

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“…As discussed in the literature review and from Table 1, at the time of writing, most urban energy systems modelling focuses on the provision of some energy service demands within heating, cooling, transport, and electricity for appliances; or uses coarse spatial resolutions such as integrated assessment models, which model national or regional scales (such as the MARKAL model [34], the ESME model [50] or the TIMES model [24]); or focus on specific technologies or on specific energy service demands (for example, Chiam, Easwaran, Mouquet, Fazlollahi, and Millás [51] optimise the operation of a district cooling network; del Hoyo Arce, Herrero López, López Perez, Rämä, Klobut, and Febres [52] model district heating and cooling; Pye and Daly [25] focus on urban transport; and Liu, Ho, Lee, Hashim, Lim, Klemeš, and Yee Mah [53] model distributed generation for supplying service demands for heat and electricity). No modelling framework exists that simultaneously includes the demand for heating, cooling, transport, and electricity for appliances, at a fine spatial resolution, and taking into account the trade-offs between supply, network infrastructure, and end-use technologies for all the aforementioned energy service demands simultaneously.…”

Section: Research Objectivementioning

confidence: 99%

Spatially-resolved urban energy systems model to study decarbonisation pathways for energy services in cities

2020

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This work presents the COMET (Cities Optimisation Model for Energy Technologies) model, a spatially-resolved urban energy systems model that takes into account energy service demands for heating, cooling, electricity, and transport, and finds cost-effective pathways for supplying these demands under carbon constraints, trading-off energy supply, network infrastructure, and end-use technologies. Spatially-resolved energy service demands were obtained for the city of Sao Paulo, and six scenarios were modelled. Results show that district cooling is cost-effective in the highest linear cooling density zones, with full penetration in zones with over 1100 kWh/m by 2050. This threshold diminishes with tighter carbon constraints. Heating is electrified in all scenarios, with electric boilers and air-source heat pumps being the main supply technologies for the domestic and commercial sectors respectively by 2050. In the most carbon constrained scenario with a medium decarbonised electricity grid, ground source heat pumps and hydrogen boilers appear as transition technologies between 2030 and 2045 for the commercial and domestic sectors respectively, reaching 95% and 40% of each sector's heat installed capacity in 2030. In the transport sector, ethanol cars replace gasoline, diesel, and compressed natural gas cars; compressed natural gas buses replace diesel and electric buses; and lorries continue using diesel. In carbon constrained scenarios, higher penetrations of electric cars and buses are obtained, while no change is observed for lorries. Finally, the most expensive scenario was only 6% more expensive than the reference scenario, meaning that achieving decarbonisation targets is not much costlier when comparing scenarios from a system-wide perspective.

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“…These statistics are even more valid in regions with tropical climates [5]. For instance, the percentage of energy used for space cooling in Mumbai (40%) is nearly as twice as that of London (20%) [6].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, it has to be considered that the temperature difference between the supply water temperature and the return water temperature for DCSs is usually around 8 • C, while in district heating systems the difference is generally higher than 40 • C [3]. Additionally, the tendency to be cautious in the design phase leads often to oversize DCSs, thus resulting in equipment underutilization, which is detrimental for energy efficiency [6]. For all these reasons, DCSs show an increase of the piping system cost and of the required pumping energy respect to district heating systems [3].…”

Section: Introductionmentioning

confidence: 99%

Potential of District Cooling Systems: A Case Study on Recovering Cold Energy from Liquefied Natural Gas Vaporization

et al. 2019

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District cooling systems (DCSs) are networks able to distribute thermal energy, usually as chilled water, from a central source to industrial, commercial, and residential consumers, to be used for space cooling/dehumidification. As cooling demand will increase significantly in the next decades, DCSs can be seen as efficient solutions to improve sustainability. Although DCSs are considered so relevant for new city developments, there are still many technical, economic, and social issues to be overcome to let such systems to spread out. Thus, this paper aims to highlight the advantages and issues linked to the adoption of DCSs for building cooling when cold is recovered from a specific application. A case study based on liquified natural gas (LNG) cold energy recovery from the transport sector is presented. Starting from the estimation of the free cooling availability, a DCS design method is proposed and the potential energy saving is investigated. Results show that a DCS using the cold waste derived from LNG can provide a relevant amount of electricity saving (about 60%) for space cooling compared to traditional solutions, in which standard air conditioning systems are installed in every building.

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A hierarchical framework for holistic optimization of the operations of district cooling systems

Cited by 41 publications

References 21 publications

Strategical district cooling system operation in hub airport terminals, a research focusing on COVID-19 pandemic impact

Strategical district cooling system operation in hub airport terminals, a research focusing on COVID-19 pandemic impact

Spatially-resolved urban energy systems model to study decarbonisation pathways for energy services in cities

Potential of District Cooling Systems: A Case Study on Recovering Cold Energy from Liquefied Natural Gas Vaporization

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