Use Case 4: Supporting Data-Driven Space Cooling Interventions for Technicians
Target Users
Renewable energy communities, engineers, energy consultants.
User Story Description
More and more technicians need data to measure buildings’ energy consumption and cooling needs to design effective interventions. The consortium should decide if the CoolLIFE tool will be able to provide this kind of data and therefore target the designers of interventions.
Research Question
How can space cooling data be utilized to support engineers and energy consultants in designing effective cooling interventions based on building energy consumption and demand patterns?
Calculation Module Use and Order
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Technology and Measures: The first step in designing effective cooling interventions is quantifying the energy consumption associated with different cooling technologies. The Technology and Measures Calculation Module allows users to estimate electricity consumption for space cooling by considering cooling degree days and system efficiency. This module provides a scenario-based assessment of cooling demand under different technology adoption and efficiency improvement scenarios, helping engineers and energy consultants determine optimal cooling strategies for various building types.
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District Cooling: For certain buildings or areas with high cooling demand density, centralized district cooling may offer a more efficient solution than decentralized cooling units. The District Cooling Calculation Module enables users to assess the feasibility of district cooling grids by spatially identifying regions where district cooling networks could be implemented. This module supports engineers in evaluating whether district cooling is a viable option for specific locations, helping them design interventions that maximize system efficiency and minimize energy costs.
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Economic Feasibility: To ensure that proposed cooling interventions are financially viable, the Economic Feasibility Calculation Module allows users to compare different passive cooling measures and active cooling technology development scenarios. By analyzing the costs of various cooling solutions at the national and building archetype levels, engineers and energy consultants can identify the most cost-effective measures. This module supports decision-making by providing a financial comparison of different energy efficiency improvements, ensuring that interventions are both technically and economically feasible.
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Demand-Side Management: Integrating renewable energy sources into space cooling solutions requires understanding how cooling demand can be optimized through demand-side flexibility. The Demand-Side Management Calculation Module evaluates demand response potential and PV self-consumption for cooling. By shifting cooling demand to better align with renewable energy generation, this module helps engineers develop strategies that reduce reliance on grid electricity while improving energy efficiency. This is particularly valuable for designing interventions that incorporate on-site renewable energy sources.
By systematically applying these calculation modules, engineers, energy consultants, and renewable energy communities can access the necessary data to design effective cooling interventions. This structured approach enables them to assess technology impacts, evaluate district cooling feasibility, ensure financial viability, and integrate demand-side flexibility into cooling strategies. The result is a data-driven methodology for optimizing space cooling solutions, improving energy efficiency, and supporting the transition to sustainable cooling technologies.
How To Cite
Aadit Malla, in CoolLIFE-Wiki, User Story 4: Supporting Data-Driven Space Cooling Interventions for Technicians
Authors And Reviewers
This page was written by Aadit Malla EEG-TU WIEN.
This page was reviewed by Ardak Akhatova e-think.
License
Copyright © 2024-2025: Aadit Malla
Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons CC BY 4.0 International License.
SPDX-License-Identifier: CC-BY-4.0
License-Text: https://spdx.org/licenses/CC-BY-4.0.html
Acknowledgement
We would like to convey our deepest appreciation to the LIFE Programme CoolLIFE Project (Grant Agreement number 101075405), which co-funded the present investigation.