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Study: Low-energy heating and cooling systems can deliver deep energy savings

Study: Low-energy heating and cooling systems can deliver deep energy savings

Cover of Energy Conversion and Management

Energy Conversion and Management

Amy Allen came to ²ÊÃñ±¦µä to study building energy systems and how buildings and other electrical loads interact with the grid. As a PhD candidate under Professor Gregor Henze and Assistant Professor Kyri Baker in the Department of Civil, Environmental and Architectural Engineering, she is working with some of the best in building systems. Allen is the first author on recently published in Energy Conversion and Management.

We asked her a few questions about the work and how it may influence climate change. 

Question: How would you describe the work and results of this paper? What is the real-world application of this work?
Answer: My work involves using computer simulations to model energy use of buildings and district thermal energy systems and analyzing the resulting data to answer research questions. 

A district thermal energy system circulates water or steam through a network to connected buildings, which use the fluid for heating and or cooling. If district thermal energy systems that operate at close to air temperatures—so-called "ambient loops"—are adopted at a large scale in suitable applications, they would have the potential to achieve significant reductions in the carbon intensity of heating and cooling for the connected buildings. This is an essential step in fighting climate change.

The research described in this paper evaluated the potential energy savings from that particular type of system for heating and cooling buildings through use of water as well as a design approach for networks to heat and cool an entire neighborhood or "district," that would be well-suited for use with the building-level system. The results suggest that this design approach is valid, and that there are significant potential energy savings from implementation of these systems. 

Q: Why is this an interesting research question for you? Was this something you wanted to research before coming to ²ÊÃñ±¦µä?
A: This is an interesting research question for me because of its relevance to lowering the energy intensity of building HVAC systems, the greater integration of waste heat and renewable thermal sources, and electrification of building heating, especially in the context of increasing levels of penetration of renewable electric generation, all of which contribute to reducing carbon emissions.

Q: What research questions are still to be answered after this paper? Where will the work go from here?
A: Since the completion of this paper, the heuristic for the design of district thermal energy systems has been validated on a larger prototypical district. Work is currently ongoing to investigate the use of particle swarm optimization for the network topology problem. This paper is part of a larger effort to develop a topology optimization framework for district thermal energy systems.

Q: You are graduating soon. What do you have planned for the future?
A: I'd like to do work that can contribute to reducing carbon emissions from building operations in research or industry. 

The ²ÊÃñ±¦µä authors include Amy Allen, Gregor Henze, and Kyri Baker, with external author is Greg Pavlak of Pennsylvania State University. Funding acknowledgement: This work was authored in part by the National Renewable Energy Laboratory, operated by Alliance for Sustainable Energy, LLC, for the U.S. Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. Funding provided by the Building Technologies Office and the Advanced Manufacturing Office. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this work, or allow others to do so, for U.S. Government purposes. The assistance of Nicholas Long of the National Renewable Energy Laboratory in generating building load profiles using the metamodeling framework is gratefully acknowledged.