Load-based testing of heating and cooling equipment informed by detailed energy models.

Summary

Load-based testing is an emerging approach for evaluating and rating heating and cooling equipment by simulating the transient nature of loads in the lab to emulate real world operating conditions as closely as possible. These test methods aim to generate more accurate performance data (e.g., coefficient of performance) that can be translated into useful ratings to compare disparate equipment, as well as performance maps that can be directly used with building energy modeling software. There are several industry and academic efforts to develop these procedures such that they may someday replace existing methods of testing and rating HVAC&R equipment.
One of the approaches for load-based tests is to couple the laboratory equipment to detailed building energy modeling software in a “Hardware-in-the-Loop” type system. The building energy models accept integrated energy input and output from the tested equipment and output information about the building’s thermal response (e.g., indoor air temperature change) This information is then used to control the return air/water conditions and/or to simulate thermostat calls. This type of approach can be complex but potentially offers the most accurate representation of real loads. Reduced order building models offer a much simpler approach for integration but are challenged by very rough approximations of the building and loads. In this paper, a hybrid approach is presented that uses a lumped heat capacitance approach for load-based testing in the lab but informs the necessary parameters from detailed building energy simulations. This approach was applied to evaluating part-load operation of a condensing modulating furnace operated under different control strategies, with results presented in this paper. The features, benefits, as well as limitations of this approach are also discussed.

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Details

  • Original title: Load-based testing of heating and cooling equipment informed by detailed energy models.
  • Record ID : 30030666
  • Languages: English
  • Subject: Technology
  • Source: 2022 Purdue Conferences. 19th International Refrigeration and Air-Conditioning Conference at Purdue.
  • Publication date: 2022

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