Predicting central plant HVAC equipment performance using neural networks -- Laboratory system test results
Conference
·
OSTI ID:653192
- Univ. of Colorado, Boulder, CO (United States)
- Architectural Energy Corp., Boulder, CO (United States)
Adaptive and predictive neural network models have been developed for a chiller and ice thermal storage tank of a central plant HVAC system. With relatively few input parameters, equipment performance is modeled without the use of first principles. Once trained, the models quickly predict output with relatively few calculations and self-calibrate, making them ideal for use with real systems that use adaptive and predictive controllers. The models are suitable for computer simulation or with actual systems.
- Sponsoring Organization:
- Department of the Army, Washington, DC (United States)
- OSTI ID:
- 653192
- Report Number(s):
- CONF-980123--
- Country of Publication:
- United States
- Language:
- English
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