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Optimal sequencing of chillers and boilers based on short-term energy demand forecasts represents an untapped opportunity to improve the energy efficiency of central heating and cooling plants. This paper presents a case study conducted in a heating and cooling plant with four boilers and five chillers. Time-series modeling methods are examined to forecast hourly heating and cooling loads 24 hours in advance. The results indicate thatahybrid of autoregressivemovingaverage and change-point models can parsimoniously predict the heating and cooling loads. A boiler and chiller sequencing scheme that uses the day-ahead load forecasts is determined by using a nonlinear programming solver. The implementation of this sequencing scheme is estimated to result in a 4% reduction in heating and 25% reduction in cooling energy use.
Citation: 2019 Annual Conference, Kansas City, KS, Technical Papers
Product Details
- Published:
- 2019
- Number of Pages:
- 11
- Units of Measure:
- Dual
- File Size:
- 1 file , 2.4 MB
- Product Code(s):
- D-KC-19-005
