Influence analysis of building energy demands on the optimal design and performance of CCHP system by using statistical analysis

• Published in: Energy and buildings Vol. 153; pp. 297 - 316
• Main Authors: Yang, G., Zheng, C.Y., Zhai, X.Q.
• Format: Journal Article
• Language: English
• Published: Lausanne Elsevier B.V 15-10-2017; Elsevier BV
• Subjects: Building design; Buildings; Climate; Climate zone; Combined cooling heating and power; Commercial building; Design engineering; Design parameters; Energy consumption; Energy demand; Energy modeling; Energy storage; Environmental management; Environmental performance; Health care; Multivariate regression; Multivariate statistical analysis; Performance indices; Regression analysis; Regression models; Statistical analysis; Statistical methods; Statistics; Thermal energy; United States > US; Climate zone; Multivariate regression; Commercial building; Multivariate statistical analysis; Combined cooling heating and power
• ISSN: 0378-7788; 1872-6178
• DOI: 10.1016/j.enbuild.2017.08.015

•The statistical methods are used in the influence analysis of the optimal design and performance of CCHP systems.•The regression models between building energy demand indexes and the design and performance parameters are built.•The design and performance features of CCHP systems for 16 building across 7 climate zones are analyzed.•Some instructive conclusions on the promotion of CCHP systems are summarized.
Combined cooling, heating and power (CCHP) is a promising technology to provide energy for various energy consumers for its good economic, energy and environmental performance. However, the widely promotion of CCHP is hindered by its complex design and varying performance under different situations. In this paper, the influence of energy demands, operation strategy and thermal energy storage strategy on optimal design and performance of CCHP systems is studied by using statistical methods 13,472 energy demand samples for 16 types of building across 7 climate zones in the U.S. are used in the paper. On the whole, building energy demands are the most influential factor. Among the building types, the performance of large hotel, hospital and outpatient healthcare is outstanding. Among the climate zones, CCHP systems have better performance in cold and very cold climate zones. For operation strategies, the ATCSR and PESR values of the FTL mode are averagely less than those of the FEL mode, and the differences between the two modes for ATCSR and PESR are on average 0.25% and 1.03%, respectively. Besides, the use of thermal energy storage can improve the integrated performance of CCHP. In the FEL-TES mode, the average increments of ATCSR and PESR are 0.82% and 0.79%, respectively. In the FTL-TES mode, the average increments of ATCSR and PESR mode can reach 3.42% and 3.46%, respectively. The relationship between building energy demand indexes and the design and performance parameters of the CCHP is also explored by stepwise regression method to build regression models and determine the most effective parameters.