Feasibility Analysis of the Operation Strategies for Combined Cooling, Heating and Power Systems (CCHP) based on the Energy-Matching Regime

• Published in: Journal of thermal science 2020-10, Vol.29 (5), p.1149-1164
• Main Authors: Feng, Lejun, Dai, Xiaoye, Mo, Junrong, Shi, Lin
• Format: Article
• Language: English
• Subjects: Classical and Continuum Physics; Design factors; Design parameters; Electric power systems; Energy; Energy conservation; Engineering Fluid Dynamics; Engineering Thermodynamics; Feasibility studies; Heat and Mass Transfer; Heating; Matching; Physics; Physics and Astronomy; Thermal analysis
• ISSN: 1003-2169; 1993-033X
• DOI: 10.1007/s11630-020-1314-2

Although numerous studies have considered the two traditional operation strategies: following the electric load (FEL) and following the thermal load (FTL), for combined cooling, heating, and power (CCHP) systems in different case studies, there are limited theoretical studies on the quantification methods to assess the feasibility of these two strategies in different load demands scenarios. Therefore, instead of a case study, we have undertaken a theoretical analysis of the suitable application scenarios for FEL and FTL strategies based on the energy-matching performance between systems’ provision and users’ demands. To compare the calculation models of energy saving rate (ESR) for FEL and FTL strategies in the left and right sub-regions of the energy-supply curve, a comprehensive parameter ( χ ) that combines three inherently influential factors (off-design operation parameter, energy-matching parameter, and install capacity coefficient) is defined to determine the optimal installed capacity and feasibility of FEL or FTL strategies quantitatively. The results indicate that greater value of χ will contribute to a better energy saving performance, and FEL strategy shows better performance than FTL in most load demands scenarios, and the optimal installed capacity occurs when the load demand points were located in different regions of the energy-supply curve. Finally, taking a hotel in Beijing as an example, the value of the optimal install capacity coefficient is 0.845 and the FEL strategy is also suggested, and compared to the maximum install capacity, the average values of the ESR on a typical summer day, transition season, and winter can be enhanced by 3.9%, 8.8%, and 1.89%, respectively.