An illustration of the optimization of combined cooling heating and power systems using genetic algorithm. (May 2014)

• Record Type: Journal Article
• Authors: Wang, Jiangjiang; Yang, Kun; Zhang, Xutao; Shi, Guohua; Fu, Chao
• Is Part Of: Building services engineering research & technology. Volume 35:Number 3(2014)
• Page Start: 296
• Page End: 320
• Publication Date: 2014-05
• Subjects: Combined cooling heating and power system -- building type -- electric demand management -- thermal demand management; Buildings -- Environmental engineering -- Periodicals; Buildings -- Environmental engineering -- Research -- Periodicals; Sanitary engineering -- Periodicals; 696.05
• DOI: 10.1177/0143624413497734
• Languages: English
• ISSNs: 0143-6244

Abstract

The performances of combined cooling, heating and power (CCHP) system are greatly dependent on its design, operation strategy and thermal and electric demands. This paper illustrates how the use of a genetic algorithm can provide speedy optimization, by applying it to two styles of buildings operated in different operation strategies. The primary energy consumptions of CCHP system following electric demand management (EDM) and thermal demand management (TDM) are firstly analyzed respectively. Then, sixteen hypothetical buildings are constructed to represent various energy demands. Primary energy saving (PES), annual total cost saving (ATCS), and CO2 emission reduction (CO2 ER), are weighted to evaluate the integrated performances of CCHP system in comparison to separation production system. Finally, the optimized CCHP system for sixteen scenarios using GA are compared. Practical application: This paper provides an optimization design method for CCHP system. The performance analysis of CCHP systems running different operation modes for different buildings is believed by the authors to contribute to a significant guide for the fundamental design of CCHP systems. Although sensitivity to a number of other important design considerations such equipment performance, possible future changes in operating conditions, changes to the price or carbon intensity of grid-supplied energy etc are not addressed, the conclusions present a simple and effective direction and the proposed optimization algorithm and the evaluation method for CCHP system can be extended to other buildings.