Synthesis and dual-objective optimization of industrial combined heat and power plants compromising the water–energy nexus Academic Article uri icon

abstract

  • © 2018 Elsevier Ltd Water and energy are inextricably linked in various industrial applications. In a Rankine cycle-based combined heat and power plant, water is used as a working fluid for power generation and as a heat carrier. The water used as heat carrier is typically incompletely recovered. Therefore, a considerable amount of make-up water is required. Energy-intensive water treatment technologies are typically used given the strict quality requirements for boiler feed water. Thus, a systematic approach is required for the synthesis and optimization of water desalination and energy conversion processes. In this study, a novel water desalination system that couples thermal membrane distillation and reverse osmosis is proposed. A water-energy integration system that features strong nexus of water and energy is then developed. A dual-objective mathematical model is also formulated for the thermodynamic analysis and optimization of the novel system to minimize fuel and freshwater consumption. Furthermore, a case study is elaborated to validate the proposed novel integration system and optimization methodology. A sensitivity analysis of the key parameters on the performance of the novel system is also conducted. The water consumption objective optimization results show that the freshwater consumption of the proposed novel water-energy integration system is reduced by 54.8% compared with the conventional system. Similarly, the results achieved from minimizing the fuel consumption show that the fuel and freshwater consumptions of the proposed novel water-energy integration system are reduced by 1.7% and 21.0%, respectively, compared with those of the conventional system. The Pareto frontier achieved from the dual-objective optimization offers a trade-off between water and fuel consumption for the proposed water-energy integration system.

author list (cited authors)

  • Huang, X., Luo, X., Chen, J., Yang, Z., Chen, Y., Ponce-Ortega, J. M., & El-Halwagi, M. M.

citation count

  • 12

publication date

  • August 2018