Optimisation of cogeneration system design with extended automated targeting model (ATM)

In this work, a mathematical optimisation technique known as automated targeting model (ATM) was extended for techno-economic evaluation of gas turbine (GT), steam turbine and combined cycle CHP systems. The objective is to introduce a systematic methodology for rigorous targeting of steam and power generation from complex CHP systems. In particular, the non-linear model of GT was linearised and incorporated for use in ATM. The extended ATM was applied to target minimum total annualised cost (TAC) for CHP systems in various scenarios. The extended technique was demonstrated with case studies of glycerine distillation and oleochemical plants. For the glycerine distillation plant, the result showed that combined cycle CHP system is the most cost-effective and environmental friendly scheme for the scenario, with minimum TAC of $ 5,668,000/y and carbon footprint of 69,008 t CO(2)e/y. In Scenario 1 of the oleochemical plant case study, with constant steam and power demand, the result showed that GT-CHP is the most cost-efficient scheme with minimum TAC and carbon footprint of $ 2,184,000/y and 24,363 t CO(2)e/y respectively. Meanwhile, for Scenario 2 with fluctuating steam and power demand according to plant production capacity, which is more realistic, its minimum TAC for GT-CHP only increases by 2 %. The new approach allows the identification of the optimum mode of operation at different demand conditions.

Automated summary

This article introduces an extended mathematical optimization technique ATM, which is used for the techno-economic evaluation of gas turbines, steam turbines, and combined cycle CHP systems. The effectiveness of this technique is demonstrated through case studies, showing its ability to determine the optimum mode of operation under different demand conditions.