Thermoeconomic and environmental analysis and multi-criteria optimization of an innovative high-efficiency trigeneration system for a residential complex using LINMAP and TOPSIS decision-making methods

A combined cooling, heating, and power integrated system suitable for a residential complex, with two new cycles in hot and cold seasons, is proposed and designed here. By a comprehensive modeling approach (in four aspects of energy, exergy, economic, and environmental), the integrated system is optimized for variable electrical, heating, and cooling loads during a year. Two objective functions (exergy efficiency, eta(Ex,tot), and relative annual benefit, RAB) and six design parameters are considered for multi-objective Genetic Algorithm optimization. Also, a novel variable operational price method during the system lifetime was applied. Optimization results showed that selecting 14 gas engines (with 912 kW nominal power output) and 9 backup boilers (with a heating capacity of 1450 kW) leads to 74% of overall thermal efficiency and 1.6 years' payback period for the above studied integrated system. Furthermore, the comparison of results in integrated and traditional (buying electricity from the grid and burning fuel in boiler for providing heat) systems showed a 2.46 x 10(7) m(3) year(-1) (68% in comparison with traditional system) saving in boiler fuel volume flow rate, a 2.11 x 10(6) $ year(-1) saving in boiler fuel cost, a 4.55 x 10(8) kg year(-1) (87.5% in comparison with traditional system) reduction in CO, CO2 and NOx emissions and a 9.46 x 10(6) $ year(-1) reduction in its corresponding penalty cost.

Automated summary

A combined cooling, heating, and power integrated system suitable for a residential complex was proposed and optimized through a comprehensive modeling approach. The selection of 14 gas engines and 9 backup boilers led to an overall thermal efficiency of 74% and a payback period of 1.6 years. The integrated system also showed significant savings in fuel volume flow rate, fuel cost, and reductions in emissions compared to traditional systems.