Multi-objective approach in thermoenvironomic optimization of a small-scale distributed CCHP system with risk analysis

Multi-objective optimization for designing of a small-scale distributed CCHP system has been performed. Small-scale combined cooling, heating, and power generation technologies represent a key resource to increase generation efficiency and reduce greenhouse gas emissions with respect to conventional separate production means. In the multi-objective optimization of the small-scale distributed CCHP system, the three objective functions including the exergetic efficiency, total levelized cost rate of the system product and the cost rate of environmental impact have been considered. The environmental impact objective function has been defined and expressed in cost terms however this objective has not been integrated with the thermoeconomic objective. The thermodynamic modeling has been implemented comprehensively while the economic analysis conducted in accordance with the total revenue requirement (TRR) method. One of the most suitable optimization techniques namely as genetic algorithm has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. In the present work, reliability and availability are introduced in the thermoenvironomic model of the system, so that redundancy is embedded in the optimal solution. Risk analysis is used for decision-making of the final optimal solution from the obtained Pareto optimal frontier.

► This paper has presented a general methodology to optimize a CCHP system in urban areas under full-load operating condition.
► Evolutionary algorithm was utilized for multi-objective optimization.
► The comprehensive economic modeling according to the TRR method was implemented.
► For three objectives problem, risk analysis was used in decision-making process.
► The results of the closest point of Pareto Frontier to the equilibrium point and the best point chosen by risk analysis were compared.