Multi-scale smart management of integrated energy systems, Part 2: Weighted multi-objective optimization, multi-criteria decision making, and multi-scale management (3M) methodology

[Display omitted] •A smart multi-scale management approach (3M) is proposed for optimal energy systems.•Real world policies were adopted with conceptual exergy-based models in 3 scenarios.•Comparative exergorisk, exergoeconomic, and exergorisk analyses are performed.•Novel weighted multi-objective optimization is applied to model-based systems.•Optimal system configuration with best organic fluid is selected using fuzzy-TOPSIS. A novel smart management approach is proposed for optimization, management, and analysis of integrated energy systems considering contemporary economic, safety, and environmental policies referred to as 3M methodology. Accordingly, three key scenarios are defined including an urban plant application (S-I), a domestic economic growth policy (S-II), and a sustainable development plan (S-III). The proposed systems are globally optimized considering exergoeconomic, exergorisk, and exergoenvironmental analyses using a weighted multi-objective optimization in accordance with the circumstances of S-I, S-II, and S-III. Subsequently, a suitable optimal system is selected using a hybrid deterministic fuzzy-TOPSIS approach among optimal configurations, and the best working fluid is allocated via system-based multi-scale management. The MGS allocating R718, R141b, R123, R142b, and R365mfc had smaller total environmental impact rate, smaller total cost rate, lower heat losses, and lower consumption of cold utility in all scenarios compared to the CGS. In turn, the CGS allocating R718 had the smallest total specific risk (0.602 injury.MJ−1) in the S-I than the MGS (0.811 injury.MJ−1). However, the MGS allocating R123 had a lower consumption of cold utility in the S-II (3.92 MW) and S-III (3.90 MW).