| Reference | Components | Objective function | Processing method for multiobjective function |
| [9] | PV and ESS | Cost of power exchanged with other local microgrids and the grid | Sum of the cost method | [10] | DG, BESS, and microgrid | Determine the lifetime of BESS and the cost of microgrids functioning | Weighted summation method | [12] | DGs and grid | Active power loss, reactive power loss, and the voltage deviation index | Weighted summation method | [18] | DG, PV, ESS, EV, HVACs, and other RLs | Maximizing TVPP’s day-ahead and intraday profit in the flexible market | Two-stage adaptive robust optimization | [19] | DN, WIND, PV, ESS, PEMFC, EB, GB, TR, and HS | Carbon trading cost, operational cost, maintenance cost, and rescheduling cost | Two-stage distributionally robust optimization | [21] | DG, renewable energy, ES, and grid | Line loss rate, renewable energy abandonment power penalty item, and ESS residual penalty item | Multistage decoupling structure based on extreme scenario evaluation | [26] | PV, ESS, EV, and grid | Maximizing the profit and minimizing the peak-to-valley difference of the load and loss rate of ESS | MOMUS + TOPSIS | [28] | PV, WIND, BESS, EV, TL, IL, and grid | Maximizing the benefits of GS and maximizing the benefits of LS | NSGA-II + TOPSIS | [32] | DG, ESS, PV, WIND, and grid | Annual energy losses, annual investment, maintenance, and operation costs and reliability | Multi-objective sine-cosine algorithm | This study | PV, wind, DG, and BESS | Line loss, maximum voltage deviation, abandoned amount of new energy, and power generation cost | A two-stage optimization based on expected point tolerance |
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