Two-Layer Optimization Method for Sharing Energy Storage and Energy considering Subjectivity
Algorithm 1
The Process of the Nested Algorithm.
Step 1: Load basic information and initialize parameters of the upper-level optimization.
Initialize n=0.
Initialize the NSGA-II parameters according to Table 1.
Step 2: Randomly generate the 0th population.
Stochastically generate Ecap.
Step 3:Initialize parameters of the lower level optimization.
Initialize .
Initialize =0, =max (If ≥0) or =min (If <0).
Initialize and .
Step 4: Optimize the lower-level model.
Solve optimization models (22) and (23) to obtain and by using solvers of Gurobi 9.0.3. The target vector () is constant in the child layer, and the result vector () is constant in the parent layer
Step 5: Check the stop criterion of the lower optimization.
If formula (27) is met, go to Step 7; otherwise go to Step 6.
Step 6: Update parameters of the lower optimization.
Update the Lagrange multipliers with formulas (28) and (29).