**5. Performance of TVMS-BPSO**

To evaluate the capabilities of TVMS-BPSO presented in Section 3.2 for day-ahead BESS scheduling, the conditions of Case I (low wind speed with fully charged battery) previously described in Section 4.1 have been considered. This case has been chosen because the number of optimization variables to be determined is the highest. Regarding the number of agents and iterations, these have been set equal to the population size and generations of GA previously implemented in Section 4 (75 agents and 100 iterations), and this guarantees a fair comparison between both methods. Other parameters of BPSO have been adjusted as follows; *CaPSO*= 2.05, *CbPSO*= 2.05, σ*min* = 0.1, and σ*max* = 1.

Figures 31–33 show the comparison between GA and TVMS-BPSO for di fferent wind speed profiles, whereas Table 13 shows the value of the objective function. As can be observed, TVMS-BPSO employs global exploration during the first iterations, analyzing solutions with high objective function value. As the algorithm evolves, exploitation has the relevant role of guiding the algorithm to a high quality solution, comparable to that obtained from GA implementation, according to Table 13.


**Table 13.** Comparison of objective function values.

**Figure 31.** TVMS-BPSO evolution for diurnal pattern strength equal to 0.

**Figure33.**X.TVMS-BPSOevolutionfordiurnalpatternstrengthequalto0.3and0.4.
