Table 1.
Classification of specialized literature in the proposed research area.
Fig 1.
Graphical conceptual model for proposed optimization.
Table 2.
Cost-benefit summary for the 33-bus system (10-year horizon).
Table 3.
Comparison of optimization methods (IEEE 118-bus network).
Table 4.
Comparison of key features of optimization algorithms.
Table 5.
Amounts of consumption and generation in every hour of the day for 33-Bus System.
Table 6.
Hourly consumption and generation in the 69-bus system.
Table 7.
Hourly consumption and production in the 118-bus system.
Table 8.
Total power generation and associated costs for 33-bus, 69-bus, and 118-bus networks from simulation results.
Fig 2.
Solar irradiance (W/m2) across different hours of the day.
Fig 3.
Hourly temperature (°C) data throughout the day.
Fig 4.
Wind speed (m/s) at different hours of the day.
Fig 5.
Total loads with uncertainty (kW) in each hour of the day.
Fig 6.
Input loads with uncertainty (kW) over a 24-hour period.
Fig 7.
Distribution of input loads with uncertainty (percentage).
Fig 8.
The amount of consumption and production in each hour of the day.
Fig 9.
Demand load before and after implementing the demand response program.
Table 9.
Objective and technical parameters in the 33-bus system.
Table 10.
Objective and technical parameters in the 69-bus system.
Table 11.
Objective and technical parameters in the 118-bus system.
Table 12.
EENS before and after implementation of the proposed optimization framework.
Fig 10.
VD before and after program implementation.
Fig 11.
Comparison of active losses before and after the implementation of the optimal management program.
Fig 12.
Comparison of reactive losses before and after the implementation of the optimal management program.
Table 13.
Performance metrics under different res penetration levels.